Ocean Protocol Subtitles (English)

Julia Reinhardt - What do GDPR and AI regulations mean for Silicon Valley?.vtt

WEBVTT

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As a matter of principle, I don't 
believe regulation stifles innovation.

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Very often in my daily life, 
I work with technologies 

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who feel that, actually, 
regulation gives them some

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guard rails that they actually 
appreciate, as a matter of fact.

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I think on the contrary, smart 
regulation that gets out in front 

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of emerging technology can protect 
consumers and drive innovation.

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So my focus is on protecting consumers and 
that I think is the most important thing.

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I mean we're not just a huge 
couple billion of mice in a lab, 

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we are people with rights and dignity.

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This is season two of Voices of the Data Economy,
a podcast supported by Ocean Protocol Foundation.

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We bring to you the voices 
shaping the Data Economy 

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and challenging it at the same time. 
Listen to founders,

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tech policy experts and 
pioneers in impact investing.

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All sharing their relationship with data.

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So hello and welcome, 
today we have Julia with us.

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She is a privacy professional 
and AI governance expert.

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She's also a Mozilla Fellow 
in Residence and has been 

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a German diplomat in the past, 
so a very versatile profile.

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Hello, Julia.

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Hi, Diksha.

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Hi, I'm sorry, I said it wrong.

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Hello, Julia. I always...

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I have American friends and German friends
and it's always confusing but here we are, Julia.

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Exactly, fine.

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So, you are in Germany today.

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Yes, I am. I am normally based in San Francisco
but for the first time since the pandemic started,

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I was able to travel and
I'm really happy to be 

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here and see everybody again 
after such a long time,

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but I will go back to San Francisco 
again in a couple of weeks.

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Yeah, summer is always a great 
time to be here in Germany.

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And it's not the best time in San Francisco.

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I think somebody said that nothing 
is worse or colder than  

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summer in San Francisco because of the fog.

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Okay, great, so you have 
the best of both worlds.

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And okay, so coming back to your profile.

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So tell us a little bit 
about your journey from being 

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a German diplomat to now 
an advisor in data policy

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and regulations in the US.

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I mean it's a very interesting shift.

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How did one thing lead to another 
and you are doing what you are doing?

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Yeah, maybe a red thread has 
always been that I always want 

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to work on things that matter. 
I enjoy cross-functional work most.

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I mean things that matter, 
that sounds very mission driven.

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I think that's what I am but 
I'm just very curious about things 

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that have some relevance 
for me, also for the world.

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I studied international 
relations and European studies 

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in Germany and then went to 
California and finally completed

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my studies in France.

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Went to work at a major foreign policy think tank
and then at a commission outpost in Lebanon.

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I have them, like a love for 
the middle east but then decided 

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to enter the German diplomatic service and spent

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almost 15 years in various, what I found super
interesting positions in government in Germany,

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but also for France and Italy.

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And I became fascinated with 
technology when I was part 

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of negotiation teams on tech 
policy frameworks in Europe.

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My focus in that role was on 
drafting and coordinating policies 

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for a new and smart regulation of technology

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and during that time, actually, 
I was deeply involved in 

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the beginning of GDPR 
negotiations on a European level.

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I mean they took forever, 
they took six years all in all 

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but I was there at the 
beginning and then in 2012,

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nine years ago, I came to 
the US and my job was 

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to organize multi-stakeholder 
meetings and discussions between

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Germany and tech companies 
in Silicon Valley and also 

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to do communication work around that.

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So, in a way I combine being strong on content
and being interested in content, but I also really

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like coordination and trust 
and relationship building 

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and so with that I've been 
growing this really big network

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in the tech and regulation space.

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And so after those three years 
were over at the diplomatic 

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outpost, at kind of the intersection 
of tech and policy I decided

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to become a tech policy consultant, 
bridging Europe and the US, 

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so I can be in both places 
geographically and also in terms

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of disciplines for different clients and 
right now I wear, let's say two hats.

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One is that I'm working as a privacy professional, 

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so I become part of trust and 
safety teams and tech companies

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in Europe and in the bay area 
and I also do the same job 

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for advisory firms and for non-profit foundations.

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And the main topic is compliance on privacy 

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and data protection, so 
in Europe that's the famous

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General Data Protection Regulation, 
but there's something 

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like that also now in California.

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We can talk about that if you're 
interested in that later on, 

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but I also do consequence scanning 
which is kind of a key word

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recently in Silicon Valley and on security.

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And so, I become really part 
of those engineering 

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and product teams and start out 
with data protection

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and then also work on other policies that 
I helped draft for those companies.

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And the second hat is that, 
because I wanted to work on 

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geopolitics of tech regulation 
a bit more, maybe that's

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a continuation or I wanted to start 
something again that I really 

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liked in diplomacy, the non-profit 
Mozilla Foundation offered

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me that Fellowship in Residence that you mentioned.

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I started that last year and 
I work on upcoming EU regulation 

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on trustworthy AI and that's 
kind of an analytical research work,

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but I do like to go out and 
talk with AI builders and also 

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with government experts and 
lead workshops and

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get my insights directly from 
tech companies building AI.

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And I'm also on the policy 
team at Mozilla Corporation, 

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as opposed to the Foundation, 
and so I help identify

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and monitor and analyze policy 
issues that affect Mozilla's 

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products, at both state, national 
and international levels.

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So, the team there is really 
small but still very global 

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and I'm glad I can contribute 
to someone who knows

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several regions of the world really well.

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Wow. So, I mean it's great that 
you work on the public side 

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also and then you are pretty 
much in the tech hub

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and you are dealing with all, sort of, 
say, partners in this ecosystem.

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We will definitely discuss AI 
regulation in depth but let's take 

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a step back and go to GDPR 
and we are sort of obsessed

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in EU with that and it's 
just completed three years 

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and now you can see things are 
getting into place in EU.

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But what has broadly been its impact 
in Silicon Valley in these three years?

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What has worked? What has not worked?

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Like a sort of report card 
of GDPR in Silicon Valley.

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Yeah. So, GDPR has had some really notable 
and immediate impacts worldwide, 

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well first of all in Europe as you can 
witness, but it has also brought

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an awareness to Silicon Valley and 
the US, that privacy is important 

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to people in Europe but also in 
other regions of the world and

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that it's a human right that in 
the US many had not really 

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considered important, but the 
surveys, even there among

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population, prove them wrong.

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So the global conversation around 
privacy has really shifted 

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in the past, yeah, three years 
but even before a little bit,

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but definitely since 2018 
and so have the laws.

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So, as a direct result of GDPR 
in Europe, countries, like Japan 

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or Brazil, passed GDPR-inspired 
privacy laws and India

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and even China considering their 
own law, even though those 

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look different from what 
we think they should be

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but it's definitely a big push.

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And California's new privacy law, 
which went into effect in 2020, 

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is a direct result of GDPR and 
California is the first state

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in the United States to have 
set up a privacy protection 

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agency at state level.

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No other US state has 
that, although in Europe  

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each member state has at least 
one on a national level,

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Germany, 16, for every Bundesland. 
But in California, 

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that's the first for the United States 
and this agency has just taken up its work.

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It has a Spanish-born GDPR 
expert as a board member on 

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a California state level of this agency, 
so I think that's really notable.

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And also, overall, in more geopolitical 
terms, GDPR has also shown 

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to Silicon Valley that one of 
their biggest markets, Europe, 

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has its own rules and that 
they have to follow when they

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want to be a player there 
and earn money there.

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And as a result, 
many US-based organizations 

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that process personal data 
of people around the world

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have decided to apply GDPR 
and extend all the rights 

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that go with it to their 
customers, who don't need to

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be European residents but 
who live outside of Europe 

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and this is the case for many 
companies around the world.

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It gives them an edge in global compliance 

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and it's easier for them in terms 
of handling complaints and requests.

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So, they say, just give all 
of our customers all the rights 

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that Europeans have, which you don't have to,

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it's a very high bar but it's 
still easier for the organization 

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than to sort out the customer's 
location and sometimes

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they only have an email address, 
or attribute different 

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rights according to their location, 
I mean that's really

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complicated when you have a hundred 
different sets of terms and conditions.

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So, GDPR offers them a 
legal framework and a set 

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of standards that is, well, 
at least compared to other less

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spelled out legislation or when 
there's no legislation at all, 

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relatively clearly adoptable.

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So, my clients are mainly small 
and medium enterprises based 

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in the US with only some clients 
in Europe or sometimes just

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the mere intention of 
soon expanding to Europe, 

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but this privacy management 
strategy, just take GDPR

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as a high level standard 
and apply it to everybody, 

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has been found with bigger tech firms as well.

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Because they appreciate that 
there's a standard now that 

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is law in one part of the world, 
but can serve as a guideline

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also for other parts of the world 
and that it's just easier 

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to have one high profile standard 
than many different ones,

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what I call, the growing global privacy patchwork.

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That made the EU the de facto 
rule setter and technology policy 

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worldwide, so the whole perspective 
on European rule setting

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and on Europe as a factor in 
the tech industry has changed

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in a very short time in Silicon 
Valley and yeah, so narratives

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have changed and internal 
data management has changed.

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I need to mention that a 
disappointing factor is enforcement so, 

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even when tech companies do get 
hit with billion dollar fines,

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for them it's a tap on the wrist 
and so far GDPR hasn't changed 

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the underlying business 
models, the way money is

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made on the internet, with 
surveilling people's behavior.

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And so it's not just the 
business model of a company, 

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it's the entire internet 
that is based on a, yeah,

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economic model that doesn't 
have privacy top of mind, 

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so changing that, of 
course, requires fundamental

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and probably painful adjustments to 
the way things have been structured.

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That's definitely something 
that GDPR so far hasn't been 

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able to achieve and that's 
definitely a bit disappointing.

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So there is GDPR in the 
US, sorry, in Europe, 

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and there are also data regulations 
in the US. I think it's CIPP.

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So, when you compare the 
standards, how compatible 

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are these two when implemented 
by companies together?

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Does my question make sense?

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Absolutely, yeah.

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So, yeah, I mentioned this 
global privacy patchwork 

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and definitely, so, the privacy law 
in effect in California is called,

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CCPA, called, California's Consumer Privacy Act.

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It will actually be replaced again 
soon by another one that's called, 

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CPRA and it's a bit, even 
an advanced version of CCPA,

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abbreviations, but some principles 
are the same as GDPR 

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and then again it has some elements 
that even go beyond GDPR

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and I would say that enforcement 
of these will be very hard.

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I think in a way it's been a 
law that has been created very, 

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very fast in a way that is 
maybe weird for us in Europe

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by a petition of people, 
that got a lot of signatures 

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and then actually pressed 
the California legislature

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to create that law very rapidly.

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So, in a way it's not as 
systematic, not as clear as GDPR.

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It does go further in some 
areas which don't always make 

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sense to a consumer because 
they're kind of hard to understand,

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but then they do have elements that 
have just nothing to do with GDPR 

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or just are, yeah, don't go as far.

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So it's a bit different but 
I would say that what's important is, 

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so in a way it's easier 
for companies, I would say,

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to comply with GDPR and then 
just to say, and then add some 

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important elements of CCPA 
and hope for understanding

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on the part of, enforcement agency.

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I have to say that enforcement 
is weak in California as well, 

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so that's hard of course, as 
a privacy professional when

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you try to explain to companies 
that it's really important 

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to follow the law but then the 
whole enforcement is so, yeah,

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there's so many deficits and 
there's so few people working on that.

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I think in the end in California 
it will be, usually in the US, 

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it will be litigated in court, mainly.

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Okay, but as you just said 
that for Big Tech, probably, 

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this is not difficult as much 
and they don't get so panicked

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about it because they have big 
legal teams and heavy pockets and  

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you said you deal mostly with SMEs

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and I'm not sure if you deal 
with non-tech companies also, 

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but what are particularly the 
challenges that these kind of companies face

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and have there been any 
stories where they did something 

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that they were not aware of was illegal 
and then they had huge fee and fine and so?

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I mean take us through the struggles that 
usually these kinds of SMEs face with GDPR.

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Yeah, so, well, so as I mentioned 
I work as an independent 

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privacy professional, both 
before GDPR became enforceable

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and then also after, and working 
mostly with small companies in the US, 

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I've witnessed how hard it has been 
for those small startups outside of Europe

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in a different legal system 
with a different understanding 

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or traditional understanding 
of privacy, to understand why

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and how they're exposed to GDPR.

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My work, in a way, is both legal 
and technical but it's also cultural.

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So I translate mentalities in a 
way and what's important in Europe 

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and why and plus, for a startup, 
of course, it costs time and money.

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And so they took a bit longer, 
I mean I'm only one 

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for privacy professional, 
many others worked on this as well,

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but still there was a delay 
in adaptation and it sometimes 

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resulted in vendor agreement cancellations,

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which means that they lost 
business with other bigger firms 

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and yeah, I mean we all lost 
great ideas and innovation

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and diversity among tech builders.

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So, academically speaking, 
I did witness what's 

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called the Brussels effect in 
California as a, let's say,

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dyed in the wool European 
integrationist, I did celebrate it.

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I thought it was really great 
that European style rules come 

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to California and I think overall 
it's a positive result,

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but I also witnessed how much 
easier it was for Big Tech 

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to adapt because they have 
a presence in Brussels,

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they have huge legal teams, 
they know about compliance, 

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about loopholes and this 
over time has been leading

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to more concentration of power 
in the hands of Big Tech.

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I wouldn't say that compliance 
is more difficult for startups 

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or small firms, actually, 
the opposite is true because,

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very banal, they have less 
data to start with because 

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they're just starting to collect 
data from their users in their products.

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So, in a way it's easier 
for them to right away, 

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establish good and compliant 
data management systems.

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So what I always tell them 
is start early, have a system 

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and follow it and in a way that's 
much easier than to clean up

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a whole mess of collected 
data with no legal basis, 

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or that you've been storing 
forever in some place because

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you might be using it for another product.

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So, in a way when you start 
early enough and you're aware 

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of the rules it is easier and 
you just have to follow through,

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but that of course, needs some kind of a shift 
in culture but I think that shift has happened.

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It's also shown that some small companies, 
and the big ones now as well, use privacy,

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yeah, as a marketing tool 
but that sounds too negative, 

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it's actually a big asset 
because consumers demand it.

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And so when you do that in a 
smart way as a small startup, 

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you have huge tools at your hands and so

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it's not negative when you  

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start early, when you are aware of 
the rules but also upcoming principles

20:31.520 --> 20:37.040
and you deploy them in your systems, 
in your products early on.

20:38.720 --> 20:44.320
Yeah. Now, I just sort of picked up your 
line that they do it out of marketing 

20:44.320 --> 20:49.040
because I think this is also something we 
discussed in a podcast with Safiya Noble,

20:49.600 --> 20:53.760
the author of Algorithms 
of Oppression, and I'm not sure 

20:53.760 --> 20:58.560
if there is a word called, privacy washing, 
like you have green washing.

20:58.557 --> 20:59.360
Yeah.

20:59.360 --> 21:04.400
But probably it has become 
a marketing gig to talk about 

21:04.400 --> 21:09.920
your customer data and how safe it is 
and having discussions around that.

21:10.800 --> 21:16.160
So yeah, just a comment, 
not a question, but okay.

21:16.160 --> 21:21.440
Now, so, first we had GDPR 
and now we have the proposed 

21:21.440 --> 21:25.200
AI regulations in Europe and 
we have never really spoken about

21:25.200 --> 21:30.080
it in this podcast and so 
I would say that even me 

21:30.080 --> 21:34.560
or particularly the audience, 
are pretty new to this.

21:35.120 --> 21:39.360
So, if you could, and you seem to 
be very deeply involved in this, 

21:39.360 --> 21:43.440
so if you could take us 
through what are actually these

21:43.440 --> 21:49.440
AI regulations that have been proposed in Europe
and what are their challenges?

21:49.440 --> 21:52.480
And then probably we can go deeper into it.

21:53.280 --> 21:57.600
Yeah, sure. So, yeah, 
the upcoming AI regulation that 

21:57.600 --> 21:59.280
has been tabled by the commission,

21:59.280 --> 22:05.440
but is only on the negotiation 
table now for member states 

22:05.440 --> 22:06.640
and the European parliament,

22:06.640 --> 22:12.320
is actually the core thing 
I'm working on in my fellowship 

22:12.320 --> 22:16.800
and my intention is really 
to make sure that this

22:17.760 --> 22:19.680
upcoming regulation, again from Europe,  

22:21.120 --> 22:24.400
does not again cause that 
lagging behind of small players.

22:24.400 --> 22:29.120
Because in the field of AI, as 
you all know, size clearly matters.

22:29.120 --> 22:32.960
The more data you can gather, 
the better your AI system works 

22:32.960 --> 22:35.920
and we're already pretty far 
down the road to monopolization,

22:36.720 --> 22:41.760
because few players in the market have access
to an impressive range of data and they can also

22:41.760 --> 22:45.600
afford gathering high quality 
data, which then enables them 

22:45.600 --> 22:50.880
to build better performing AI 
and for small scale providers,

22:50.880 --> 22:53.840
what's most important is the clarity of the guidance.

22:54.560 --> 22:56.560
I mean that sounds banal, who wouldn't say that? 

22:56.560 --> 23:00.880
But if you follow it wise, 
you set up an internal team analyzing

23:01.440 --> 23:07.840
those rules for your in-house implementation, 
adapted to your AI system,  

23:08.640 --> 23:12.000
you get much better at estimating 
necessary additional processes.

23:14.080 --> 23:25.040
Yeah, so that to say why I work on that and again 
this link to the small scale providers of AI.

23:26.400 --> 23:30.720
In general, the regulatory draft 
that the European commissioned 

23:30.720 --> 23:34.400
and it was tabled on april 21st, 
so that's not very long ago

23:34.400 --> 23:39.040
and in Brussels things take time, 
committees are formed, 

23:40.960 --> 23:44.080
but the draft that the 
European commission tabled also

23:44.080 --> 23:46.960
has been a very long time in the making.

23:46.960 --> 23:51.840
Von der Leyen, the commission 
president, announced something 

23:51.840 --> 23:54.800
like it already at the 
beginning of her presidency

23:54.800 --> 23:57.200
and then it came up this year.

23:57.840 --> 24:01.520
It's the most ambitious and 
the most comprehensive attempt 

24:01.520 --> 24:05.520
at reigning in the risks linked 
to the diplomatic AI that

24:05.520 --> 24:09.920
we have seen so far across the globe, 
so it's a bold new step.

24:11.440 --> 24:16.480
Before, the big focus of the past 
years were always just principles, 

24:16.480 --> 24:21.040
I'm saying, just, but I mean of course, you 
start with principles on an international level.

24:21.040 --> 24:26.000
The OECD principles on AI 
that were adopted in May 2019, 

24:27.280 --> 24:29.760
most European countries 
and the US are members  

24:30.720 --> 24:33.520
of the Organization for Economic 
Cooperation Development.

24:33.520 --> 24:35.280
So they're already...

24:36.800 --> 24:40.880
They promoted uses of AI that are 
innovative but also trustworthy, 

24:40.880 --> 24:43.840
that respect human rights 
and democratic values.

24:43.840 --> 24:47.280
And I think now, in 2021, 
really we're at the stage of, 

24:47.920 --> 24:52.400
how do you transform these principles 
into practical rules and regulations?

24:52.400 --> 25:00.320
So, the rules that the European commission 
proposed wouldn't cover all AI systems.

25:00.320 --> 25:08.000
They do cover systems that are 
deemed to pose a significant risk 

25:08.000 --> 25:12.000
to the safety and fundamental 
rights of people living in Europe.

25:12.960 --> 25:19.600
So it's, again, it's this geographical 
scope of people living in Europe, 

25:21.040 --> 25:25.760
so it's a risk-based approach, 
it has several layers

25:25.760 --> 25:32.320
and those layers have different rules 
for different classes of AI systems.

25:32.320 --> 25:36.400
There are some that are 
prohibited, there are some that 

25:36.400 --> 25:41.360
are considered high risk and 
have to follow certain rules

25:41.360 --> 25:48.560
and then, others where they just say, 
you have to be more transparent.

25:48.560 --> 25:52.640
Do you want me to go more into 
details of what those rules are?

25:53.760 --> 25:57.440
Yes, I mean broadly, if you could 
point it out, one, two, three. 

25:57.440 --> 25:59.680
I don't know if it can be done that way but...

25:59.680 --> 26:00.459
Absolutely.

26:00.800 --> 26:01.593
...yeah.

26:01.920 --> 26:05.760
Sometimes it's confusing because 
it's really so much of a risk, 

26:05.760 --> 26:10.400
like you have to know in which 
category your AI system falls

26:10.400 --> 26:15.920
and that's really on the developers, 
kind of, to understand 

26:15.920 --> 26:19.360
the categories and in the end 
it's actually pretty clear that

26:20.720 --> 26:25.360
not many AI systems actually 
fall under that rule. So..

26:25.360 --> 26:26.400
Oh, wow.

26:26.400 --> 26:29.680
...definitely something to understand. 

26:29.680 --> 26:34.000
So, for some users of AI the 
commission proposes an outright ban.

26:34.560 --> 26:39.280
So, that's a use where the commission says it's 

26:39.280 --> 26:42.960
an unacceptable threat to 
citizens, that for example,

26:42.960 --> 26:48.000
it's an AI system that likely causes 
physical or psychological harm by  

26:48.720 --> 26:50.800
manipulating a person's behavior.

26:51.520 --> 26:55.280
What that means, I mean that's 
a question of definition 

26:55.280 --> 27:00.000
or by exploiting their vulnerabilities, 
like age or disability.

27:00.880 --> 27:08.320
Then also something like social scoring systems,
where people collect points and also minuses,

27:08.320 --> 27:09.840
like those which we know in China  

27:11.040 --> 27:15.520
and facial recognition in public 
spaces by law enforcement authorities.

27:16.560 --> 27:23.040
So not all facial recognition, but just those 
used by police in public spaces, essentially.

27:23.040 --> 27:27.760
Although, even there you have exceptions 
and I think too many of them.

27:29.280 --> 27:37.040
So that's, you know, the systems that the 
commission proposes should be banned in Europe.

27:38.160 --> 27:41.520
But most of the regulatory draft, 
actually focuses on AI 

27:42.400 --> 27:47.360
that is considered high risk and 
what is high risk is, of course,

27:47.360 --> 27:52.480
defined in the regulatory draft, 
so that's, kind of problematic 

27:52.480 --> 27:56.160
uses in the recruiting field, in the employment

27:56.160 --> 28:01.120
and admissions context, in determining a person's 

28:01.120 --> 28:04.640
credit worthiness or 
eligibility for public services

28:04.640 --> 28:10.880
and benefits and also some 
applications used in law enforcement 

28:10.880 --> 28:15.600
and security and judiciary and 
for those, these systems have

28:15.600 --> 28:21.280
to meet different requirements and 
undergo kind of a conformity assessment, 

28:22.960 --> 28:27.680
so, of course, before they can be 
placed in the in the European market.

28:27.680 --> 28:34.640
So, in a way, that's kind of a, 
yeah, FDA, as we call it in the US, 

28:34.640 --> 28:39.120
like clinical testing for, 
not for drugs or for vaccines

28:39.120 --> 28:44.320
but for algorithms. It's to 
make sure that an AI system 

28:44.320 --> 28:50.400
complies with several requirements 
around serious risk management.

28:50.400 --> 28:58.240
It has to use data sets in training, validation 
and testing that are relevant, representative,  

28:58.240 --> 29:00.000
free of errors, complete.

29:00.000 --> 29:07.520
That's a super tall order, of course. 
Then documentation about 

29:07.520 --> 29:13.040
a high risk AI system must be 
really extensive and very precise.

29:13.040 --> 29:18.560
Why you chose certain designs, 
why you designed it in 

29:18.560 --> 29:23.840
a specific way and also to 
show that the developers

29:23.840 --> 29:26.960
really checked all these factors diligently.

29:27.520 --> 29:31.280
There has to be, the key 
word is always human oversight, 

29:31.280 --> 29:34.800
so high-risk AI systems must 
be designed in a way that

29:34.800 --> 29:40.960
allows people to understand the capabilities
and the limitations of a system and to counter

29:40.960 --> 29:46.880
the so-called automation bias and also if 
necessary reverse or overwrite the output.

29:47.600 --> 29:48.100
Yeah.

29:48.880 --> 29:54.000
And then of course, accuracy, 
robustness, security and transparency.

29:54.000 --> 29:57.280
So this is, kind of, this clinical 
testing for algorithm.

29:58.480 --> 30:04.240
So, do you see, because there’ve also 
been some articles criticizing, 

30:04.240 --> 30:07.280
I think, I mean that's why we have media, right?

30:07.280 --> 30:11.600
But do you see any loopholes in this regulation, 

30:12.320 --> 30:18.080
proposed AI regulation or 
do you feel that there was some,

30:19.040 --> 30:24.000
I mean, in terms of your learnings, do you 
see any challenges or loopholes in this?

30:25.200 --> 30:28.480
Yeah. I mean, first of all, 
of course, we only have a draft 

30:28.480 --> 30:31.760
so far and already the European parliament

30:31.760 --> 30:34.800
and also other bodies in 
Europe, have already called 

30:34.800 --> 30:39.120
for much stricter rules in 
some elements of the draft,

30:39.120 --> 30:45.680
so, certain member states will 
definitely also have their say on, 

30:45.680 --> 30:51.360
I mean all of them will have their say, but 
certain member states are of the opinion

30:51.360 --> 30:56.640
that it should be stricter in some 
cases, so this is not the final word.

30:58.960 --> 31:06.640
Well, in my personal opinion, I do think 
that exceptions for facial recognition, 

31:06.640 --> 31:15.280
just to take one big part of what people 
expected of this regulatory draft, are too wide.

31:16.800 --> 31:26.320
So, it's just difficult when you ban 
very specific uses of facial recognition, 

31:26.320 --> 31:33.600
but then, actually in industry or private 
uses there's no ban at all and so,

31:33.600 --> 31:38.640
even in the uses of law enforcement you 
have certain areas where it can be used.

31:38.640 --> 31:43.280
So in a way, practically speaking, 
law enforcement in Europe 

31:43.280 --> 31:47.600
will buy facial recognition 
systems on the market,

31:47.600 --> 31:54.400
wherever they're produced, and use them in those
specific cases that they would be allowed to

31:55.280 --> 31:59.120
and how do you really want to make sure 
that they don't use them for other things?

31:59.120 --> 32:01.920
So, I think that's a huge 
loophole and then of course, 

32:02.800 --> 32:10.240
and I think it's really dangerous, so I really 
don't want to sound alarmist but in a way,

32:10.240 --> 32:17.520
I do think that facial recognition has a 
potential to actually undermine our free society.

32:17.520 --> 32:20.800
That sounds big but I do think it is a big danger.

32:21.520 --> 32:22.020
Yeah.

32:23.600 --> 32:24.960
I mean there is also  

32:24.960 --> 32:32.560
other things that we're kind of used to 
in the European regulatory process,

32:33.440 --> 32:41.040
some rules are just very loosely 
defined and over time with use, 

32:41.040 --> 32:47.600
once it's in effect, we will better understand 
what's actually meant by it or maybe get guidance,

32:47.600 --> 32:56.240
but definitely, also, from practical life, 
court decisions, practical use cases.

32:56.240 --> 33:06.400
All of that, just like in GDPR, wasn't or 
isn't always clear for me in the end, 

33:06.400 --> 33:11.680
so there's a lot to criticize about this draft. 
It's definitely one that has been  

33:12.960 --> 33:16.640
drafted in a part

33:16.640 --> 33:22.640
of the commission that is mostly interested 
in encouraging AI development in Europe, 

33:22.640 --> 33:30.000
so, just to make it a more 
competitive market and not the legal

33:30.000 --> 33:35.840
and the justice oriented 
and human rights oriented  

33:37.440 --> 33:42.000
experts in the commission 
so that, I think it shows.

33:42.560 --> 33:47.840
But for me, the most important thing is, 
actually, that there is some draft 

33:47.840 --> 33:52.880
on the table in one part of 
the world and other places  

33:53.520 --> 34:00.240
will look at it and decide if it's 
something that they want to adopt as well

34:00.240 --> 34:07.520
or create differently, but still 
discuss what it can and what it can't do.

34:08.560 --> 34:15.120
I don't think it's a coincidence that just 
before the commission published its proposal, 

34:15.120 --> 34:20.480
the date was public, the 
United States Federal Trade Commission, the FTC,

34:20.480 --> 34:25.280
published a reminder that it's watching 
closely what AI systems companies aim 

34:25.280 --> 34:30.400
to use and that they really have to make 
sure that there's no bias in those system

34:30.400 --> 34:36.640
and no discrimination resulting from its use.

34:37.920 --> 34:42.880
So, I'm pretty hopeful that 
there will be some collaboration in making 

34:42.880 --> 34:47.840
rules compatible between the United States and Europe.

34:48.800 --> 34:56.160
There's been some really positive 
signs already from the US administration, 

34:56.160 --> 34:59.360
that the US wants to work 
with the EU in this field,

35:00.160 --> 35:02.480
because in the end let's not 
forget that the United States 

35:02.480 --> 35:08.640
and Europe share values and commitments 
to protecting rights and human dignity.

35:08.640 --> 35:13.040
It sounds cheesy but I do believe 
it's true at the core, we, 

35:13.040 --> 35:16.640
compared to the rest of the world, 
we have a lot in common

35:16.640 --> 35:20.240
and we have certain values that are at stake.

35:21.200 --> 35:29.440
We should go back to those roots and know that 
if we let AI develop completely unregulated, 

35:30.560 --> 35:36.000
those core values of our democracies 
are at stake and that's not alarmist,

35:36.000 --> 35:40.320
as I mentioned, it's not 
some science fiction,  

35:41.280 --> 35:45.600
it's actually already happening 
in a lot of developments.

35:46.800 --> 35:54.400
So, I think, yeah, that's a very good reason 
to cooperate internationally on these rules.

35:54.400 --> 36:00.000
Yeah, actually that's a very interesting 
perspective because one of my next questions, 

36:00.000 --> 36:06.080
I don't know if it's null and void now, 
but I was going to ask you that  

36:07.600 --> 36:12.720
if regulation is going to impact innovation in AI,

36:12.720 --> 36:20.480
but you just mentioned that this is a very 
pro and innovation, kind of regulation, 

36:22.400 --> 36:27.760
so I would rather reframe it and ask you that, 
how do innovation and regulations  

36:29.120 --> 36:31.120
in AI go hand in hand?

36:32.640 --> 36:38.560
Yeah, well, as a matter of principle, I 
don't believe regulation stifles innovation. 

36:38.560 --> 36:43.760
Very often in my daily life, I work with 
technologies who feel that, actually,

36:43.760 --> 36:48.080
regulation gives them some guard rails that 
they actually appreciate, as a matter of fact.

36:49.520 --> 36:52.640
I think on the contrary, 
smart regulation that gets out in 

36:52.640 --> 36:57.760
front of emerging technology can 
protect consumers and drive innovation.

36:57.760 --> 37:04.240
So my focus is on protecting consumers and 
that, I think, is the most important thing.

37:05.360 --> 37:07.025
I mean, we're not just a  

37:07.520 --> 37:18.880
huge, couple billion of mice in a lab, 
we are people with rights and dignity.

37:18.880 --> 37:21.840
And it feels to me that policymakers have,  

37:22.720 --> 37:28.880
kind of, over the last decades,
forgotten that regulation 
can be beneficial and  

37:28.880 --> 37:33.360
that it's not always just good to 
give industry players free reign,

37:35.040 --> 37:40.160
just to deploy the technologies 
according to their business model, 

37:40.160 --> 37:47.040
because there's also, definitely, 
an increasing backlash against tech companies.

37:48.080 --> 37:52.080
People kind of have this suspicion, 
kind of a dark suspicion, 

37:52.080 --> 37:56.080
that these companies are interested 
primarily in promoting their own dominance.

37:56.800 --> 38:00.480
Very low trust. I mean there are 
surveys that show this very clearly.

38:00.480 --> 38:05.920
The technology companies enjoy 
very low trust in general but then, 

38:05.920 --> 38:10.160
I mean, they do sell their products 
but people don't trust them

38:10.160 --> 38:16.960
and as a result, this is when 
policymakers at state and local level, 

38:17.520 --> 38:23.520
actually begin to consider 
technology bans and that's starting mostly

38:23.520 --> 38:27.600
at those lower local and state 
levels but I think that at some point, 

38:27.600 --> 38:32.480
and it's already happening, at a 
higher level they're also talking about that.

38:32.480 --> 38:39.680
In Europe faster than in other 
places but, yeah, as I said, 

38:39.680 --> 38:46.640
I think those who know AI development well 
and who warn of unguarded development,

38:47.920 --> 38:52.960
are often considered that they're 
overreacting to science fiction speculation, 

38:52.960 --> 38:57.760
but actually there are really creepy 
AI systems already deployed in real life.

38:59.280 --> 39:04.240
Examples that I really find creepy 
are those algorithmic selection systems  

39:04.240 --> 39:06.960
in hiring interviews that are 
actually based on bias data,

39:06.960 --> 39:10.560
so you could say that, well, it's 
just a really badly built product 

39:11.440 --> 39:16.240
but I mean they're just let loose 
on people before being tested

39:16.240 --> 39:26.080
or checked and they cause real harm or 
mood detection systems and music apps.

39:26.080 --> 39:32.560
Spotify presented something like that. 
It sounds fun but actually those  

39:32.560 --> 39:39.360
systems put people in categories and they 
reinforce, sometimes, dangerous cliches.

39:40.560 --> 39:44.960
They do, as a matter of fact, not 
comply with existing consumer protection 

39:44.960 --> 39:51.120
laws or non-discrimination laws or actually 
just basic principles of decency. So...

39:51.120 --> 39:51.760
Yeah.

39:51.760 --> 39:57.200
...I think what's changing right now in the 
US, is that the idea that the technology sector 

39:57.200 --> 40:02.720
is in some way different from other industry 
sectors, that it needs more freedoms

40:02.720 --> 40:04.960
and exceptions to general market rules.

40:04.960 --> 40:10.080
That's fading and agencies are more looking 
into how to apply their existing rules  

40:11.120 --> 40:14.160
around competition also or anti-trust,

40:14.160 --> 40:17.440
called in the US, and consumer protection safety, 

40:18.000 --> 40:21.760
non-discrimination to technology 
and that's very similar in Europe.

40:21.760 --> 40:28.720
I think it's time that we consider the technology 
sector as a normal part of our economies, 

40:28.720 --> 40:31.360
that doesn't need and shouldn't enjoy exceptions

40:31.360 --> 40:34.960
or special protection, compared 
to other more regulated industries.

40:35.680 --> 40:44.000
Yeah and also I think generally, people are 
redefining innovation, it's that sentiment.

40:44.560 --> 40:48.720
But beautifully put and also 
a very positive note to come  

40:48.720 --> 40:53.440
to concluding statements for today's episode.

40:54.000 --> 41:02.480
So, Julia, if there was one thing 
you would want our audience to take away 

41:02.480 --> 41:11.200
from today's discussion, what 
would it be? Very broad question.

41:11.200 --> 41:15.600
Yeah, very broad, but let me 
think of something good for you. 

41:15.600 --> 41:21.040
I think what I really want is 
that people look at technology,

41:21.040 --> 41:29.760
as I just mentioned, as one industry 
among many, that should be centered around 

41:29.760 --> 41:38.240
us people who use it as a tool 
and should not be a cause in itself.

41:38.800 --> 41:43.040
So, those companies don't need some special status. 

41:43.040 --> 41:47.680
They're not, like, 
small innovation sparks anymore.

41:47.680 --> 41:56.400
They are our biggest and most costly and 
most powerful economic players and so, 

41:57.120 --> 42:07.760
we should really kind of turn around the 
picture and say, who are you there for?

42:07.760 --> 42:14.400
Are you there for us or are you there 
for just sucking up power and money? 

42:14.400 --> 42:23.920
And so, if we say that you're there for us and for 
us to really benefit of all the really positive

42:23.920 --> 42:30.640
and promising uses that, not only AI, but 
technology in general, can have for humanity, 

42:30.640 --> 42:39.920
let's also create smart and easily understandable 
rules that make sure that we don't just say,

42:39.920 --> 42:48.320
“oops yeah, that was a mistake, I'm sorry 
that I just destroyed your existence”.

42:50.880 --> 42:57.120
And so, we have to make sure that 
the human is at the center and that AI 

42:57.120 --> 43:02.480
or in general, technology, is a 
tool for humans and that humans are  

43:02.480 --> 43:06.480
still created equal and have dignity as an individual.

43:07.680 --> 43:12.800
Yeah, and we try to do a bit 
by interviewing people like you 

43:13.440 --> 43:16.480
and I mean it was such a pleasure,  

43:16.480 --> 43:22.880
it was a spontaneous plan that we had to 
record this but it turned out so great.

43:22.880 --> 43:27.680
I'm so happy that we could host 
you after all these trays of months 

43:27.680 --> 43:33.760
to get you on Voices of Data Economy and 
thank you for being here today.

43:34.560 --> 43:38.149
Thank you, Diksha. It was a really nice conversation.

Michael Healy & Thy-Diep (“Yip”) Ta - How token economy could contribute to distributing value.srt

1
00:00:00,150 --> 00:00:05,260
You know, similar to the internet on the mobile,
everything, which was in the non-internet

2
00:00:05,260 --> 00:00:08,040
and non-mobile world, moved to the internet.

3
00:00:08,040 --> 00:00:15,789
So, things like the newspaper went online,
shopping went online, education went online,

4
00:00:15,789 --> 00:00:18,810
art went online, travel went online.

5
00:00:18,810 --> 00:00:20,680
So, every single industry went on to the internet.

6
00:00:20,680 --> 00:00:27,780
Same with the mobile, every single industry
went onto mobile, you know, if it didn't have

7
00:00:27,780 --> 00:00:31,265
an app or there wasn't an app for it, then,
you know, there's an opportunity to build an app for it.

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So, it's the same with the token and blockchain world.

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If there isn't a decentralized app or a token
for a particular industry, or a particular

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business, then there is an opportunity.

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If there's a supermarket, which is centrally
owned and centrally run, it's an opportunity

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for you to create a supermarket, which is
decentralized in ownership and decentralized

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in the way it operates.

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So, we think this is going to ignite so much
innovation and it's such a big opportunity

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and we think we're very close to that.

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What it takes is just a few case studies,
a few hundred case studies of projects, which

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do this and then people are gonna go, wow,
I'm gonna do that too, I'm gonna apply it

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to my existing business 
and then it's gonna really transform.

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This is Season 2 of Voices of the Data Economy.

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A podcast supported by Ocean Protocol’s foundation.

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We bring to you the voices shaping the data
economy and challenging it at the same time.

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Listen to founders, tech policy experts and
pioneers in impact investing.

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All sharing their relationship with data.

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Hello and welcome and today we have not one,
but two guests with us.

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Michael and Yip.

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The one thing common about both of them is
that they are both founders of Unit.

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Unit is a blockchain project 
built with Polkadot ecosystem.

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They are also both advocates of token economy
and how tokens could probably contribute to

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the democratization of data and help in all
the inequality in the society.

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Michael is based in Bali, 
Indonesia and Yip is in Munich.

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So, before we begin, it's important to talk
about what is their relationship with data.

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So, we'll start with you Michael.

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Since you have experience in developing apps
and you also developed the android app for

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Wikileaks, at the age of 16, it would be interesting
to know from your perspective, how do you

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look at the concept of data ownership and
how do you think it has changed in the last

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few years, as all these companies 
continue to develop products?

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00:02:46,700 --> 00:02:48,950
Yeah, it's a great point.

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I think, data is really the underlying value
for almost any Web 2.0 or a Web 1.0 project

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or business, so if you think about the likes
of Netflix or you think of Facebook or Google

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or Amazon, you know, what makes these companies
extremely extremely valuable is it's data.

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And, you know, mentioning about what's coming
next, in terms of the data revolution, the

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cool thing about Web 3.0 or the blockchain
revolution is where the people have access

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to their own data and they're not bounded by these 
walls and gates that these big tech companies have.

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So, it's really power back to the people and
that's what makes me so excited.

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And Yip, what is your definition of data ownership
and how do you look at it and particularly

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in your role, do you think you are working
towards democratizing data in any way?

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00:03:41,529 --> 00:03:47,599
Well, we are working towards solving 
the inequitability problem, right?

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This has, like, how do you solve inequity
by helping people to gain ability to contribute

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to shaping the economy of tomorrow.

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I think that's a way of, like, showing democracy.

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Like, helping everyone in the world to be
able to navigate this entire world and thereby,

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one way of how to do that is education, right?

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00:04:10,099 --> 00:04:17,120
So, what we do is in Unit and in particular
my role in Unit Masters, is to provide education

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in a way that is efficient and effective,
so that in a very structured and fast way

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everyone can participate in that new, I would
say, El Dorado of vast opportunities that

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we're building in the Web3 economy.

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And how does it work?

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Well, everywhere you have a lot of data, internet
basically provides a lot of free data to everyone,

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but data alone is not insight, right?

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Data needs to be clustered and clustered into
clusters of data, which are information.

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And then information needs to actually be
connected so it can become an insight and

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the moment a person owns the process of making
insights for themselves out of a bunch of

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random data, that is the moment they, in my
view, own the data and own like, have a passport

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to shaping, not only consuming, but 
contributing to the world of tomorrow.

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And so, basically looking back at data ownership,
data democracy, we actually also need to look

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at the skills and help everyone who wants
to contribute, contribute in a way that is

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meaningful to them, but in a way also that
no one is left behind, so a world of zero

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exclusivity driven by the ownership of data.

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And the ability to connect data into insights.

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Okay.

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Well, I'm glad you spoke about two important
things, education and also about what you're

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doing at Unit and we'll dive deeper into that
also in the subsequent part of the podcast.

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But one thing probably that we've never spoken
about this in podcast before is the role of

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tokens and token economy as such.

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And both of you, particularly you, Michael,
are a big advocate of for token economy and

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you've spoken about it and you feel it's going
to solve a lot of problems, inequality, etc.

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So, just for an overview, give us a view of
what token economy is and why do you think

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it's going to solve these problems.

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Great question, so, the token economy is super
exciting, because it basically refers to an

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economy which is driven 
by tokens and what are tokens?

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So, the concept of tokens is super new, it's
kind of similar to, 30 years ago people were

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discussing what is this thing 
called the internet, you know.

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So, tokens at the moment, when people think
about coins or tokens, they think about Bitcoin

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they think about Ethereum, they think about
the blockchain, but, how we view tokens is

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that, they're just a way for value to flow
around the economy much more efficiently and

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freely and a way to share and distribute 
value in a more equitable way.

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So, you mentioned and alluded to the point earlier about 
solving inequity, or creating a more equitable world.

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And why is the world not 
as equitable now as it should be?

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So, we believe that, you know, currently the
way the world works is the people benefit

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from businesses, organizations doing well,
are the founders and the investors, so the

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people will start companies 
and the people invest in them.

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And then, the other side, you know, the customers
and the employees, without them businesses,

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organizations, they won't be 
able to thrive or survive.

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You know, without the employees, you've got
nobody who's working on operating and making

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sure the project works well.

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The customers, the employees, the founders
and the investors have no customer base to

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provide products and services to.

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However, when a project like Uber becomes
worth 80 billion dollars on the stock exchange

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none of it goes to the 2 million drivers,
so, the really exciting vision of the token

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economy is where everything 
in the world has a token.

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Whether it's your local restaurant, it's your
friend who's an artist, it's your friend who

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runs an agency, it's this project that you
read about in the newspaper, it has a token

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you can buy into it.

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You have an idea for a project you create
a token, so, that is I guess a really quick

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sum up of the token economy and why we believe
in it to be the future.

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And would you like to add something, Yip?

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And probably also on where does 
Unit really come into the picture?

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Because you help in launching tokens as one
of the things that you do at Unit.

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So where does, really Unit, 
come into the picture?

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How are you helping the token economy evolve?

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So, just to build on what Michael said earlier
about the token as a container that enables

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the flow of economic transactions in a world
where every stakeholder, who helps contribute

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value, can have a fair share in it.

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That's the token economy and the idea behind
it.

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And the token economy is also, or actually
Unit is what is providing the tech infrastructure

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on the base layer, to enable that internet
of value to come to life.

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So, how we are actually doing it, is we have
different features inbuilt on the tech layer,

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but maybe, I think it's better Michael, if
you share about it as being our CTO behind

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driving, building the tech infrastructure.

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Most definitely.

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So, I guess, like what is Unit, like what
is the Unit Network, what is the token economy,

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how does it work.

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So, we think it's like, it comes in phases.

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So, a lot of people who know about cryptocurrencies
or tokens, they think, what should I build

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on, or I want to make a token, what do I make it on?

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Or, I want to build a decentralized application,
what do I build it on?

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And, we think, this technology of the 
blockchain is going to become commoditized.

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And what that basically means, is if you look
at the innovation of technology over time,

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you go back 40, 50 years, people used to talk
about which hardware were they going to get.

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Were they going to get HP?

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Were they going to get a Compact?

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Were they going to get a Dell?

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Like, which hardware.

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Then, the hardware didn't matter, it moved
to the operating system, so it's like, should

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I use Windows?

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Should I use Mac?

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Should I use Linux?

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Should I use Ubuntu?

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And then, everything moved to the internet.

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It didn't matter the desktop software, the
operating system, cause all went to the web.

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And then soon enough it moves 
from the web to the mobile.

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So, it didn't matter on the web, 
because it's all like Iphone or Android.

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What we see next, is at the moment people
are like trying to say, hey my blockchain

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is better than this blockchain, because it's
got so many transactions a second, it's more

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decentralized blah blah blah.

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What will confidence going to happen next?

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It's going to become commoditized, meaning
that, it's not going to matter which chain

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you issue your token on, it's not going to
matter which platform you're using to put

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data on, it's just going to 
become commoditized and how it..

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00:10:45,890 --> 00:10:50,310
Well the cool thing about the blockchain,
is that it's decentralized, so the idea that

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even though Yip and myself, with the co-founders
alongside our extremely passionate and talented

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team, we aren't in a position to be 
able to take the whole thing down.

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So, if we changed as individuals, or we changed
as people, as the co-founders, it wouldn't

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be in our position to change in a way which
suits us, or is putting in jeopardy the community.

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It's kind of similar to, like, a language.

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If let's say, you came out of a language and
you taught this language to the two of us

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and we talked it to a bunch of people, you
couldn't just turn please into a really vulgar word.

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You've talked to us, we understand that to
be the case on mathematics, it's kind of like,

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once we agree on a truth, or we agree on symbols,
then it reaches this consensus, it isn't down

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to a particular individual to be able to change it.

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So, I hope that was a good analogy.

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Yeah.

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And also, we always try to talk also to, in
beginner language, sort of, in our podcast

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and there might be a lot of people who are
hearing the term Polkadot for the first time.

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And you are building this on Polkadot, right?

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So, if you could just give people who are
not familiar with Polkadot, what is it and

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why Polkadot?

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Most definitely.

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So, I guess a lot of you have heard about
Bitcoin.

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If you haven't heard about Bitcoin, 
Bitcoin is, like, a decentralized bank.

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It's a decentralized way of 
transferring value and storing value.

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It starts at about 11 years ago, 2008, 2009
after the global financial crisis.

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And then, a few years later, Vitalik Buterin,
he wanted to build improved Bitcoin, but they

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didn't let him improve bitcoin, so he launched
Ethereum and Ethereum talks about smart contracts.

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It's like, you know, decentralized payments
is cool, like Bitcoin offers.

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What's even better, is building other decentralized
things, like a decentralized social network,

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a decentralized news platform, 
a decentralized marketplace.

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So, Ethereum, basically let everyone build on top 
of this one, it's called general purpose blockchain.

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This general purpose computer, but then, the
unfortunate thing is everyone's trying to

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do everything on this one single 
highway, on this one blockchain.

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So, the cool thing about Polkadot, it's from
the person who built Solidity, the coding

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language for Ethereum and he said, if I was
to build this again, how would I do better?

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And he thought, what I'm going to do is, I'm
going to make a way for you to build your own Ethereum.

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And when you build your own Ethereum, on top
of this thing called Polkadot, we're going

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to connect your version, your 
blockchain to another blockchain.

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We're going to create application specific
blockchain, so blockchains which work for

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a particular application.

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00:13:26,240 --> 00:13:31,845
So in the case of the Unit Network, we believe
that we're the most advanced and simple token builder.

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So, with the blockchain for the token economy.

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And we basically allow tokens to be created
and allow them to thrive.

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Okay.

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00:13:39,490 --> 00:13:45,610
And coming back to token economy, like, how
big is it right now?

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00:13:45,610 --> 00:13:54,010
And, I mean how many tokens can I really expect
in the future and how will I ever assess that,

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which token to really go for, which is legit
and what are the answers to these questions?

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00:14:04,180 --> 00:14:05,180
It's a great question.

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00:14:05,180 --> 00:14:07,060
So, like, what and how big is the token economy.

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00:14:07,060 --> 00:14:09,200
So, I guess, what are tokens?

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00:14:09,200 --> 00:14:10,200
Coins and tokens are quite similar.

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The difference between a coin and a token,
the coin has its own blockchain but if you

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00:14:13,480 --> 00:14:17,620
look at tokens it's about 8.000 tokens and
if you count the crypto market cap or the

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00:14:17,620 --> 00:14:23,540
token market cap, it's between two to three
trillion dollars, which, sounds like a lot

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00:14:23,540 --> 00:14:29,068
of money, but it's only, the biggest company in the 
world, is Apple, which is about two to three trillion.

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00:14:29,100 --> 00:14:32,500
Tesla, just crossed over being worth one trillion
and that's just one company.

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00:14:32,500 --> 00:14:36,720
And if you think about the number of people
and the number of companies in the world,

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00:14:36,720 --> 00:14:40,480
you think, a lot of governments are way bigger
than companies, companies like a subset of

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00:14:40,480 --> 00:14:45,750
a government, so, they're about seven eight
billion people in the world, we think each

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00:14:45,750 --> 00:14:49,030
person is gonna have a token, we think more
than having a personal token, they're gonna

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00:14:49,030 --> 00:14:53,120
have a token for the community, a token for
the different businesses and projects.

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00:14:53,120 --> 00:14:56,010
So, we think there's gonna be 10 billion tokens.

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00:14:56,010 --> 00:14:58,520
Eight to nine, to ten billion tokens.

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00:14:58,520 --> 00:15:00,350
And, where’s the stage now, 
there's eight thousand tokens.

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00:15:00,350 --> 00:15:06,839
So, you know, if this was a party, the music hasn't 
turned on, there's nobody here, we're just such early days.

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00:15:06,870 --> 00:15:10,060
So, when you look at like, 2.5 trillion it
sounds like a lot, but it's really just scratching

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00:15:10,060 --> 00:15:14,912
the surface, in terms of what's to come for
how big this industry and economy would be

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00:15:14,912 --> 00:15:18,120
and another good analogy is to, 
you know, you think about mobile.

216
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So, when Instagram got bought by Facebook
for a billion dollars it was 18 months old,

217
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it had 30 million users and people were like
wow isn't it crazy that Facebook is spending

218
00:15:26,580 --> 00:15:31,230
a billion dollars of cash to buy this new
picture of camera application?

219
00:15:31,230 --> 00:15:37,070
You know, that Apple could just add filters
into their camera app and just kill Instagram,

220
00:15:37,070 --> 00:15:44,911
but then, it turned out to be an amazing acquisition,
because Facebook's most valuable asset is now Instagram.

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They saw the opportunity of mobile.

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So, most people in the world, most companies,
most leaders, they don't see yet, the potential

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and possibility of tokens, so I guess our
responsibility and our vision and our mission

224
00:15:55,190 --> 00:16:01,995
and our purpose behind Unit is to really bring
the future and the value of tokens to the entire world.

225
00:16:02,970 --> 00:16:07,890
And, how many tokens have you helped launch?

226
00:16:07,890 --> 00:16:09,770
I mean does that question make sense?

227
00:16:09,770 --> 00:16:15,100
Yep, so there's about 200 tokens, which have
been issued on the Unit Network at the moment.

228
00:16:15,100 --> 00:16:16,100
Okay.

229
00:16:16,100 --> 00:16:20,460
And, you know, we're launching our Unit Ventures
Program, starting January, so 30 projects

230
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will go to our Ventures Program in the first batch.

231
00:16:22,500 --> 00:16:26,540
Our second batch, we increase this to 100
and then we want to work to a point where

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00:16:26,540 --> 00:16:30,680
it's a thousand projects every batch so, our
batches run for three months, we have four

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00:16:30,680 --> 00:16:35,060
batches a year, so it's a thousand times four,
so we expect to have four thousand projects

234
00:16:35,060 --> 00:16:38,850
going through our Unit Ventures Program every
year and we think that this will serve as

235
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a nice base for the entire token economy.

236
00:16:42,040 --> 00:16:47,790
And you also have parameters about judging
which token you want to actually help launch

237
00:16:47,790 --> 00:16:49,320
and, you know, are there rejections?

238
00:16:49,320 --> 00:16:58,880
I mean, I don't know if, so, how do you really
assess that and what's your like, say checklist?

239
00:16:58,880 --> 00:16:59,880
How do I make it?

240
00:16:59,880 --> 00:17:03,390
So, it's tomorrow, I can't be like, okay,
I want to launch a token, so let's launch

241
00:17:03,390 --> 00:17:07,410
a Diksha token, because I'm a content creator and…

242
00:17:07,410 --> 00:17:11,560
It's a great idea, I think, if you launched
a Diksha token, I would buy some and I'd love

243
00:17:11,560 --> 00:17:14,220
to support what you do and 
how big you are successful.

244
00:17:14,220 --> 00:17:18,089
And how do we tell what is the underlying
value of the Diksha token?

245
00:17:18,089 --> 00:17:22,010
There is this concept of a treasury, so, this
concept of a treasury, it's really simple,

246
00:17:22,010 --> 00:17:26,050
but it's also super revolutionary and nobody
else has done it in the blockchain or token

247
00:17:26,050 --> 00:17:30,200
ecosystem and it basically means that, if
I have a Michael token and you have a Diksha

248
00:17:30,200 --> 00:17:34,240
token and both of us have a thousand tokens
each, so, there's a thousand Michael tokens,

249
00:17:34,240 --> 00:17:37,030
a thousand Diksha tokens, a thousand Yip tokens.

250
00:17:37,030 --> 00:17:41,390
If there's nothing in the treasury, it means
that, if someone bought each of our tokens

251
00:17:41,390 --> 00:17:49,268
and we kind of gave up on the token or ran
away, they would lose 100% of whatever they bought.

252
00:17:49,280 --> 00:17:52,270
So, if they bought it at a dollar and there
were zero dollars in the treasury, then it

253
00:17:52,270 --> 00:17:57,060
would drop from a dollar to 50 cents, to 40,
to 30, to 20, to 10, to 5, to 0 effectively.

254
00:17:57,060 --> 00:18:02,240
But if there was 500 dollars in the Diksha
treasury, that means that, at least the lowest

255
00:18:02,240 --> 00:18:06,810
price of the Diksha token is gonna be 50 cents,
meaning that, someone might pay three dollars

256
00:18:06,810 --> 00:18:09,060
for it, they might pay seven dollars, 
twenty dollars for it.

257
00:18:09,060 --> 00:18:12,730
But, if people start selling, it won't drop
below 50 cents, because there's a thousand

258
00:18:12,730 --> 00:18:14,980
Diksha tokens and there's 500 dollars.

259
00:18:14,980 --> 00:18:19,640
So, it sounds very simple, put funds into
a treasury, the treasury's providing this

260
00:18:19,640 --> 00:18:24,440
fundamental book value but, why it's super
interesting is, because then you can provide

261
00:18:24,440 --> 00:18:29,140
products and services, you can create lots
of value for the world and this is going to

262
00:18:29,140 --> 00:18:33,850
generate profit, which you put into the treasury
and when your treasury value goes up, your

263
00:18:33,850 --> 00:18:36,240
floor price increases and then 
your token price goes up.

264
00:18:36,240 --> 00:18:41,820
So, it gives a level of economic fundamentals
and, for instance, if the Yip token has gone

265
00:18:41,820 --> 00:18:46,760
up five times in price, the two of us can
go, wow, I understand why the Yip token has

266
00:18:46,760 --> 00:18:50,850
gone up so much in price, because, Yip has
done a really good job to build up a treasury,

267
00:18:50,850 --> 00:18:55,400
which is providing amazing products, amazing
services and this is generating profit, which

268
00:18:55,400 --> 00:18:57,340
it puts into the treasury.

269
00:18:57,340 --> 00:19:02,730
So I think this is super cool as a way of
addressing and understanding how to value

270
00:19:02,730 --> 00:19:06,930
different tokens, because currently, you can
look at different coins and tokens on two

271
00:19:06,930 --> 00:19:10,870
popular sites, Coinmarketcap or Coingecko
and you're like, wow, this project's worth

272
00:19:10,870 --> 00:19:15,071
tens of billions, this one's hundreds of millions,
but there's no like, as you say, parameter

273
00:19:15,071 --> 00:19:19,010
for assessing what is the underlying value
that's being created or generated or backing

274
00:19:19,010 --> 00:19:23,190
up the token, but, the Unit 
treasury really solves for that.

275
00:19:23,190 --> 00:19:28,367
And the Unit treasury is 
centralized or decentralized?

276
00:19:28,801 --> 00:19:29,840
Decentralized, so, 
you know, everything…

277
00:19:29,840 --> 00:19:30,840
Oh wow.

278
00:19:30,840 --> 00:19:37,580
What we’re doing in Unit, it is with a Web
3.0 decentralized approach from day one, so…

279
00:19:37,580 --> 00:19:38,580
Okay.

280
00:19:38,580 --> 00:19:42,700
You know, we wouldn't be doing, someday if
we couldn't move it to a point of complete

281
00:19:42,700 --> 00:19:47,640
decentralization, or it would 
require a central actor, so…

282
00:19:47,640 --> 00:19:53,540
And the cool thing is, the Diksha treasury,
you put these funds in the treasury, we don't

283
00:19:53,540 --> 00:19:56,090
have to trust you that the money is there.

284
00:19:56,090 --> 00:19:59,670
It's held in digital assets, once you put
funds in there, the only people that can access

285
00:19:59,670 --> 00:20:04,920
it are myself and Yip who own 10% of the Diksha
tokens, so, you know, if nobody buys these

286
00:20:04,920 --> 00:20:10,209
tokens from us, we can go to the treasury and claim 10% 
of the treasury and give back our 10% of tokens.

287
00:20:10,230 --> 00:20:14,013
So it really is an effective way of doing,
creating this floor price.

288
00:20:15,790 --> 00:20:16,790
So, great Michael.

289
00:20:16,790 --> 00:20:21,920
I want to come back to your life in Indonesia
and Bali that I'm very envious of, but before

290
00:20:21,920 --> 00:20:25,950
that, I'll have a little 
bit of chat with Yip as well.

291
00:20:25,950 --> 00:20:31,460
So, Yip, you know we were talking about Axie
Infinity and in one of the previous podcasts

292
00:20:31,460 --> 00:20:36,910
we featured them and they're 
a project from Vietnam on play-2-earn.

293
00:20:36,910 --> 00:20:45,720
And sort of that, it really intrigued my interest
in, particularly Asia, that, what are the

294
00:20:45,720 --> 00:20:53,085
kind of crypto projects, or use cases that are coming, 
in the Web3 economy, that are coming from Asia.

295
00:20:53,100 --> 00:21:00,530
So, do you think you'll be able to give us
a sense of like, how far Asia is when it comes

296
00:21:00,530 --> 00:21:07,366
to crypto projects and innovation in Web3 and are there 
any interesting use cases that come to your mind?

297
00:21:10,136 --> 00:21:17,376
So, I think what will drive crypto adoption in the future 
is two things that Michael has already briefly mentioned.

298
00:21:17,390 --> 00:21:18,980
One is mobile adoption.

299
00:21:18,980 --> 00:21:24,410
So the moment that everybody is on their mobiles
and can do everything from their mobile, which

300
00:21:24,410 --> 00:21:30,556
is typically the younger population, the moment
we have instant connectivity and adoption across all.

301
00:21:30,559 --> 00:21:38,164
So a few things that need to be solved there, is just create 
ways for everyone to participate in the internet.

302
00:21:38,180 --> 00:21:43,820
We are already having a few companies or organizations,
projects coming up that provide decentralized

303
00:21:43,820 --> 00:21:48,130
internet, helping the, let's say, instead
of having the unbanked only gain banking,

304
00:21:48,130 --> 00:21:50,940
also the unconnected to gain connectivity.

305
00:21:50,940 --> 00:21:54,940
So I think that's where you're going to see
a lot of use cases, in particular looking

306
00:21:54,940 --> 00:22:00,360
at economies like Vietnam, where the average
age is something around 25 years old.

307
00:22:00,360 --> 00:22:03,760
It's completely a different world than what
you're seeing in Germany, where the average

308
00:22:03,760 --> 00:22:09,295
age is 45 years old, that's where I live at
the moment, where we have very little crypto adoption.

309
00:22:09,310 --> 00:22:13,890
You look at the economies of the future, it's
actually at a stage where people can learn,

310
00:22:13,890 --> 00:22:18,020
actually in Unit Masters, we see that after
six weeks of training, basic training, people

311
00:22:18,020 --> 00:22:23,260
are already going out and issuing their own
tokens, are inspired to create their own tokens,

312
00:22:23,260 --> 00:22:27,170
to launch their mom-and-pop businesses, right?

313
00:22:27,170 --> 00:22:32,130
One of the use cases, or categories of use
cases we have in Unit economy is actually,

314
00:22:32,130 --> 00:22:39,240
we provide tools for the long tail tokens,
like for people who want to go crypto native

315
00:22:39,240 --> 00:22:45,210
with very predictable businesses, like businesses
with predictable revenue streams, come on

316
00:22:45,210 --> 00:22:49,059
to the token economy, so what you would see
in the future is hopefully not too far away

317
00:22:49,059 --> 00:22:54,370
actually from the moment that we are speaking,
that like a restaurant in the neighborhood

318
00:22:54,370 --> 00:22:58,480
can provide a token service for their community.

319
00:22:58,480 --> 00:23:04,290
Others can create education services for their
community and it's like small things that

320
00:23:04,290 --> 00:23:10,059
you will see popping up super super fast in
the emerging economies, not only talking about

321
00:23:10,059 --> 00:23:14,650
Asia for example, we can also talk about Africa,
where I've been last week, just spending a

322
00:23:14,650 --> 00:23:19,830
week teaching, you know, startups about how
to tap into the blockchain economy.

323
00:23:19,830 --> 00:23:24,080
What you're seeing is like, now people come
back with thinking of, how can we actually

324
00:23:24,080 --> 00:23:30,300
solve problems such as very 
very high interest rates?

325
00:23:30,300 --> 00:23:36,540
Because of, like, inefficient banking structures,
how can we provide decentralized banking services?

326
00:23:36,540 --> 00:23:40,230
How can we provide collateralization?

327
00:23:40,230 --> 00:23:45,370
Building on the existing social bank clubs
that are run across different economies already

328
00:23:45,370 --> 00:23:51,297
in southeast Asia with the micro finance learning
clubs, or in Africa we have a lot of these coming up.

329
00:23:51,309 --> 00:23:57,200
So, overall I think the bigger use cases we're
seeing, apart from like gaming in the metaverse,

330
00:23:57,200 --> 00:23:59,770
which Axie Infinity is already doing, it's
great.

331
00:23:59,770 --> 00:24:04,543
We will see actually more fundamental use
cases on the long-tail token economy side.

332
00:24:05,970 --> 00:24:07,850
Yeah.

333
00:24:07,850 --> 00:24:17,489
And if you have to say the top three use cases
that you can vouch for, could I ask, what would they be?

334
00:24:17,500 --> 00:24:21,220
I'd be curious to see Michael.

335
00:24:21,220 --> 00:24:23,080
To hear what Michael was saying about that.

336
00:24:23,080 --> 00:24:24,330
I'm happy to add mine.

337
00:24:24,330 --> 00:24:25,330
Most definitely.

338
00:24:25,330 --> 00:24:31,300
So, I think, similar to the internet on the
mobile, everything which was in the non-internet

339
00:24:31,300 --> 00:24:37,480
and non-mobile world moved to the internet, so, 
you know, things like the newspaper, newspaper

340
00:24:37,480 --> 00:24:45,984
went online, shopping went online, education
went online, art went online, travel went online.

341
00:24:45,984 --> 00:24:48,580
So, every single industry went on to the internet.

342
00:24:48,580 --> 00:24:53,060
Same with the mobile, every single industry
went onto mobile, you know, if it didn't have

343
00:24:53,060 --> 00:24:58,497
an app or there wasn't an app for it, then, you know, 
there's an opportunity to build an app for it.

344
00:24:58,510 --> 00:25:00,730
So, it's the same with the 
token and blockchain world.

345
00:25:00,730 --> 00:25:05,540
Well, if there isn't a decentralized app or
a token for a particular industry, or a particular

346
00:25:05,540 --> 00:25:07,070
business, then there is an opportunity.

347
00:25:07,070 --> 00:25:11,420
If there's a supermarket, which is centrally
owned and centrally run, it's an opportunity

348
00:25:11,420 --> 00:25:15,260
for you to create a supermarket, which is
decentralized in ownership and decentralized

349
00:25:15,260 --> 00:25:16,260
in the way it operates.

350
00:25:16,260 --> 00:25:22,880
So, we think this is going to ignite so much
innovation and it's such a big opportunity

351
00:25:22,880 --> 00:25:24,360
and we think we're very close to that.

352
00:25:24,360 --> 00:25:28,580
What it takes is just a few case studies,
a few hundred case studies of projects, which

353
00:25:28,580 --> 00:25:30,840
do this and then people are gonna go, wow,
I'm gonna do that too, I'm gonna apply it

354
00:25:30,840 --> 00:25:33,832
to my existing business and 
it's gonna really transform.

355
00:25:35,660 --> 00:25:36,660
Okay.

356
00:25:36,660 --> 00:25:38,700
And you second that, Yip.

357
00:25:38,700 --> 00:25:39,700
Yeah.

358
00:25:39,700 --> 00:25:47,210
I, personally, I'm quite very optimistic about
different layers of the tech stack, when you

359
00:25:47,210 --> 00:25:51,760
look at the security layer, 
base layer of technology.

360
00:25:51,760 --> 00:25:55,700
We will see, hopefully, in the future a lot
of decentralized initiatives, like I could

361
00:25:55,700 --> 00:25:58,500
imagine women runs, taking notes.

362
00:25:58,500 --> 00:26:03,850
Like women in villages for example, that come
together, have a lending club and so on and

363
00:26:03,850 --> 00:26:10,080
learn how to provide decentralized infrastructure,
in a way that is like, generating income for

364
00:26:10,080 --> 00:26:15,920
them and with that income for example, they
can then go and fund other small token economy

365
00:26:15,920 --> 00:26:18,840
projects, using the Unit chain.

366
00:26:18,840 --> 00:26:19,840
This is one of the use cases.

367
00:26:19,840 --> 00:26:20,840
The second use case.

368
00:26:20,840 --> 00:26:27,510
I think everything related to helping the
gaming, the metaverse economy come to life.

369
00:26:27,510 --> 00:26:31,620
So, what we're seeing is in the future, a
lot of time people will spend time in these

370
00:26:31,620 --> 00:26:36,960
VR AR mixed reality environments and 
all of this needs creators and so on.

371
00:26:36,960 --> 00:26:42,430
So a lot of people can already start to earn
a living, producing content, like this is

372
00:26:42,430 --> 00:26:48,380
so important, it's not about consuming gaming,
but being able to consume it and produce at

373
00:26:48,380 --> 00:26:53,520
the same time, so you can become a creator
in that new economy and already play and earn,

374
00:26:53,520 --> 00:26:55,360
but also create and earn.

375
00:26:55,360 --> 00:26:58,420
And I think, this is something, you know,
that will reduce a lot of inequities in the

376
00:26:58,420 --> 00:27:02,960
market, because right now, if you don't have
education and you don't have proper training,

377
00:27:02,960 --> 00:27:09,120
all that is left for you is like not good
revenue creating opportunities, right?

378
00:27:09,120 --> 00:27:15,050
And we can close that gap and within the blockchain
economy, it's very very easy to get into it

379
00:27:15,050 --> 00:27:17,470
and contribute from day one.

380
00:27:17,470 --> 00:27:21,480
We are still and I think, I just want to add
to that, when you asked earlier, how big is

381
00:27:21,480 --> 00:27:22,650
the market actually.

382
00:27:22,650 --> 00:27:28,714
You know, the global, if you look at world bank data 
for example, the global stock market is 100 trillion.

383
00:27:28,714 --> 00:27:32,900
So, if we have two to three trillion, like
Michael said earlier, we had 2-3% of possible

384
00:27:32,900 --> 00:27:37,590
stock market and then if you take into account
all these inflation and so on, which is not

385
00:27:37,590 --> 00:27:43,970
incorporated in that, you can see that we
have a lot of like 30x 40x 50x room to grow

386
00:27:43,970 --> 00:27:47,690
within the next like, you know, 
very seizable time frame.

387
00:27:48,690 --> 00:27:49,690
Yeah. Wow.

388
00:27:49,690 --> 00:27:54,640
I'm glad you spoke about, what did 
you say, create and earn.

389
00:27:54,640 --> 00:28:01,410
And talking of create to earn, Michael, correct
me if I'm wrong in this information, but I

390
00:28:01,410 --> 00:28:05,640
think you are based in Bali right now, correct?

391
00:28:05,640 --> 00:28:06,940
Okay, awesome.

392
00:28:06,940 --> 00:28:13,460
And you, I heard one of your interviews where
you spoke about a sort of co-living village

393
00:28:13,460 --> 00:28:20,220
of artists and creators and now we see a lot
of artists and creators actually, you know,

394
00:28:20,220 --> 00:28:23,980
trying to understand blockchain and token and NFTs.

395
00:28:23,980 --> 00:28:31,830
So tell us about your groundwork there, like,
what are you trying to do with this co-living

396
00:28:31,830 --> 00:28:36,340
village and is it something 
that is, create and earn?

397
00:28:36,340 --> 00:28:37,340
Related to, create and earn?

398
00:28:37,340 --> 00:28:38,884
Great question Diksha.

399
00:28:38,884 --> 00:28:43,240
So, you know, if you think of fashion, many
people think of Milan, they think of Paris.

400
00:28:43,240 --> 00:28:47,310
If people ask about the internet, they think
of Silicon Valley or San Francisco.

401
00:28:47,310 --> 00:28:51,730
Like with tokens, the blockchain, the crypto world isn't 
really a hub, you know, it's kind of decentralized, you know.

402
00:28:51,760 --> 00:28:55,809
So I guess, what we're trying to do is building
like the Silicon Valley for the blockchain

403
00:28:55,809 --> 00:28:59,370
crypto space and show, give people a glimpse
of what the future society looks like, 

404
00:28:59,370 --> 00:29:03,690
you know, where I meet someone like you, I meet
someone like someone else and I go wow, she's

405
00:29:03,690 --> 00:29:08,970
so inspiring, I want to support her, how can
I invest in her or if someone does have money,

406
00:29:08,970 --> 00:29:14,586
how can they do some work to get a piece of
their future success and get a piece of the pie?

407
00:29:14,600 --> 00:29:18,220
So we want to show how, you know, we're doing
two village projects here, one of them will

408
00:29:18,220 --> 00:29:22,370
accommodate three and a half thousand or four
thousand people, the second one will accommodate

409
00:29:22,370 --> 00:29:24,310
between 35.000 to 40.000 people.

410
00:29:24,310 --> 00:29:32,270
We want to show how both of these, essentially village and 
town, can showcase what the future society looks like.

411
00:29:32,300 --> 00:29:36,850
So, if you think of, imagine all of the apps
that exist now, you know, whether it's Uber

412
00:29:36,850 --> 00:29:42,120
or Airbnb or Wikipedia, many of these things,
you know, now they are in lots of cities around

413
00:29:42,120 --> 00:29:46,040
the world, so what we're trying to do, is
imagine you were back in time and you built

414
00:29:46,040 --> 00:29:52,670
a way for a small case study of experiment
of what Uber looked like for a small town,

415
00:29:52,670 --> 00:29:55,000
what Airbnb looked like for a small town.

416
00:29:55,000 --> 00:30:03,040
It's possible to do it all at once, but we
just want to show for a community of four

417
00:30:03,040 --> 00:30:07,405
thousand people, a community of 40.000 people what it 
looks like to live and to operate within a token economy.

418
00:30:07,672 --> 00:30:08,974
Yeah.

419
00:30:08,974 --> 00:30:15,630
So, what exactly, how does this model of yours
or experiment, I don't know if I can call

420
00:30:15,630 --> 00:30:20,090
that, really work, like 
in a logistical way, yeah.

421
00:30:20,090 --> 00:30:26,550
It basically, is a society where the ownership
is distributed, so, if you go to a restaurant,

422
00:30:26,550 --> 00:30:30,270
you can go onto your phone and buy into a
piece of the restaurant, or you meet, someone

423
00:30:30,270 --> 00:30:35,500
who’s an artist, or someone who's a writer, you can 
find out what their token is and buy tokens of them.

424
00:30:35,530 --> 00:30:36,530
Okay.

425
00:30:36,668 --> 00:30:41,580
That is the distributed cooperative 
economy that Unit helps to power.

426
00:30:41,580 --> 00:30:43,679
All right, awesome.

427
00:30:43,679 --> 00:30:52,720
And, so, talking about Unit again, how far
do you think you are in your mission of what

428
00:30:52,720 --> 00:30:57,210
you are trying to solve with Unit and probably
I think this is the question I should have

429
00:30:57,210 --> 00:31:05,040
asked a little bit earlier, but if you could
explain the structure of what Unit is and

430
00:31:05,040 --> 00:31:10,980
mission you already spoke a bit about, but
really, what are your future plans with Unit?

431
00:31:10,980 --> 00:31:15,780
So, yeah, in terms of where we're at the moment
and where we're going to be in the future,

432
00:31:15,780 --> 00:31:19,960
at the moment we're a team of 60 people, our
community is about 30.000 people, we've got

433
00:31:19,960 --> 00:31:24,860
200 tokens issued, our initiatives are going
extremely well with five-minute initiatives

434
00:31:24,860 --> 00:31:29,730
conferences, ventures, 
master's program university and news.

435
00:31:29,730 --> 00:31:37,179
We are working towards having a few hundred
case studies of token-based projects and building

436
00:31:37,179 --> 00:31:38,540
out hubs in lots of different cities.

437
00:31:38,540 --> 00:31:43,130
We are working on 50 different cities and
50 different industries, working on building

438
00:31:43,130 --> 00:31:44,669
teams within each of them.

439
00:31:44,669 --> 00:31:48,780
In terms of where we are at the moment relative
to where we're going to be in the future.

440
00:31:48,780 --> 00:31:52,890
So, our goal is seven billion people in the
world having a token for themselves.

441
00:31:52,890 --> 00:31:56,830
We're at a moment now, where there's eight
thousand tokens that exist outside of Unit,

442
00:31:56,830 --> 00:31:59,050
there's about 200 tokens 
that exist within Unit.

443
00:31:59,050 --> 00:32:04,590
So, it might seem that we have a long way
to go so, I guess by 2025 we want to have

444
00:32:04,590 --> 00:32:10,840
the early adopters, the 3-4-5% of society
creating a token, buying into tokens, supporting

445
00:32:10,840 --> 00:32:14,950
tokens and then, what we expect is between
2025 and 2030 for everyone else in the 

446
00:32:14,950 --> 00:32:22,407
world to either be creating tokens, buying into
tokens and that's when everyone else is going to catch up.

447
00:32:23,508 --> 00:32:28,710
So, I'm curious, you're from 
the VC world as well, right?

448
00:32:28,710 --> 00:32:35,059
You were working with Venture Capital and
then you've been a founder yourself and 

449
00:32:35,059 --> 00:32:42,560
I particularly, when I talk to traditional VCs
and startups that have nothing to do with

450
00:32:42,560 --> 00:32:50,870
tokens or crypto and it's something they just
don't want to touch or invest in, so what

451
00:32:50,870 --> 00:32:57,070
has been your experience when you talk to
that ecosystem of yours, that you were a part

452
00:32:57,070 --> 00:33:03,570
of, or were you luckily part of people who
were already early adopters of crypto?

453
00:33:03,570 --> 00:33:10,000
And I'm just trying to get a sense of, do
you feel that we are getting out of the bubble

454
00:33:10,000 --> 00:33:12,620
and really traditional VCs 
are trying to understand?

455
00:33:12,620 --> 00:33:14,290
I think, still not.

456
00:33:14,290 --> 00:33:19,660
So, I think we still need to cross over the
chasm, the innovation chasm, and I think the

457
00:33:19,660 --> 00:33:24,936
treasury is what's going to get, you know,
the serious investors of the world to understand tokens.

458
00:33:24,950 --> 00:33:28,549
Until we have this treasury, people are going
to look at tokens and they're not going to

459
00:33:28,549 --> 00:33:34,012
get it, they're going to, like how can something which is 
a few months old be worth a few hundred million dollars?

460
00:33:34,030 --> 00:33:37,090
They're gonna be like, this is ridiculous,
what is the product being sold?

461
00:33:37,090 --> 00:33:38,540
Where's the value coming from?

462
00:33:38,540 --> 00:33:40,870
You can't just create something there and
you can't just pump it up and then dump it.

463
00:33:40,870 --> 00:33:46,929
It needs to have, you know, some real underlying
fundamentals and we're super confident because

464
00:33:46,929 --> 00:33:51,740
we think that, Unit is going to help you guys
there and I speak to a lot of my friends,

465
00:33:51,740 --> 00:33:55,330
who are, you know, super high profile entrepreneurs
and investors and they just look at this space

466
00:33:55,330 --> 00:34:00,839
and they go like, it's just so disappointing, it's full 
of scams, so little substance, so little value creates it.

467
00:34:00,840 --> 00:34:05,010
But, you know, there are a few that are in
the space, which see the future.

468
00:34:05,010 --> 00:34:09,409
It's kind of like, if you looked at the app
ecosystem and you're like well, there's so

469
00:34:09,409 --> 00:34:14,029
many apps, which people are downloading, 
but it's not making any money.

470
00:34:14,029 --> 00:34:18,979
Apps are getting a crazy amount of valuation,
but none of them have real business models,

471
00:34:18,979 --> 00:34:24,750
or internet companies, which are just 
hemorrhaging and wasting Venture Capital money.

472
00:34:24,750 --> 00:34:29,960
So, we think that it's just a matter of time
before the real projects emerge, underlying

473
00:34:29,960 --> 00:34:34,979
business models, products and substance, which
allows them to have long-term sustainability.

474
00:34:34,979 --> 00:34:41,690
Okay, yeah, I mean particularly I also feel
that, because I'm in touch with both sides

475
00:34:41,690 --> 00:34:48,389
and I mean, that's what also we at Ocean,
through this podcast, are trying to do and

476
00:34:48,389 --> 00:34:52,479
close that gap a bit and try 
to educate people around it.

477
00:34:52,479 --> 00:34:59,900
So, yeah, it's actually been a great conversation
with you and Yip both and on a closing note

478
00:34:59,900 --> 00:35:09,349
I would ask you to leave us with one message
that we do with every guest per se.

479
00:35:09,349 --> 00:35:17,430
Ideally related to democratization of data
and one message that you want to leave and

480
00:35:17,430 --> 00:35:20,980
that you want people to take 
through this entire conversation.

481
00:35:20,980 --> 00:35:27,670
Yeah, most definitely, so I would recommend
creating a token, issuing a token on Unit.

482
00:35:27,670 --> 00:35:31,069
Building an underlying economic model behind it.

483
00:35:31,069 --> 00:35:34,539
So, a lot of people think that tokens should
be like currencies, you don't have to back

484
00:35:34,539 --> 00:35:38,640
it by anything, you don't need a business model.

485
00:35:38,640 --> 00:35:44,549
I would believe that every token is more like
a software share, where it has to be providing

486
00:35:44,549 --> 00:35:49,700
products and services that have an economic
model, because then it basically has the financial

487
00:35:49,700 --> 00:35:54,630
sustainability and economic sustainability
to grow in the long run, otherwise people

488
00:35:54,630 --> 00:35:58,979
buy it, skyrockets in value and then people
start selling and then it drops and then people,

489
00:35:58,979 --> 00:36:02,369
oh my gosh it's the end, I lost 
so much money and then cycle repeat.

490
00:36:02,369 --> 00:36:08,066
So the cool thing about this treasury is it
really allows for that long term sustainability.

491
00:36:08,933 --> 00:36:10,819
Okay.

492
00:36:10,819 --> 00:36:17,450
Thank you then, Michael it was great talking
to you and we'll be in touch, once we have

493
00:36:17,450 --> 00:36:20,319
probably a token for our podcast itself.

494
00:36:20,319 --> 00:36:25,883
Yeah please do it, I would love to buy some
and share with our community and share with

495
00:36:25,883 --> 00:36:28,920
our close advisor and friends and I really
appreciate the kind of opportunity.

496
00:36:29,187 --> 00:36:30,121
Looking forward to it.

Shiv Malik - Why We Need Data Unions to Support the Data Economy.vtt

WEBVTT

00:00.800 --> 00:03.120
An important note before we start.

00:03.120 --> 00:07.520
This episode was recorded on the 9th of Αpril 2021.

00:08.240 --> 00:12.480
This is when Shiv Malik was still 
a part of Streamr as Head of Growth,

00:13.040 --> 00:16.320
now he's the CEO of Pool Foundation.

00:17.040 --> 00:18.160
Enjoy the episode.

00:19.120 --> 00:24.400
What has Web3 done to date? You've got money, 
digital money, that's Βitcoin.

00:24.400 --> 00:28.960
Got contracts, really important, in with Ethereum.

00:29.600 --> 00:32.240
And we've got a way to trade 
and financialize all of that, 

00:32.240 --> 00:35.520
that's DEXs. What do NFTs represent in that schema?

00:36.320 --> 00:36.820
Assets.

00:37.920 --> 00:40.640
Well, what are some other great assets?

00:41.440 --> 00:45.280
Well, it's really hard to take a house 
and put that on the blockchain.

00:45.280 --> 00:47.360
It's really really hard to do that.

00:47.360 --> 00:52.080
But data is worth trillions 
and it's already digitally native, 

00:52.080 --> 00:53.120
but it is stuck in Web2.

00:56.400 --> 01:01.360
Voices of the Data Economy, 
a podcast supported by Ocean Protocol Foundation.

01:02.080 --> 01:04.960
We bring to you the voices shaping the Data Economy 

01:04.960 --> 01:06.720
and challenging it at the same time.

01:07.280 --> 01:11.840
We talk about breaking down data silos 
and equalizing access to data for all.

01:13.920 --> 01:17.760
Hey everyone, welcome to this episode 
of Voices of the Data Economy.

01:17.760 --> 01:19.440
I'm here with Shiv Malik.

01:19.440 --> 01:20.400
Hey Shiv.

01:20.400 --> 01:22.080
Hey, hi, how are you doing?

01:22.080 --> 01:23.200
Nice to see you.

01:23.200 --> 01:25.600
And Diksha as always, hey Diksha.

01:25.600 --> 01:26.560
Hello both of you.

01:27.120 --> 01:27.620
Hello.

01:28.320 --> 01:34.640
Shiv, I think we met more than a year ago
in Berlin during the RadicalxChange conference.

01:35.200 --> 01:38.320
I always wanted to have, 
like this kind of conversation on a podcast,

01:38.320 --> 01:40.160
so it's great to see you here.

01:40.160 --> 01:43.520
Yeah, it was a great event, that one in Berlin.

01:43.520 --> 01:45.280
It was like a year, yeah, a year and a half ago.

01:46.800 --> 01:49.280
It's just, it was a really intimate conference,

01:49.280 --> 01:51.760
there were some great connections 
to be made there and...

01:52.880 --> 01:53.840
Really tight space.

01:56.240 --> 01:59.920
Yeah it got very hot and sweaty, 
very quickly, but, 

01:59.920 --> 02:02.480
I think that Trent was there, 
Vitalik was there.

02:02.480 --> 02:02.980
Yeah.

02:03.440 --> 02:05.840
Yeah.

02:05.840 --> 02:07.200
Yeah, yeah, exactly.

02:08.320 --> 02:10.000
Always amusing, always amusing.

02:10.000 --> 02:10.320
Yes.

02:10.320 --> 02:10.998
Okay.

02:11.680 --> 02:14.080
So glad to know both of you 
already know each other, 

02:14.080 --> 02:16.720
but very glad to meet you for the first time Shiv

02:16.720 --> 02:20.480
and thank you for being a part of this episode.

02:21.680 --> 02:25.360
So you've been a former 
investigative journalist with Guardian 

02:25.360 --> 02:27.680
and now you're the Head of Growth at Streamr,

02:28.480 --> 02:32.000
which is a decentralized platform for real-time data.

02:33.520 --> 02:36.640
Actually I'm really curious how you got into this world 

02:36.640 --> 02:40.640
of Data Economy from journalism and what's really,

02:41.680 --> 02:45.920
what really inspired you to get 
into this movement of data privacy.

02:48.160 --> 02:52.400
So I've been asked this question a few times
and I've never been able to answer it properly,

02:52.400 --> 02:54.960
because I’ve actually never given it, 
I think proper thought, 

02:54.960 --> 03:00.400
like what is it that actually 
motivated me and post event,

03:00.400 --> 03:03.280
everyone has kind of post hoc rationalization.

03:03.280 --> 03:06.000
You're like, yeah I did it because 
of this and that makes sense, 

03:06.000 --> 03:08.080
but that usually isn't why it happened.

03:08.720 --> 03:11.920
Things are kind of serendipitous and things happen 

03:11.920 --> 03:15.200
and you're like, yeah sure 
and it doesn't always make sense.

03:15.200 --> 03:19.440
So I kind of left the Guardian in 2016 
and I was actually, 

03:19.440 --> 03:22.640
I was researching a book 
on mutualism and cooperatives.

03:23.680 --> 03:27.520
And as part of that, someone said have you, 
this is sort of yeah, 

03:27.520 --> 03:29.920
late 2016, do you know anything about Ethereum?

03:30.427 --> 03:30.927
Was like no.

03:31.520 --> 03:35.680
And so they showed me smart contracting 
and the power of that.

03:35.680 --> 03:38.080
I knew about Bitcoin obviously 
from being a journalist and the like, 

03:38.080 --> 03:41.680
but never really got into it. 
But I fell in love with Ethereum

03:41.680 --> 03:45.120
because I suddenly realized, right, 
you can do all these things, 

03:45.120 --> 03:49.680
and just divvy up money in all sorts 
of interesting ways and actually,

03:51.200 --> 03:54.800
at first I was like, this is great 
because like all my transactions 

03:54.800 --> 03:57.760
will be in one place, 
I can file my taxes so easily now.

03:58.640 --> 04:04.240
This is the future, so even at that 
level I was in love with Ethereum.

04:04.240 --> 04:08.640
I was like, no more accountants, 
I'm sold, sign me up.

04:09.920 --> 04:12.640
But then there was this other, 
I think deeper motivation for, 

04:12.640 --> 04:15.760
I kind of ended up with Streamr 
and why I'm kind of doing what

04:15.760 --> 04:21.040
I'm doing now with Data Unions 
and that's journalism, investigative journalism.

04:21.680 --> 04:24.800
It’s about holding people to account, 
holding power to account.

04:26.160 --> 04:28.960
And drilling down and 
exposing what can't otherwise be, 

04:29.520 --> 04:31.680
sort of readily exposed.

04:31.680 --> 04:32.560
Usually wrongdoing.

04:34.560 --> 04:39.680
And I think that the Web3 space 
also does that very well.

04:42.400 --> 04:43.360
And there's this weird other bit, 

04:43.360 --> 04:45.440
which is that I had always been 
interested in the Data Economy.

04:45.440 --> 04:49.360
In 2012, I was invited onto 
a new show to explain myself, 

04:49.360 --> 04:51.120
because I was deleting my Facebook account.

04:51.120 --> 04:53.840
It was such a weird thing to do 
in 2012, they're like yes, 

04:53.840 --> 04:59.840
call Shiv on and, you know, 
trial by kind of public media.

05:00.720 --> 05:03.040
And then, even then 
I was like, look we've all, 

05:03.040 --> 05:06.080
we're already becoming, 
this is at the time of Facebook's IPO,

05:06.080 --> 05:07.760
I said we're becoming serfs.

05:08.800 --> 05:12.560
Data serfs and I don't 
want to be a slave anymore, 

05:12.560 --> 05:13.680
so that's why I'm deleting it.

05:13.680 --> 05:17.680
I don't want Mark Zuckerberg to be any richer
of the fact that I'm producing this value.

05:18.320 --> 05:21.040
So I've always had that and 
then so you marry all those things up 

05:21.040 --> 05:23.840
and the journey starts to make sense I guess.

05:25.600 --> 05:30.000
So you just mentioned 
Data Unions and that's something 

05:30.000 --> 05:33.840
that you've been speaking about a lot 
in the past and for the past one year,

05:33.840 --> 05:39.680
rather to be more specific, and Streamr, 
I think, went live in June last year, 

05:40.400 --> 05:42.480
with the beta version of Data Unions?

05:43.120 --> 05:48.160
So those who are not familiar, 
what actually is a Data Union 

05:48.160 --> 05:51.840
and in the practical world, 
how does it really work?

05:52.640 --> 05:55.120
Yeah, so, I mean, 
I think most of your listeners 

05:55.120 --> 05:58.720
will be really familiar with 
the fact that we all produced information

05:58.720 --> 06:02.160
and other people are harvesting 
that and profiting from it.

06:02.720 --> 06:04.160
And that seems inherently wrong.

06:05.040 --> 06:09.760
And there seems to be no way for ordinary people,
who are actually producing the value to actually

06:09.760 --> 06:11.360
retain any of that value themselves.

06:12.560 --> 06:18.480
So a Data Union is a way of 
pooling data between various parties 

06:19.600 --> 06:21.840
and trying to monetize it, as a collective.

06:22.720 --> 06:26.480
And that sounds really simple, 
that's actually a really, really old idea, 

06:26.480 --> 06:30.960
like it's, you can find stuff going 
dating back to the 90s for sure.

06:30.960 --> 06:32.480
About how this should be done

06:32.480 --> 06:35.680
and actually if you pull it 
together you'll still need 

06:35.680 --> 06:38.080
an organization in the middle 
because actually a lot of this stuff

06:38.080 --> 06:39.680
is about reaching out to data buyers.

06:39.680 --> 06:41.680
You need to pick up a phone 
and speak to people, right?

06:42.240 --> 06:43.280
Machines can't do that yet.

06:44.720 --> 06:45.220
Yet.

06:46.960 --> 06:48.560
Not far off of that happening,

06:48.560 --> 06:49.060
I'm sure.

06:51.440 --> 06:53.760
And you also need to 
be able to market yourself 

06:53.760 --> 06:57.280
and attract new members, so you can 
have more data to this Data Union.

06:59.120 --> 07:02.000
So that's the kind of model 
we went for and it's one really 

07:02.000 --> 07:05.440
well fleshed out by people 
like Jaron Lanier and Glenn Weil,

07:06.560 --> 07:11.200
who we mentioned in regards to RadicalxChange
and that kind of thing, so they'd already kind of,

07:11.200 --> 07:14.800
lots of people have fleshed this out academically,
no one's really done it practically.

07:14.800 --> 07:16.960
And it turns out, when you try 
and do it in practice, 

07:17.520 --> 07:20.000
there are some really, 
like big stumbling blocks

07:20.000 --> 07:22.400
so that's what Streamr wanted to resolve.

07:24.480 --> 07:32.720
So what are the examples of Data Unions
that are there on blockchain, particularly?

07:32.720 --> 07:36.960
And I think some of you already have use cases 

07:36.960 --> 07:40.320
and partners that have 
successful models around this.

07:41.840 --> 07:46.480
Yeah, it's all starting to 
brew wonderfully and take off.

07:46.480 --> 07:48.720
It's, you know, 
that's the most exciting thing.

07:49.440 --> 07:56.800
I can remember in January 2018, 
we were sitting in the Streamr office in Zug

07:56.800 --> 07:59.120
and trying to come up with ideas, like, okay, 

08:01.680 --> 08:06.400
how do we kind of, at heart by the way, 
I should explain Streamr’s initial

08:07.840 --> 08:11.680
and still, core aim is to 
create this peer-to-peer network 

08:11.680 --> 08:17.200
for messaging, for peer-to-peer 
messaging, in a decentralized fashion.

08:17.200 --> 08:20.320
So we already have things that 
do that, like Amazon AWS services 

08:20.320 --> 08:23.280
or UpCloud or whatever, but if you wanted 
to run in a decentralized way,

08:23.280 --> 08:24.240
it's really difficult to do.

08:24.800 --> 08:27.040
It's the kind of thing that could 
power a smart city for example.

08:29.360 --> 08:31.040
And one of the ideas that 
we came up with was obviously 

08:31.040 --> 08:36.960
Data Unions and a few months after that kind 
of fleshed out this original, like diagram.

08:36.960 --> 08:39.600
It should look like something 
like this, just like with a pen 

08:39.600 --> 08:44.000
and a ruler, like really, 
really terrible wireframe drawing.

08:44.000 --> 08:45.840
The kind of thing that 
I'm sure our designer looked at 

08:45.840 --> 08:47.600
and just like, you know, facepalm.

08:49.200 --> 08:50.320
What’s Shiv done again?

08:51.520 --> 08:58.240
But from that journey, we've now seen, I think,
four or five Data Unions start to emanate.

08:58.800 --> 09:03.680
The most prominent of which 
is Swash, it has 20.000 members now.

09:03.680 --> 09:04.560
And what is Swash?

09:04.560 --> 09:08.080
It's a browser plugin, 
so you downloaded this plugin, 

09:08.080 --> 09:09.840
it monitors your web browsing habits

09:10.720 --> 09:13.680
and obviously you're consenting to it,
because you're downloading it and you're getting

09:13.680 --> 09:16.080
the value returned right 
into the browser plugin.

09:16.080 --> 09:19.200
You've got a wallet set up, 
Ethereum wallet address 

09:19.840 --> 09:22.480
and you get paid, 
every time that dataset sells.

09:22.480 --> 09:25.680
So 20.000 is a lot of people, 
I think they need to get 

09:25.680 --> 09:28.160
to about 50.000 before 
they're like fully viable

09:28.160 --> 09:29.280
and they'll get buyers on board.

09:29.840 --> 09:33.360
Couple of other ideas, you can do 
the same thing, it turns out for Spotify.

09:33.360 --> 09:36.320
If you want to port your Spotify 
real time stream of information.

09:37.040 --> 09:42.480
Not very privacy sensitive, so that's good,
port it to a pool of other people and you have

09:42.480 --> 09:48.320
a Data Union that gives buyers, 
like information on what people listen to.

09:48.880 --> 09:51.280
Podcasts and songs and playlists, great!

09:51.840 --> 09:54.880
You know, that stuff, that Spotify 
doesn't sell, at the moment.

09:55.440 --> 09:57.280
And that the music industry really wants to know.

09:58.000 --> 10:02.480
Fitbit, you can do the same thing 
with your Fitbit or Withings, in this case.

10:02.480 --> 10:03.840
Because they have an open API.

10:04.480 --> 10:04.960
Great!

10:04.960 --> 10:06.720
Take that information and bring health data, 

10:06.720 --> 10:10.000
that's already been set up by 
a wonderful developer called Chalil.

10:12.480 --> 10:15.280
And then there's another project 
that's under the radar a little bit.

10:15.280 --> 10:17.120
Actually they're not, 
they have a Twitter account, 

10:17.120 --> 10:21.120
so they tweeted, they're out 
in public, called Unbanks,

10:21.120 --> 10:23.680
same thing with financial transaction data.

10:24.320 --> 10:26.000
The banks already sell this information.

10:27.040 --> 10:29.840
Just they don't give you 
a cut of that, but you can 

10:29.840 --> 10:34.160
easily pool it yourself, through 
open banking infrastructure in Europe.

10:35.120 --> 10:35.600
So, great!

10:35.600 --> 10:39.600
You have a widget read your 
third party, it's your Data Union.

10:39.600 --> 10:42.080
It reads your banking transaction details.

10:42.080 --> 10:44.400
It makes sure it's done in 
a really privacy-centric way, 

10:44.400 --> 10:48.080
so you can't be identified, but 
then you've got a pool of that information,

10:48.080 --> 10:51.200
which is again, people will realize, 
that's probably worth quite a lot of money.

10:51.200 --> 10:51.700
Great!

10:52.240 --> 10:53.200
Return that to the users.

10:55.760 --> 10:57.040
If I could jump in here.

10:58.480 --> 11:02.640
So all or most of these examples are data that 

11:02.640 --> 11:07.520
is already being produced 
and then these Data Unions

11:07.520 --> 11:11.360
or efforts, they're kind of adding 
a monetization layer on top.

11:11.360 --> 11:17.280
Do you know of any examples 
that data is primarily produced 

11:17.280 --> 11:20.720
for this use case of 
Data Unions to be monetized?

11:22.240 --> 11:24.880
Yeah, so, are you asking this?

11:24.880 --> 11:28.080
Which is kind of, how do 
Data Unions encourage data that, 

11:28.080 --> 11:30.960
yeah, just isn't really readily 
available to really be more.

11:30.960 --> 11:34.400
Yeah, it's like is it 
financially viable one day 

11:34.400 --> 11:39.520
or for some use cases to 
generate data just for this?

11:40.320 --> 11:43.280
So we're not quite there in having that, 

11:44.960 --> 11:48.640
an actual example into the 
world yet, but we we're trying.

11:48.640 --> 11:51.040
We're almost getting there 
I think, with pollution monitors.

11:51.760 --> 11:53.680
The pollution monitors are really expensive.

11:53.680 --> 11:56.080
If you want to buy them kind 
of individually, like decent ones, 

11:56.080 --> 11:58.640
you know, kind of two, well not really 
expensive, 200 dollars, right?

11:59.360 --> 12:03.200
Or 100 plus dollars, but 
you know it's, if suddenly, 

12:03.200 --> 12:06.000
if you add the feature that actually you 
could make this money back over time,

12:06.960 --> 12:10.960
then suddenly people go right, okay, 
I've got this and I've got this, 

12:10.960 --> 12:12.560
you know, hopefully it won't cost 100 dollars,

12:12.560 --> 12:15.760
it’ll cost me like 20 over three years, 
because I'll get the money back.

12:16.320 --> 12:17.840
That's the kind of thing that we were looking for.

12:17.840 --> 12:22.320
So suddenly people are like, okay right, 
we'll have one pollution monitor per street

12:22.320 --> 12:26.400
and suddenly you have really 
useful real-time information 

12:26.400 --> 12:29.280
about what's going on and people, 
obviously they care about their kids

12:29.280 --> 12:32.640
and they want to know, like, is it 
a good time to go and walk to school?

12:33.280 --> 12:34.080
Or not?

12:34.080 --> 12:36.240
And if it isn't, I want 
to complain to my counsel 

12:36.240 --> 12:38.560
and now I have the information 
to be able to do that.

12:39.200 --> 12:41.040
And the same thing, by the way, 
it turns up a noise pollution.

12:41.040 --> 12:42.560
People who live next to airports,  

12:42.560 --> 12:46.640
they have terrible time trying to like, 
reduce that noise pollution.

12:46.640 --> 12:49.040
I mean, obviously for the 
last year it's been an irrelevance, 

12:50.000 --> 12:52.240
but they all know it's coming back and then

12:52.240 --> 12:55.040
and we've had people emailing 
us going, we want this system  

12:55.920 --> 12:57.840
and matching up the sensor maker

12:57.840 --> 13:02.320
with a Data Union is a little tricky, 
requires humans to talk, 

13:02.320 --> 13:04.640
pick up the phone, but we're getting there.

13:05.600 --> 13:06.720
That's fascinating.

13:06.720 --> 13:11.840
So it's almost like a new revenue 
source for all of these IoT 

13:11.840 --> 13:18.160
and kind of machine Data Economy 
tools that generate data,

13:18.160 --> 13:21.440
but maybe they need government subsidies right now, 

13:21.440 --> 13:24.240
and this is a new way for monetizing.

13:25.760 --> 13:26.560
Yeah, that's right.

13:26.560 --> 13:30.960
And you know, and there's other 
ways that you can think of.

13:32.800 --> 13:37.120
There's a welter of ideas out there, 
that we've kind of also had.

13:38.720 --> 13:41.520
Because you can imagine, your phone, 

13:41.520 --> 13:44.640
smartphones are amazing 
devices at collecting information.

13:44.640 --> 13:47.520
They have a whole load of 
internal sensors for a start, 

13:47.520 --> 13:51.520
including obviously a camera 
amongst anything and noise devices.

13:52.080 --> 13:56.960
And, as soon as you kind of allow 
those individuals to then, 

13:56.960 --> 14:00.480
you know, all you have to do is create 
an app that collects a specific dataset.

14:00.480 --> 14:02.080
And then you can imagine, okay, 

14:02.080 --> 14:04.400
now there's a monetary 
incentive for people to do this.

14:05.200 --> 14:10.400
Then, that's how that takes off. 
And then you can imagine half a dozen ideas.

14:10.400 --> 14:12.960
I'm sure if we sat here for another 
five minutes, we could come up with them.

14:12.960 --> 14:13.520
Yeah.

14:13.520 --> 14:14.720
It's all ultra playful.

14:14.720 --> 14:19.440
And I think it's important 
to keep them like opt-in.

14:19.440 --> 14:23.120
It means like, I would imagine 
probably in countries like China 

14:23.120 --> 14:27.600
or like Thailand, where 
data privacy regulations are not or,

14:27.600 --> 14:32.640
I don't think they're non-existent, but they're
not as established as in Europe with GDPR.

14:32.640 --> 14:37.920
You, like handset makers, manufacturers,
they might be selling phones in future that when

14:37.920 --> 14:40.800
you just start booting up your phone, 

14:40.800 --> 14:44.000
you just agree to some 
terms and conditions and one

14:44.000 --> 14:46.960
of the lines says we're going 
to sell all of your sensor data 

14:46.960 --> 14:49.360
for free and you don't get anything from.

14:49.360 --> 14:53.440
I mean, this is what's happening now 
and it's causing all sorts of problems.

14:54.160 --> 14:56.960
The first one is obviously, 
a lot of people are getting rich, 

14:57.840 --> 15:01.760
sorry a tiny group of people are getting 
very rich off the back of everyone else.

15:01.760 --> 15:02.560
So that's the one part.

15:02.560 --> 15:06.080
The second problem is, and they also have
a giant monopoly on the world's information.

15:06.720 --> 15:08.880
That's not great, because it's going to get worse.

15:10.080 --> 15:12.240
That also stymies innovation.

15:12.240 --> 15:16.400
So, why do we only have, like, 
in most countries in the west certainly, 

15:16.400 --> 15:19.760
there's only one map application or two, Waze

15:19.760 --> 15:23.120
and Google Maps, but 
actually they're owned by the same company.

15:23.120 --> 15:26.960
So that's what 21st century 
innovation has given us, one map app.

15:26.960 --> 15:28.240
You're like, that's rubbish.

15:28.240 --> 15:30.160
And like an Apple but no one uses Apple's, 

15:30.960 --> 15:35.440
so, and the reason for that is because 
they have a monopoly on our location.

15:35.440 --> 15:36.560
We create that data.

15:38.560 --> 15:42.480
You know, I would like 
other options but viable ones.

15:42.480 --> 15:45.200
So if you take the 
raw datasets away from them, 

15:45.200 --> 15:47.840
anyone can build applications 
on top of the raw datasets

15:47.840 --> 15:49.440
and that's the world we want to live in.

15:50.000 --> 15:54.160
So, there are all those problems and 
then the most interesting problem is this.

15:54.160 --> 15:56.400
From the data bias perspective.

15:56.400 --> 15:58.160
This is terrible data.

15:58.160 --> 16:00.960
No one actually really wants this data, 
but it's the only data they can get.

16:01.840 --> 16:07.280
Why do you want to collect data under the table,
in a way that you're sort of spying on your users,

16:07.280 --> 16:10.240
that you buried the consent on page 70 of a contract 

16:10.240 --> 16:12.720
that you know no one's read, no one's read,

16:12.720 --> 16:14.320
not even your lawyers have probably read it.

16:15.200 --> 16:16.960
And that no one's going to 
object to, because they don't 

16:16.960 --> 16:20.320
have time to like, 
commission a lawyer and sit there

16:20.320 --> 16:21.760
for four hours to read the term.

16:21.760 --> 16:22.560
No one does that, right?

16:23.600 --> 16:26.960
So you get, data is just 
a by-product now of our digital lives, 

16:26.960 --> 16:29.520
when actually you really wanted to be the product

16:29.520 --> 16:30.640
and that's what Data Unions do.

16:30.640 --> 16:32.800
You're like okay, look, 
if you want to create good data products, 

16:34.080 --> 16:37.360
get people to create the data, 
who actually want to be part of this

16:37.360 --> 16:39.440
and like, and are happy to do it.

16:39.440 --> 16:40.960
Like, doesn't that make sense?

16:40.960 --> 16:42.480
And you think that sounds nice and fluffy.

16:42.480 --> 16:46.240
Should be like no, 
it creates better data products by far, 

16:46.240 --> 16:49.840
like much richer, much more 
interesting, much more stable,

16:49.840 --> 16:52.560
much more sustainable data products.

16:52.560 --> 16:53.760
And they're worth so much more.

16:53.760 --> 16:56.800
That you can trust 
and when you pay for data, 

16:56.800 --> 16:59.520
you can trust that your access 
is not going to be cut off,

16:59.520 --> 17:02.640
whereas, if you are building 
on top of Facebook or Google, 

17:02.640 --> 17:06.320
like we know countless examples 
of startups getting their

17:06.320 --> 17:10.000
API access shut down, 
just because Google felt, 

17:10.000 --> 17:14.320
"well they're extracting 
more value from our ecosystem

17:14.320 --> 17:16.640
and closed garden than we would like to".

17:16.640 --> 17:19.120
Yeah, there's that problem 
and then there's the other problem 

17:19.120 --> 17:25.200
which is that, so these 
data brokers go bust all the time.

17:26.000 --> 17:28.880
You know, you kind of hear about it. 
Cambridge Analytica is the most famous, right?

17:28.880 --> 17:29.440
Yeah.

17:29.440 --> 17:30.080
Big data broker.

17:30.080 --> 17:31.040
They went bust, right?

17:31.040 --> 17:32.800
Pretty much overnight, like, effectively.

17:33.840 --> 17:36.800
There was another one, 
Jumphot, which went bust last year.

17:37.920 --> 17:40.880
Huge company. 
Well for the data science world, like, 

17:40.880 --> 17:44.480
growing 30 million revenues, 
growing probably to 70 million kind of,

17:44.480 --> 17:46.800
within the next year, 
that was a projection.

17:47.920 --> 17:51.040
They had 400 people employed 
and literally within a week, 

17:51.040 --> 17:53.920
when they got uncovered by, 
I think it was Motherboard,

17:54.720 --> 17:56.160
which was owned by Vice magazine, 

17:56.960 --> 17:59.200
within one week their 
parent company shut them down.

17:59.200 --> 18:00.613
That's insane.

18:00.613 --> 18:03.360
They’re like, yeah, we can't handle this 
and it's all about the ethics, nothing else.

18:03.360 --> 18:05.360
Business was great, 
like everything, all about the ethics.

18:05.360 --> 18:09.600
You're like, we're spying, we can't spy on people,
you’re like, well you were doing that before.

18:10.240 --> 18:15.360
This is almost as severe 
as like when there's like a news 

18:15.360 --> 18:19.360
about a company in, I don't know, 
Southeast Asia, using slave labor.

18:19.360 --> 18:19.860
Yeah.

18:20.960 --> 18:23.680
I think I coined this data slavery.

18:24.320 --> 18:28.560
I did a whoa, you were even involved, 
I'm not sure but like, 

18:28.560 --> 18:33.040
there was some kind of podcast, 
they invited me and then like,

18:33.040 --> 18:37.760
my talking point was all about 
data slavery and it is really like that.

18:37.760 --> 18:40.240
It's slavery of your digital twin.

18:40.240 --> 18:44.160
I think, I mean look, people 
object to slavery, being used 

18:44.160 --> 18:49.200
and bandied around like that 
because of the kind of actual,

18:49.200 --> 18:52.080
yeah, right, the implications, 
historical implications of that 

18:52.080 --> 18:54.880
and trivializing that historical experience.

18:55.600 --> 18:58.560
So I kind of end up using 
serfdom, because somehow we're less 

18:58.560 --> 19:02.800
sensitive to the word serfdom. 
I'm sure people, historians of…

19:03.360 --> 19:04.377
It’s really exploitation.

19:05.360 --> 19:06.560
But it is true, it is.

19:07.280 --> 19:11.600
Yeah and, you know, and it's really overt

19:11.600 --> 19:14.800
and one interesting thing 
that's just happened, is in California.

19:14.800 --> 19:19.680
So, Enoch Liang from DDP, 
which is the data dividend project, 

19:19.680 --> 19:24.560
supported and founded by Andrew Yang, 
who people, I'm sure will know.

19:25.760 --> 19:29.040
They have been fighting 
the legal good fight, if you want.

19:29.040 --> 19:32.160
It's got to be fought by 
tech and in the courtroom.

19:33.840 --> 19:35.200
And what they managed to get was a ruling 

19:35.200 --> 19:37.840
from a California judge, 
in the last, I think month.

19:38.880 --> 19:43.200
The case is called Calhoun, if you're 
interested in this, in looking it up.

19:43.200 --> 19:46.320
Where the judge said, yeah, 
there is a natural property right to data,

19:46.320 --> 19:48.560
this stuff is worth something and yeah, 

19:48.560 --> 19:52.640
and it's owned by the people 
who create it like, that just should follow.

19:52.640 --> 19:56.640
So, you know, more will emanate 
from that case and you know,

19:56.640 --> 20:01.200
Americans, if America sets a standard 
for property rights in data, 

20:01.200 --> 20:04.640
then I think that battle is won. 
And Europe, legislatively speaking,

20:04.640 --> 20:12.080
has struggled to, because of the way 
that the law is set up in continental systems, 

20:12.080 --> 20:16.000
struggle to confer a property 
right of data onto people,  

20:16.720 --> 20:18.320
but it's doing it a slightly different way,

20:18.320 --> 20:23.760
which is to basically legalize 
and give stamps of approval 

20:23.760 --> 20:26.480
to data cooperatives and 
a bunch of funding, two billion.

20:27.120 --> 20:28.880
So that's all happening in Europe now.

20:29.760 --> 20:31.920
This is a huge scene that’s about to take off...

20:31.920 --> 20:32.420
Wow!

20:32.880 --> 20:33.760
...in Web3.

20:33.760 --> 20:37.280
So there's EU funding for data cooperatives.

20:37.280 --> 20:37.780
Yeah.

20:38.320 --> 20:39.840
Whoa! Then what’s….

20:39.840 --> 20:41.840
There will be, yeah, 
I mean they've said two billion, 

20:41.840 --> 20:45.760
so the pot of money gets unlocked soon apparently.

20:47.520 --> 20:51.040
What should people Google 
to find about, find more about this?

20:51.840 --> 20:53.280
About the EU funding?

20:53.280 --> 20:54.000
Yeah, exactly!

20:55.360 --> 20:57.760
Well it was announced, 
I think about, when was it?

20:58.960 --> 21:01.120
I'm getting confused whether 
it was, it wasn't November, 

21:01.120 --> 21:03.760
it was, yes in January, 
I think, on January and February,

21:04.400 --> 21:08.160
the EU data strategy and 
if you google, I think Vestiger,

21:08.160 --> 21:13.920
who's the EU commissioner on this, 
you'll find the press release somewhere.

21:14.960 --> 21:16.560
They're not going to shout about it until it's 

21:16.560 --> 21:18.320
a little bit buried, 
but it is in the press release.

21:19.280 --> 21:19.520
Okay.

21:19.520 --> 21:21.520
They're not going to shout about 
it until it's actually up and running.

21:22.240 --> 21:22.560
Okay.

21:22.560 --> 21:26.160
But it will be match funding, yeah.

21:27.040 --> 21:29.840
You're already putting in your 
application now, I can see you writing.

21:31.840 --> 21:36.320
It'll be match funding for people 
who have data cooperative ideas, 

21:37.040 --> 21:41.200
which is great, because then, whatever Streamr

21:41.200 --> 21:44.320
or other organizations put 
into this they'll get twice out 

21:45.200 --> 21:47.680
and these ideas, some of them will fail, sure.

21:47.680 --> 21:52.480
But I think there's enough good ideas that a lot
of them will start succeeding pretty quickly.

21:52.480 --> 21:55.600
Yeah, and I think you also mentioned as one of this, 

21:56.240 --> 21:59.360
the legislations and the grants as one of the biggest

21:59.360 --> 22:03.760
wins for Data Unions, or to support Data Unions 

22:03.760 --> 22:07.120
and one of them is the example you already mentioned.

22:07.120 --> 22:09.520
So there are two parts to this question sort of, 

22:10.240 --> 22:14.560
like, what are the other wins 
that you can think of apart from this?

22:14.560 --> 22:19.840
And geographically, which parts 
of the world do you feel are 

22:20.560 --> 22:27.200
more receptive to a model like a Data Union, 
or is it like, borderless sort of?

22:29.440 --> 22:30.560
Nice question Diksha.

22:30.560 --> 22:31.600
Always the best questions.

22:33.280 --> 22:41.360
I would say that in theory every 
government should be pro this.

22:42.320 --> 22:44.560
Because it does lend those two things.

22:44.560 --> 22:48.160
One, it's clearly giving 
monetary value to ordinary people 

22:48.160 --> 22:53.680
and returning it back to ordinary 
people, as opposed to companies

22:53.680 --> 22:56.320
that are usually outside of their own country.

22:56.320 --> 22:57.200
Unless you're America.

22:57.920 --> 22:59.440
So that's always like a win.

22:59.440 --> 23:01.040
If you're in any way a democratic or 

23:01.040 --> 23:03.840
populist government, great, 
you're like, that sounds nice.

23:03.840 --> 23:07.840
And also fair and just, as far as 
some kind of natural justice train.

23:08.400 --> 23:09.840
But it also opens up the innovation, right?

23:09.840 --> 23:11.040
So it's actually good for business.

23:11.040 --> 23:13.760
And the people who monopolize 
the data, they also know this too, 

23:14.400 --> 23:19.760
but they can't help themselves from retaining 
their monopoly, because of their shareholders.

23:21.440 --> 23:27.040
So, I think there was a report in Britain that 
said, if we did have full data portability, 

23:28.160 --> 23:33.040
which is that people had the right to at least 
port their data to anywhere and you had to,

23:33.040 --> 23:39.600
did a cooperative model effectively built in. 
It would add 27 billion in pounds.

23:39.600 --> 23:40.560
So what is that?

23:40.560 --> 23:45.600
Off the top of my head is about 
36 billion dollars in GDP, each year.

23:46.400 --> 23:53.920
And that's a lot, it's about 10, oh it's 
about did five, yeah, five percent of what, 

23:53.920 --> 23:58.640
yeah, scrap that statement, I better not do 
the math in my head, get it all horribly wrong.

23:59.520 --> 24:02.640
But, you know, there's a substantial 
amount of money to any country, 

24:02.640 --> 24:08.640
so, I think where it might not work and I mean,

24:08.640 --> 24:14.240
you can also see it starting 
to take off in, is absolutely in Europe 

24:14.240 --> 24:18.560
and where Europe has led, I think other 
countries will have followed, especially on GDPR.

24:20.160 --> 24:23.920
We are getting good noises from the US.

24:24.480 --> 24:28.000
I think the UK will actually try 
and because of the politics of it all, 

24:28.000 --> 24:30.960
outgun the EU on this front, that's my wish.

24:32.000 --> 24:34.640
And we've been talking to policymakers here.

24:36.000 --> 24:39.680
In the UK we've been subsumed 
obviously by Brexit and Coronavirus, 

24:39.680 --> 24:42.320
but I think they're getting 
their ducks in there in a row.

24:42.320 --> 24:46.080
So that would be really interesting, if the 
UK decides to go even further than the EU.

24:47.680 --> 24:51.520
And India I think has a natural 
resonance to this kind of  

24:52.080 --> 24:56.160
this model, of kind of 
grassroots cooperativism.

24:56.160 --> 25:02.720
It’s built into the country's 
economic history in the last 100 years  

25:03.760 --> 25:06.240
and it's also a democratic country.

25:06.240 --> 25:09.600
I don't know where China will 
go with them, but who knows.

25:11.120 --> 25:15.760
So coming back to Data Union, 
I mean, I have a practical question.

25:15.760 --> 25:18.480
Maybe you can tell me whether it makes sense.

25:19.200 --> 25:25.120
So can I really choose who 
to sell my data to and if I sell it, 

25:26.160 --> 25:31.120
how can I be assured that it's the end user,

25:31.120 --> 25:36.240
or really how do I know that it 
doesn't, can it basically be acquired?

25:36.240 --> 25:38.560
Can a Data Union sort of be acquired?

25:40.480 --> 25:42.240
Again, beautiful questions both.

25:42.240 --> 25:46.560
So the first question is 
about member preferences.

25:46.560 --> 25:50.560
At the moment we don't have 
a way, in a technological way,  

25:50.560 --> 25:52.480
of signaling the preferences built.

25:53.120 --> 25:56.240
But it's actually not that 
difficult to build that in.

25:57.280 --> 26:01.680
So people basically say at the start, 
look these are the kinds of organizations  

26:01.680 --> 26:02.880
I'm interested in selling to.

26:03.520 --> 26:05.760
If you're sort of the kind 
of person who wants to make every 

26:05.760 --> 26:08.960
single decision about how their 
data is sold, don't sell your data.

26:08.960 --> 26:10.800
Because you want someone, most people are like, 

26:10.800 --> 26:14.800
I just want you as a body 
to do this for me. Good news.

26:15.360 --> 26:18.160
The EU scheme is based on this fiduciary model.

26:18.160 --> 26:22.720
So it says, if you are a data cooperative, you 
have to have a legal duty of care to your members.

26:23.520 --> 26:25.680
And that's where the safeguards come in.

26:25.680 --> 26:29.200
Once you have that, then they 
have to work for their members, 

26:29.200 --> 26:31.360
in this way and they can't just disregard them.

26:32.240 --> 26:36.800
That also brings me to this, the second 
point, but we'll build in these preferences, 

26:36.800 --> 26:40.880
so you'll be able to at some point, 
we're not quite there yet with the stack,

26:40.880 --> 26:43.680
but at some point you'll be able to say, 
I only want to sell to charities.

26:43.680 --> 26:46.480
I only want to sell to charities 
and university researchers.

26:47.200 --> 26:48.800
I'm happy to sell to everyone, right?

26:49.680 --> 26:52.480
And you'll just be in a different bucket of data 

26:52.480 --> 26:56.720
and only those buckets will be able 
to be bought by certain types of buyers.

26:56.720 --> 26:58.640
It's actually pretty easy, but we'll get there.

26:59.520 --> 27:00.400
The second question  

27:01.680 --> 27:06.560
was, I think follows on from that fiduciary 
stuff, which is can you be bought out?

27:06.560 --> 27:09.200
Like what's the point of building 
all of this stuff if one day Google says,  

27:09.200 --> 27:10.320
I will just buy you all out.

27:11.120 --> 27:12.000
That is a problem.

27:12.560 --> 27:14.960
Obviously that haunts a lot of 
people, but certainly it haunted me 

27:16.240 --> 27:20.800
and I would love to see, 
you can't force data operators,

27:20.800 --> 27:24.720
these people who come along as 
entrepreneurs to be cooperatives, 

27:24.720 --> 27:27.600
but I would like a federation of cooperatives.

27:27.600 --> 27:29.040
That would be really cool.

27:29.840 --> 27:34.240
But if that doesn't work, then the 
fiduciary aspect, that thing of that 

27:34.240 --> 27:37.440
legal duty of care will 
probably make it really easy for,

27:37.440 --> 27:40.640
or really difficult for Google to purchase, right?

27:40.640 --> 27:44.320
Because they'll have to be under the law, 
it'd have to be a separate legal entity.

27:45.040 --> 27:48.320
They can't really talk and they 
have to work for the members, right?

27:48.320 --> 27:50.400
And does Google really want to do that?

27:50.400 --> 27:53.600
Yeah, we've got access, or 
they could just buy it to shut it down 

27:53.600 --> 27:56.400
and people kind of know that and that's possible.

27:57.680 --> 28:02.000
The token model also helps, because 
the whole point of tokens really is that you can 

28:03.120 --> 28:09.920
disassociate equity and ownership of an 
underlying capital asset from utility and value.

28:10.800 --> 28:13.120
And if you can do that, you can turn revenues to people 

28:13.120 --> 28:15.360
and then not have to sell out your equity to anyone.

28:15.360 --> 28:17.760
And that also helps with the cooperative stuff.

28:17.760 --> 28:20.480
But it is difficult. 
All of this stuff is stuff that we need to think about 

28:20.480 --> 28:23.040
and I know why that keeps me, 
that's what keeps me up at night.

28:24.960 --> 28:26.960
So it's a work in progress still.

28:26.960 --> 28:27.680
Yeah.

28:27.680 --> 28:29.200
It's a little bit of work in progress.

28:29.200 --> 28:32.960
I think we'll get there and I mean 
there are other technological sides. 

28:32.960 --> 28:38.080
I was just having a chat with one 
of the original founders, Oren Macmillan.

28:38.080 --> 28:41.840
I hope he doesn't mind me revealing 
this, yeah he won't, of the DAO, 

28:42.640 --> 28:46.800
like The DAO, like the 2015 thing that went horribly wrong.

28:47.520 --> 28:52.720
Was it 2016? He was saying, look, you know,
also there's these interesting technological  

28:53.600 --> 28:54.800
things you can build in, right?

28:54.800 --> 29:01.920
So safeguards, where you have the 
Data Union directing as a whole through 

29:01.920 --> 29:07.280
preferences to one ENS address which is 
then the organization that sells the data.

29:07.280 --> 29:10.160
And then you could end up with 
a situation where the Data Union 

29:10.160 --> 29:14.800
just decides to vote en masse 
to flick to another direct,

29:14.800 --> 29:17.040
you know, another organization 
that actually sells the data.

29:17.680 --> 29:20.640
So, you don't end up with this 
networking issue, where people go, 

29:21.200 --> 29:23.440
we've been bought up by Google, 
I guess I'll leave

29:23.440 --> 29:26.880
and everyone tries to leave as 
individuals and it doesn't really work, 

29:26.880 --> 29:29.520
but you just have one vote, 
everyone decides to leave

29:29.520 --> 29:31.760
and the whole thing is 
directed to something else.

29:31.760 --> 29:34.880
So nothing has to change, no one has 
to do anything, except for pressing one button.

29:34.880 --> 29:36.240
That's nice. I like that.

29:36.800 --> 29:45.040
Yeah, I do believe data DAOs are going to be, 
I don't know if, huge, but they're essential.

29:45.040 --> 29:50.320
It seems like it's one of the, like blockchainy 
pieces that definitely makes sense to me.

29:50.960 --> 29:55.840
And on that topic, I was wondering 
if you've ever asked yourself, 

29:56.400 --> 30:00.000
now being involved in the blockchain 
space, like, why blockchain

30:00.000 --> 30:02.000
and data, like, why does it even make sense?

30:03.920 --> 30:05.760
It doesn't and so we don't do it.

30:06.400 --> 30:07.520
Okay. Great.

30:08.240 --> 30:11.040
Where it makes sense is just for the payments.

30:11.040 --> 30:17.520
Don't put data on the blockchain, it's just like 
the worst way to structure data architecture.

30:19.200 --> 30:21.600
Like, why do you want to put 
it on thousands of databases, 

30:21.600 --> 30:24.000
when even one is already difficult enough?

30:24.640 --> 30:26.000
It's basically the short version.

30:26.880 --> 30:27.600
Yeah, of course.

30:27.600 --> 30:31.840
Like putting data itself on at least 
like current generation blockchains 

30:31.840 --> 30:34.960
doesn't make sense. 
There's like, IPFS, Filecoin, Arweave,

30:34.960 --> 30:38.160
that they're viable solutions 
for decentralized storage, 

30:38.160 --> 30:42.560
but there's payments, there's 
governance, there's the marketplace side.

30:42.560 --> 30:49.520
So you use blockchain for what it's good at, 
which is all the things you've just listed.

30:49.520 --> 30:53.840
So, the payment, so, I mean, 
I have been asked this question before,  

30:56.240 --> 30:57.920
why don't you do this with Fiat, right?

30:59.200 --> 31:00.560
And the answer is really simple.

31:00.560 --> 31:03.520
Your bank, your business, if you've 
ever done business banking before, 

31:03.520 --> 31:05.920
they charge you for transactions, 20 cents.

31:05.920 --> 31:06.880
That's how they make the money.

31:08.000 --> 31:10.800
And imagine now trying to pay 
a million people 25 cents.

31:12.080 --> 31:14.800
And then getting charged 20 cents for each 
transaction, so that isn't going to work.

31:14.800 --> 31:17.600
You can't do micro payments to 
the Fiat system and you can barely 

31:17.600 --> 31:19.920
do it with Ethereum, in fact 
you can't do it with Ethereum now.

31:20.880 --> 31:23.120
So, even then, you still struggle.

31:23.760 --> 31:26.720
So, you know, Streamr is now using Matic.

31:27.920 --> 31:32.960
Oh sorry, xDAI at the back end 
and Matic was in consideration, 

31:32.960 --> 31:35.600
but, you know, bridging and stuff 
like that, some technicalities there.

31:35.600 --> 31:41.040
But, yeah, so, we're using xDAI 
as a side chain for all of this.

31:41.040 --> 31:47.120
And for payment, can people use stable coins, 
or like, coins that are pegged to USD?

31:48.960 --> 31:52.720
Yeah, they can and in effect you can 
architect this in any way that you want, 

31:52.720 --> 31:56.480
which is that you could pay 
all of these people in stablecoin

31:57.040 --> 32:02.800
and that might make sense for 
a lot of people, but early adopters seem 

32:02.800 --> 32:06.960
to like the fact that it's crypto, they're 
getting a token that can go up and down in value.

32:06.960 --> 32:07.840
Interesting.

32:07.840 --> 32:12.400
It makes the ride a bit more exciting for them 
and in a bull run obviously, that's great.

32:13.120 --> 32:14.240
Less so in crypto winter.

32:14.240 --> 32:15.280
It's kind of like, if…

32:15.280 --> 32:15.840
Warning!

32:15.840 --> 32:21.200
If you were an advertiser back in like 2005 
and you got paid in Google stock,  

32:21.200 --> 32:22.560
that would be quite interesting.

32:23.760 --> 32:27.760
It would be. And I know people 
who have been paid in Apple stock.

32:27.760 --> 32:28.400
Really?

32:28.400 --> 32:29.520
From the 80s, yeah.

32:29.520 --> 32:30.240
No shit.

32:30.240 --> 32:36.000
And apparently still have it, I don't understand 
because I still picked up the tab for dinner.

32:39.040 --> 32:39.520
God.

32:39.520 --> 32:42.320
That's how, that's, I think 
how rich people stay rich, right?

32:42.320 --> 32:43.760
Yeah, exactly.

32:43.760 --> 32:49.760
And, another, I mean, we briefly 
talked about this, but another use case 

32:49.760 --> 32:54.560
for blockchain and data would be 
decentralized governance of Data Unions

32:54.560 --> 33:01.280
and data itself and It does 
seem to make sense on the surface, 

33:01.280 --> 33:05.760
but like, if you have 
actually observed how DAOs work,

33:05.760 --> 33:09.200
or don't work in the Ethereum space, 
most people don't give a fuck, 

33:09.200 --> 33:13.280
like, they don't really care to 
vote on a thousand random things

33:13.280 --> 33:17.440
and that's even like for money, like, 
where they have real skin in the game, 

33:17.440 --> 33:20.640
like tens of thousands of dollars, 
they don't vote, they don't have time.

33:20.640 --> 33:28.160
So it would be crazy to expect millions of people 
to vote on millions of decisions for their data.

33:28.160 --> 33:33.360
So then, the Data Union 
starts to really make sense.

33:34.640 --> 33:43.840
Yeah, right, I think you'll never 
have pure DAOs and that's difficult to say 

33:43.840 --> 33:46.560
because you're like, I don't want 
to say it, but I think that's true.

33:47.280 --> 33:50.880
I think you always need and it's not, 
it's a really fascinating, 

33:50.880 --> 33:54.080
like again, if you look at the kind 
of economic history of capitalism,

33:54.080 --> 33:56.800
it's a really fascinating moment. 
It wasn't obvious that you could 

33:56.800 --> 34:01.040
actually give control of 
your assets to someone else.

34:02.080 --> 34:05.200
And then also, they wouldn't be 
fully liable for that and nor would you.

34:05.760 --> 34:11.200
So you have limited liability 
but an executor of someone who can 

34:11.200 --> 34:14.960
carry out their control and 
you can give permission to.

34:14.960 --> 34:20.960
So this is like a fascinating construct, 
it's not actually that it's pretty new, 

34:20.960 --> 34:24.160
innovation, four or five 
hundred years old kind of thing,

34:24.160 --> 34:28.320
or even less by other measurements.

34:28.880 --> 34:32.480
So I like the DAO and actually 
that's what's being kicked 

34:32.480 --> 34:36.720
around at the moment, if you want to know the 
kind of inside baseball stuff on the legislation.

34:36.720 --> 34:40.480
It's like who, can you have 
delegated authority and how far does 

34:40.480 --> 34:43.040
that go for Data Union members 
and how much does that need

34:43.040 --> 34:44.320
to be written into the legislation.

34:44.320 --> 34:47.680
Yeah, because as soon as 
you delegate, because it's 

34:47.680 --> 34:52.720
on-chain, you could easily 
trade that to delegation.

34:52.720 --> 34:53.220
Yeah.

34:53.600 --> 34:58.400
It can be tokenized, you could literally 
have NFTs that if you hold the NFT, 

34:58.960 --> 35:03.840
you have a, governance rights over 
a certain Data Union or just dataset.

35:04.960 --> 35:07.920
You know, actually, I didn't 
even think about that properly.

35:09.440 --> 35:12.320
What if you start tokenizing 
the delegated rights?

35:13.520 --> 35:15.600
The delegated rights that they're 
talking about are obviously 

35:15.600 --> 35:20.080
off chain, so the kind of 
Web2 legal structures.

35:20.080 --> 35:23.280
Could also be on-chain, like, if you 
use Arweave and things like that.

35:23.280 --> 35:29.840
Yeah you're right. 
That becomes a nightmare, it's great.

35:31.120 --> 35:36.480
And what's interesting is you could 
have limited editions of those access tokens 

35:36.480 --> 35:42.880
and you could even have a bonding curve for 
like, the first token gets 10 days first,

35:42.880 --> 35:46.160
like access to data and then 
the second token gets it after 

35:46.160 --> 35:49.520
10 days and the third one gets it 
after months and then the value goes down.

35:50.400 --> 35:55.280
Yeah and, I mean, sort of know 
the Colony guys and one of their 

35:55.280 --> 35:58.720
great innovations in ideas, they haven't 
quite put it into practice yet,

35:58.720 --> 36:02.560
it was a kind of, rights that decay over time.

36:02.560 --> 36:03.060
Yeah.

36:03.360 --> 36:04.720
And I was like, yes, that's it.

36:04.720 --> 36:05.840
That's the secret sauce.

36:06.800 --> 36:10.960
But I think they're coming out soon 
with their second more viable version 

36:10.960 --> 36:14.000
and I hope that the decaying rights 
isn't there, because that's an idea

36:14.000 --> 36:15.360
that everyone needs to copy.

36:17.520 --> 36:23.120
But you're right, you know, it's so, I think the 
inherent part is the thing that you said earlier.

36:23.760 --> 36:25.520
People want convenience, right?

36:25.520 --> 36:28.240
Yes, they want value and they 
want to get paid, but they also want 

36:28.240 --> 36:31.760
convenience and they don't want us to take up 
their, I don't want it to take up people's lives.

36:33.680 --> 36:36.800
Because otherwise that's just, failed. 
If I have to keep coming back to you 

36:36.800 --> 36:42.400
every six minutes with a question that you 
have to answer, that's never going to work.

36:42.400 --> 36:44.640
So, you know, at most once a month.

36:45.440 --> 36:48.960
The only thing you want to 
see is the number go up.

36:48.960 --> 36:52.560
You want to see on your app that, 
oh, today I have two cents 

36:52.560 --> 36:54.880
or like, two dollars more without doing any work.

36:55.680 --> 36:56.800
Yeah, right.

36:57.760 --> 37:00.240
And there's some innovations there, 
which, you know, you get two dollars 

37:00.240 --> 37:04.000
from one Data Union, but, you know, 
join five and suddenly it's ten dollars.

37:05.360 --> 37:10.080
And things get kind of more interesting within 
building up those assets of passive income.

37:11.200 --> 37:14.240
Maybe that starts to unlock other 
micro economies, because you're 

37:14.240 --> 37:17.600
now giving lots of ordinary people, 
who don't have to do anything,

37:17.600 --> 37:21.280
who don't have to go and buy crypto to start 
with, you’re just giving it to them, 

37:21.280 --> 37:23.360
because they're already doing work that is valuable.

37:24.960 --> 37:29.120
And they've got, now you've opened up 
the crypto economy to potentially hundreds 

37:29.120 --> 37:34.800
and hundreds of millions of other people, 
who can maybe trade, but more interestingly,

37:34.800 --> 37:39.760
again, like, you know, what's the thing that 
you can solve with micropayments, right?

37:39.760 --> 37:45.920
And this comes back to me being a journalist 
again, I'm like, paying for articles finally.

37:45.920 --> 37:49.600
I don't want to subscribe to 15 
different newspapers, but I do want to read 

37:49.600 --> 37:51.569
articles from 15 different outlets....

37:51.569 --> 37:52.470
Great!

37:52.470 --> 37:56.720
regularly. But I only want to 
pay like, eight cents each.

37:57.120 --> 38:00.720
I've got some crypto on my computer, 
it's just there in my MetaMask wallet, 

38:01.280 --> 38:05.440
from the several Data Unions I've joined. Now you 
can see this wonderful circular economy, right?

38:05.440 --> 38:08.480
Yeah. Suddenly everything makes sense.

38:09.440 --> 38:11.155
Great, sold.

38:13.600 --> 38:14.080
Okay.

38:14.080 --> 38:17.200
But why is media actually not adopting that model?

38:17.200 --> 38:18.800
What's really stopping them?

38:19.440 --> 38:20.640
Like, the micropayments?

38:20.640 --> 38:24.320
It's like you've been there 
and I'm sure this is the idea you've 

38:24.320 --> 38:28.240
proposed within the community 
also, so, what do you hear?

38:30.240 --> 38:35.520
So, micropayments, I remember in 2010 were 
like going to be the great savior of media.

38:35.520 --> 38:38.880
There have been a few ideas, 
you sit in a newsroom, 

38:38.880 --> 38:42.720
you know, your job depends on, 
like the business model working, right?

38:43.440 --> 38:45.120
And especially if you're 
an investigative journalist, 

38:45.120 --> 38:48.400
because it’s the most expensive 
operation in the newsroom, usually.

38:49.680 --> 38:52.720
So, you know, it was video at one 
point, video is the great savior, 

38:52.720 --> 38:57.360
that turned out not to be true, but yeah, 
and there'd be other emanations but,

38:58.000 --> 39:00.400
and now it's just like, 
Facebook will pay us or Google.

39:01.040 --> 39:03.840
You know, that's a terrible, 
this is not a business model at all.

39:04.480 --> 39:07.680
And then subscribers have 
in fact worked to an extent.

39:09.600 --> 39:12.960
But micropayments are the most beautiful 
solution and the reason why it's, 

39:12.960 --> 39:17.200
just technologically, one really difficult 
to implement, so you have to use crypto

39:17.200 --> 39:20.480
and crypto has only just got, 
literally within the last, I think, 

39:20.480 --> 39:24.000
6 months to the point of maturity, where it 
could handle that kind of thing with side chains.

39:24.640 --> 39:25.440
That's the first thing.

39:26.080 --> 39:29.200
And you'd have to like, encrypt 
the content and decrypt it, right?

39:29.200 --> 39:32.720
So that's the kind of thing you'd have to do, 
which is sort of what they do anyway.

39:32.720 --> 39:34.960
They kind of just block it out 
and like, if you want to read more,  

39:35.680 --> 39:36.880
you have to do these other things.

39:39.360 --> 39:43.520
So, I think we're there and the second 
bit is also just, you need a third party 

39:43.520 --> 39:48.000
to be able to come and get, galvanize, 
groups of people who really don't like

39:48.000 --> 39:50.800
cooperating all that much with each other, 
because they're natural competitors.

39:52.800 --> 39:58.640
And I think, and the third bit is that, 
how do you then get all these, 

39:58.640 --> 40:02.400
the same crypto token to all these 
different other people, without a,

40:02.400 --> 40:06.080
you know, that's really hard and, 
so this is a way of doing that.

40:06.080 --> 40:08.960
You're like, these people already do work, 
so we can pay them the value 

40:08.960 --> 40:13.760
for that thing and then they can use that, 
if they want, to unlock value somewhere else.

40:13.760 --> 40:15.440
That's just how economies work.

40:17.280 --> 40:19.440
And maybe that goes to your 
other question that you asked 

40:20.080 --> 40:23.280
at the beginning as well, like, what are the 
other ideas that this starts to unlock?

40:23.280 --> 40:30.480
Well, there's these huge parts of 
our lives that, for good or for worse, 

40:30.480 --> 40:32.800
but usually for worse, because 
they disempower people,

40:32.800 --> 40:36.160
aren't counted as economic activities.

40:37.040 --> 40:39.840
Because no one actually has a way of 
either paying people, or counting it.

40:40.720 --> 40:45.360
So the typical example is usually 
all of domestic work, it's not counted, 

40:45.360 --> 40:49.680
in economic terms, because no one's 
paying, vastly, generally speaking,

40:49.680 --> 40:52.000
women, to do any of this stuff.

40:52.000 --> 40:54.480
And so it's also disregarded 
and counted as second class.

40:56.400 --> 41:01.120
Well this is another aspect of 
that, with the Data Economy.

41:02.240 --> 41:06.080
And suddenly, once you start to unlock 
that stuff, then you start to see 

41:07.200 --> 41:11.040
vast improvements and vast empowerment 
of all sorts of sectors of society

41:11.040 --> 41:12.400
that were just ignored before.

41:12.400 --> 41:13.360
Yeah, agreed.

41:13.360 --> 41:18.880
I do really feel like data could 
be the gateway drug for crypto, 

41:18.880 --> 41:25.200
or empowering the next billions 
of people to start monetizing everything,

41:25.200 --> 41:28.960
like with the recent NFT 
wave in the crypto space, 

41:28.960 --> 41:36.000
we saw now there's a whole kind 
of silent economy of digital artists

41:36.000 --> 41:40.240
who couldn't capture any value and 
now they're doing it and who knows, 

41:40.240 --> 41:44.400
maybe in, like, two or three 
years, the next crypto summer,

41:44.400 --> 41:48.320
winter, it will be all 
about data and Data Unions.

41:49.040 --> 41:50.400
I mean, I really hope so.

41:51.040 --> 41:55.440
I know we're running out of time, but 
maybe just to say one last thing on that, 

41:55.440 --> 41:58.400
which is, you know, what has Web3 done to date?

41:59.520 --> 42:02.240
You've got money, digital 
money, that's Bitcoin.

42:02.240 --> 42:06.800
Got contracts, really 
important, in, with Ethereum 

42:07.440 --> 42:10.080
and we've got a way to trade 
and financialize all of that.

42:10.080 --> 42:13.360
That's DEXs. What do NFTs 
represent in that schema?

42:14.160 --> 42:18.560
Assets. Well, what are 
some other great assets?

42:19.280 --> 42:23.040
Well, it's really hard to take a 
house and put that on the blockchain, 

42:23.040 --> 42:28.160
it's really, really hard to do that. 
But data is worth trillions

42:28.160 --> 42:31.360
and it's already digitally native, 
but it is stuck in Web2.

42:31.360 --> 42:32.960
And it's begging for scarcity.

42:32.960 --> 42:33.360
Right.

42:33.360 --> 42:36.240
That’s the biggest problem with 
data, it wants to be free,  

42:36.240 --> 42:38.640
but it also wants to be scarce at the same time.

42:38.640 --> 42:41.360
Yeah, there's a huge tension on that basis.

42:42.640 --> 42:49.120
So, Data Unions are a way of 
porting all of that Web2 value into Web3  

42:49.680 --> 42:52.640
and assetizing it. 
I see what Ocean has been doing.

42:52.640 --> 42:56.720
It's like, so I think great supporters 
of Data Unions, because they're like 

42:56.720 --> 43:00.960
please bring it in and to our 
marketplace obviously and trade it.

43:00.960 --> 43:05.120
Turn it into tradable assets and 
financialize it to your heart's content.

43:05.920 --> 43:07.040
So it's a fascinating model.

43:08.000 --> 43:09.040
All fingers crossed.

43:10.320 --> 43:11.040
Yeah, indeed.

43:11.600 --> 43:13.840
I should, you know, one last thing to mention.

43:13.840 --> 43:22.000
I didn't mention Tapmydata, who also, 
they're not building on Streamr as such, 

43:22.000 --> 43:25.760
but there are other Data Unions that are out there,

43:25.760 --> 43:29.280
that aren't part of the Streamr ecosystem 
and I think that really just proves, 

43:29.280 --> 43:35.280
like GeoDB, another one, Tapmydata, 
which they're all doing brilliant work

43:35.280 --> 43:37.040
and they're all Data Unions effectively.

43:37.040 --> 43:39.840
So it isn't just what we're doing.

43:39.840 --> 43:42.080
There's a whole ecosystem 
here, which is exploding.

43:42.640 --> 43:44.640
Because they're seeing the 
value in this model.

43:44.640 --> 43:48.640
Hopefully at least on blockchain, all 
of them are going to be interoperable.

43:49.760 --> 43:56.880
Yeah, I think they will, because 
they know that it makes sense, to that lego.

43:58.320 --> 44:01.760
You know, people talk about DeFi legos, 
well data legos is something that 

44:01.760 --> 44:06.000
Trent from Ocean talks about 
and he's right about that one.

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Like people want to mix and match datasets like 
it's great, that's where these things need to be.

44:12.320 --> 44:21.040
Yes. With that I think now is a good time to wrap 
up. Shiv, by the way your name is Shivan or Shiv?

44:21.680 --> 44:22.480
No, just Shiv.

44:22.480 --> 44:22.980
Just Shiv.

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My parents couldn't be bothered to give me 
more than one syllable as the first name.

44:27.760 --> 44:28.560
It's just Shiv.

44:28.560 --> 44:33.280
Yeah, Diksha sometimes calls 
me Nim, so that's my Shiv name.

44:35.280 --> 44:39.520
So, what's your Twitter handle or like, what's 
the best place for people to follow you?

44:40.960 --> 44:43.520
@shivmalik is my Twitter handle.

44:43.520 --> 44:44.715
Okay.

44:44.720 --> 44:46.684
Pretty simple, keep it simple.

44:46.684 --> 44:49.753
Yeah, that's the best place, 
I'm fairly addicted to Twitter.

44:49.760 --> 44:53.760
I'll get to your message 
one day, within 48 hours.

44:55.040 --> 44:57.680
Okay, thanks a lot. Diksha, 
anything from your side?

44:58.800 --> 45:00.000
We’re good for now.

45:00.000 --> 45:00.320
Okay.

45:00.320 --> 45:02.240
But definitely, I think 
we'll have you again.

45:03.280 --> 45:04.640
There's so much to talk about.

45:05.280 --> 45:10.720
It'll be a real honor and humbled to 
be on the podcast and to be able to chat.

45:10.720 --> 45:16.000
This is, I love doing this, you can probably 
tell, so thanks for having me on.

45:17.280 --> 45:18.800
Same here, it was an honour.

45:18.800 --> 45:24.160
Thanks to everyone for listening to this episode 
and see you or talk to you in the next one.

45:24.160 --> 45:25.422
Bye.

Trent McConaghy | Data Tokens, NFTs and DAOs.srt

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What does it mean to own something?

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And the word ownership is really a red herring.

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It's sort of like the word consciousness.

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What does it mean to be conscious?

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Or AI, what does AI mean and stuff?

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And I've always found that it's really useful
if you can discover some pragmatic definition,

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usually someone else has come up 
with a pragmatic definition.

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And also acknowledging that there's always going to 
be many many definitions for any of these things.

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You know, there's 20 different definitions for AI, 
there's 20 definitions for consciousness etc.

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And there's 20 definitions for NFTs.

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That's okay.

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So, what is an ownership, 
actually I should say too.

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So what is a pragmatic definition for ownership?

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And over the… one that I've discovered is, a pragmatic 
definition for ownership is a bundle of rights.

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To own something is to have a particular bundle of rights.

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This is Season 2 of Voices of the Data Economy.

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A podcast supported by Ocean Protocol’s Foundation.

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We bring to you the voices shaping the data
economy and challenging it at the same time.

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Listen to founders, tech policy experts and
pioneers in impact investing.

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All sharing their relationship with data.

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Hello everyone, today we have none other than
our very own Trent with us.

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Trent is the founder of Ocean Protocol and
this is actually the second appearance of

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an Ocean founder on this podcast.

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Last year, around similar time, we had Bruce Pon 
and that's the time we really spoke about

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what is Web3, the concept of a new data economy
and all the things around that.

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So, my suggestion is that it might be a good
idea to go through that episode, before you

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come to this one, but don't worry, if not,
we will quickly try to touch upon most of

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the things that we spoke about then and see
what's happened between then and now.

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So, thank you for coming here today Trent
and it is so exciting to talk to you.

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Hello.

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Thanks for having me.

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So Trent, before we really start talking about
Ocean and all the great things that you're

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doing there, probably I would love to know
how Ocean happened to you.

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And how does it really fit into your personal
mission, when it comes to data, data ownership

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and all the things you believe in your life.

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Sure, so, we probably have to 
start at the very beginning.

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I was raised in Rural Canada, on a farm and
it was, in the area I lived in the province

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in Canada, it was very much co-ops everywhere.

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There was a local co-op for grocery store,
there was a local co-op bank and there was

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one of the biggest co-ops in the world for
farmers, something called Saskatchewan Wheat

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Pool, where there was tens of thousands of
farmers that collectively sold their grain

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to that co-op and then that co-op would market
their grain and distribute it and so on.

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So, I kind of grew up in a very co-op oriented
atmosphere, which is, you know, there's a

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capitalist side, which is, the farmers having
their own businesses and so on, but then also

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working together with other farmers to achieve,
you know, broader community aims, as part

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of the capitalist side.

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So, that's kind of what I grew up in.

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And also shoveling pig manure, driving drain
tracks and hacking computers actually.

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So that's sort of the environment I grew up in.

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And I studied in university, electrical engineering,
computer science and then for about 15-20 years, 

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I sort of found this passion for work
on artificial intelligence, so with that 

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I did a couple startups and a PHD on that, really
and because I was trained as an electrical

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engineer then the most straightforward application was 
to use AI tools to help solve problems in circuit design.

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So I really zoomed in and got really good
at helping analog designers, memory designers,

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all this, design their circuits for using
AI tools under the hood, so this whole world

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of computer-aided design and this was basically
from the late 90s until the mid-2010s or so.

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So, that was kind of a long time doing that
as an entrepreneur, as an academic, all sort

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of rolled at once and PHD of course, 
I mentioned there too.

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And then, you know, I'm a big nerd, so I like
to follow cool technologies and so on, infatuations

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with VR, or brain computer interfaces or whatever.

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And along in 2010, I became fascinated with Bitcoin and 
you know downloaded a node and played with it.

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Friends of mine and I would hang out 
and talk about it all the time.

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And I bought some Bitcoin in 2011, 
I lost those keys long ago.

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And then, in 2013 I started spending a lot
more, I basically moved to Berlin and I started

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hanging, with people in Berlin and I discovered
this group of people that was talking, not

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just about bitcoin but about blockchain and
that really caught my interest.

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I hadn't really thought much about the other
applications, beyond Bitcoin.

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And so I went back to the Bitcoin whitepaper,
learned about, looked at the detail, realized

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oh wow, this thing is super general, it's
a general purpose technology, it's not just

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to solve one problem, but it could solve a
whole swath of different problems and really

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transform the world in really 
positive ways, if we all did well, as a tool.

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So from that, that was early 2013.

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Along the way, I also talk a lot with my wife, who's 
very patient with me as I get excited about technology.

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She is a professional museologist, so she's
worked at the Louvre, she's ran galleries,

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that sort of thing and in 2013, in early 2013,
after I was learning about blockchain, we

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had just visited a gallery and we were sitting
down and she started talking about the problem

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of owning digital art and I had then also
talking, been going on and on about Bitcoin

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and then, the neurons fired together and we
basically asked what if you could own bitcoin,

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sorry, what if you could own 
digital art the way you own bitcoin.

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And that turned out to be a really great problem
to solve, so we started pursuing it.

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We started basically writing about it, pulling
in Bruce, who you had in earlier as, on this

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podcast as someone to help pursue the project with.

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And then also pulled in some people to help
build some prototypes and stuff, work with

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artists and that's what led to ascribe.

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So, by mid-2014 we were full-time at it, mid
late 2014, chasing ascribe, which is basically,

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this platform, to solve problems for digital
artists and for collectors.

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So, from the artist side, it's like, okay,
how do you get paid?

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How do you make a better money?

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From the collector side, it's, how can there
be value ascribed to these digital artworks?

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And then for the galleries, operating as middleman basically, 
how do they connect the buyers and the sellers better?

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With better tracks of providence 
of who owns what, all that.

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So, this is really what Ascribe set up to
solve and we built something we're quite proud of.

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We pursued that for a few years 
and we got investment, all that.

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And that basically pivoted into BigchainDB,
which was basically to address issues of scale,

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of data, of blockchains.

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And that pivoted into Ocean.

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So, by mid-2017, we had really started working
in earnest in Ocean, even in early 2017 with

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sort of a fork of Bigchain actually.

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And since that time, since late 2017, 
the focus has been full Ocean.

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And everything, kind of all the work that
I had done before and that Bruce had done

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and so on, all roads led to Ocean in a sense.

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So, the AI work that I had done, I had a lot
of friends in the AI world and they had a

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big problem of, how do we get our hands on data?

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They want to build…

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A friend of mine for example, he was trying
to build models to predict cancer, and, off

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of genetic data, but he could only get its
hands on samples of 100 people at once.

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So, you've got this genetic data with tens
of thousands of input variables and only about

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100 samples, so you can't even build a good
linear model, so, and imagine though if you

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can build a model off of not just 100 people,
but 10.000, or a million, or even a billion,

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without causing privacy issues.

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That would be like, pretty amazing.

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And we started to recognize that 
blockchain could solve that.

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And that was basically the impetus of Ocean.

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So, from my perspective, I saw that, how do
you get data into the hands of AI people,

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like more data into the hands of AI people,
where they really know how to create value from it.

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And then, there are other aspects too.

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It's like, okay, how do you think about data,
well data is a form of intellectual property,

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just like digital artists, so then it's like,
great, all the stuff that we learn about helping

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people to manage their intellectual property with ascribe, 
we can do the same tools and tactics with Ocean.

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And then, finally the big data side too with
BigchainDB and we pulled that in and then

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Bruce also had a bunch of 
the financial background etc.

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And all this just tied together 
and that's what led to Ocean.

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And of course, there was bigger structural
issues, we saw with the world beyond that,

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things like, where, it turns out that most
of the money in AI was flowing into the hands

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of just a small number of companies, ones
that had not only lots of data, but lots of

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AI expertise and that was a rare combination.

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00:09:51,240 --> 00:09:55,269
And that rare combination basically, 
was Google, Facebook, a few others.

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And so, they were reaping the rewards and
basically, doing this arbitrage, taking advantage

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00:10:01,730 --> 00:10:06,610
of people who didn't really see that their
data had value, but Facebook and Google etc

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00:10:06,610 --> 00:10:11,119
have known how to extract value out of that
and make billions in the process.

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00:10:11,119 --> 00:10:16,259
So, we said, okay can we rewire the rules
of ownership around data, around people's

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data etc in a way that it can benefit.

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And it's not just for people.

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It can be for small companies, 
large companies, nations etc.

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00:10:23,379 --> 00:10:28,819
They all really care about their data sovereignty,
about managing and controlling their own data.

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00:10:28,819 --> 00:10:32,850
So what if you can make, rewire the rules
for that, make it easy to implement for people

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building applications and ultimately leading
to applications that are easy to use for people.

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00:10:36,869 --> 00:10:38,209
So that's the story of Ocean.

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00:10:39,209 --> 00:10:40,209
Wow. Okay.

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00:10:40,209 --> 00:10:47,790
So, I mean, we can really zoom into a lot
of things you mentioned and also go back to

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00:10:47,790 --> 00:10:52,089
what you did with NFTs, but that, on a later part.

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So, if you're like me and you've been following
Ocean, you would have heard things like data

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marketplace, Ocean marketplace and, you know, a lot and 
I've heard that and I've been following up with that.

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00:11:02,769 --> 00:11:08,760
But I probably would love, if you can give
a little bit of background on some terms and

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00:11:08,760 --> 00:11:16,059
explain it to our listeners, like something
like, what is actually a data token and what

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00:11:16,059 --> 00:11:19,170
does a data marketplace look like?

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00:11:19,170 --> 00:11:23,717
And now, when you explain that, where does
actually Ocean come into the picture?

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00:11:24,751 --> 00:11:32,819
Sure. So, you know, at a high level, kind of the
aim is for people and organizations to reclaim

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00:11:32,819 --> 00:11:37,509
their data sovereignty, where they can own
and control and manage their own data, while

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00:11:37,509 --> 00:11:39,540
preserving privacy.

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00:11:39,540 --> 00:11:48,689
And then, if you think about it, data is valuable,
so around rewiring the world for management

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00:11:48,689 --> 00:11:56,279
of data and data sovereignty, given that data
is valuable, it really, a lot of it is about

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00:11:56,279 --> 00:12:03,790
creating this open data economy, where it's a level 
playing field for all, while preserving privacy.

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00:12:03,790 --> 00:12:07,759
So you want to have this data economy, but
then, if you've got an economy, well, what

155
00:12:07,759 --> 00:12:10,839
is, sort of, critical elements of an economy?

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00:12:10,839 --> 00:12:15,220
Well you need there to be, 
buying and selling of data.

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00:12:15,220 --> 00:12:19,860
And okay, if you're gonna have a buying and
selling of data, you could have one person's

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00:12:19,860 --> 00:12:23,649
telling to another and if you have a bunch
of those back and forth, sort of over the

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00:12:23,649 --> 00:12:29,170
counter, whatever, you call it, that's a start,
but if you can have platforms that connect

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00:12:29,170 --> 00:12:34,309
a bunch of possible buyers with a bunch of
possible sellers, those platforms are marketplaces.

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00:12:34,309 --> 00:12:36,800
Like, that's the role of a marketplace.

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00:12:36,800 --> 00:12:42,369
And so, you could imagine, okay let's have
one big giant, perfect, beautiful marketplace

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00:12:42,369 --> 00:12:46,209
to connect all the potential buyers and all
the potential sellers, but that, of course,

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00:12:46,209 --> 00:12:48,149
on its own would be centralized.

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00:12:48,149 --> 00:12:50,679
And, it's not really, one size fits all, anyway.

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00:12:50,679 --> 00:12:55,399
You're gonna have some marketplaces that are
tuned to buying data from farmers and selling

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00:12:55,399 --> 00:12:58,740
data to farmers, or otherwise.

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00:12:58,740 --> 00:13:04,670
And other ones around the data, that you might
have otherwise shared to Facebook, for example.

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00:13:04,670 --> 00:13:10,724
Or data about your location, or data that a company 
might have on sales of their cars, or whatever it is.

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00:13:10,749 --> 00:13:15,480
And so, there's all these different sorts
of shapes and sizes of types of data, different

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00:13:15,480 --> 00:13:19,680
verticals of this, so we saw, okay, instead
of one data marketplace, what if there were

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00:13:19,680 --> 00:13:21,999
a thousand different data marketplaces?

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00:13:21,999 --> 00:13:25,110
And what does it take to get to a thousand
different data marketplaces?

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00:13:25,110 --> 00:13:27,889
For a thousand data marketplaces to bloom?

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00:13:27,889 --> 00:13:30,649
And these could be web apps, these could be
mobile apps, they could even be marketplaces

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00:13:30,649 --> 00:13:32,699
that don't even look like marketplaces.

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00:13:32,699 --> 00:13:41,119
So, that's basically, what we were aiming
for is, as sort of, a first like, in a sense,

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you've got a data economy happening, if you've
got lots of exchange of data privacy reserving

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00:13:46,980 --> 00:13:52,379
etc, where there's a lot of value being 
transferred as well as open data sharing.

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00:13:52,379 --> 00:13:57,137
But for pure open data sharing, where there isn't any 
permissions or anything, we already have the web.

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00:13:57,149 --> 00:14:04,711
Like that was the idea of the web, when it was invented 
in 1989 by Tim Berners-Lee out of Cern in Switzerland.

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All he wanted to do is share data with his
physicist friends, right?

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And that's what he did.

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And so, you know, the world wide web is a
data sharing protocol itself, but it doesn't

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have anything to say about the buying and
selling of these items and it also doesn't

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have sort of, that's for the exchange of value,
where things are priced and even for the free stuff.

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What if you have a group of 10 of you, or
1.000 of you in a company and you want to

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share data amongst each other, it's sort of
like fine grain permissions.

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So those are a couple things that the world
wide web protocol doesn't do out of the box.

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But what if you could sort 
of layer on top of that?

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So going back, I'm going to answer your questions
now, but, overall, I wanted to sort of flesh

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out this idea of what 
a data economy looks like.

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So on one part, it's a thousand data marketplaces
of different shapes and sizes and another

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part it's data sharing, that is free, but
with more fine grained permissions to be able

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to share amongst a group etc.

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So extending above and beyond 
what the worldwide web does.

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So then, drilling in, how might you do this?

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And if you, and this is where basically we
said okay, we know that blockchain itself

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provides a lot of potential tools here, we
had already spent many years in blockchain,

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so we understood a lot of the benefits of
blockchain quite intimately.

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And, there's a few core benefits compared
to say, the very mundane description of a

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blockchain is, it's just a database, but it's
a very special database.

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It's very special, in that it adds four new
characteristics that kind of give it really

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cool possibilities, any one of those four
characteristics is interesting.

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It's decentralized, so instead of being controlled
by a single entity, like Facebook or something,

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it can, that control is spread among 10, 
or 1.000, or 10.000 people.

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And that, you know, if you're spread among 10.000 people, 
then you're essentially a public utility network.

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So that's one. The second is immutability.

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So you can have these providence trails of
the transactions happening.

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So just like in digital art, you can see,
okay, this digital art was first minted by

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this person, this NFT, and then it got sold
to this person, then this person, then this

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person, so you have the providence trail.

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And all of that is on the blockchain.

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It's immutable, once it's there, it's like
etched in a stone for good.

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The third thing is the fact 
that you can own assets.

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So, what does it mean if I own one Bitcoin?

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It means that I've got a private key, it's
sort of like a password, but I've got the

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private key to a particular address, 
that holds one Bitcoin.

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And it means, I can use that private key to
basically, say send 0.3 Bitcoin to this person

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here, send 0.2 bitcoin to that person, up to spending 
all of that one Bitcoin that I have there.

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So that's the third thing, basically, ownership
is the possession of that private key.

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So not your keys, not your Bitcoin, 
your keys, your Bitcoin.

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And this translates to beyond Bitcoin, 
to things like NFTs or data.

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So, your keys, your NFTs, 
your keys, your data, right?

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And then, there's one fourth benefit 
of blockchain, which is incentives.

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So, you know, Bitcoin's kind of cool and kind
of amazing in that with just a piece of software

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that initially, one team, or one person wrote,
this somehow grew into this global phenomenon,

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with tens of thousands of people running nodes.

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This asset that is worth more than a trillion
dollars and spawning a whole new industry

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and that was just with one chunk of code,
that did evolve over time.

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And the core of this is incentives, so this
piece of software said, I'm gonna pay you

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just a little bit of Bitcoin, if 
you help to secure the network.

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So every 10 minutes, if you're helping to secure the network, 
you have a chance of winning some Bitcoin, right?

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So those four things are the big benefits
of blockchain, compared to previous, you know,

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boring databases, if you will.

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So decentralized, immutable, assets and incentives.

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And then, looping back once again into markets,
we asked, okay, how do we rewire the world,

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but for new rules around data?

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How do we create?

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How do we let a thousand 
data marketplaces bloom?

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And then, with the understanding, then we
can use this new tool, blockchain to do so.

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And with that new tool, given these capabilities
like mentioned, decentralized immutable assets

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and incentives.

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So we said okay, for sure.

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So with that,the initial design of Ocean,
v1, v2, we had some designs around, you own

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the data if you have private keys.

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But then, we started asking, okay how do we
make this be even more interoperable with

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other blockchain tools out there, etc?

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Because, even when we started building Ocean
v3, this is about a year and a half ago, it

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was already a huge industry, hundreds of billions,
I forget if it had hit a trillion yet and

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there's all these tools, there's these crypto
wallets to hold your ETH tokens and Bitcoin

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tokens and tokens from everything else, including
Ocean, you know, Metamask, Trezor, hardware

253
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wallets, industrial grade ones, 
that are, all that stuff.

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So there's all these amazing tools, just for
managing those crypto assets, holding them

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for custody as well as 
transferring them and so on.

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00:19:27,650 --> 00:19:32,240
And then, there's also a bunch of tools around
DAOs and groups of people managing assets

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and exchanges.

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00:19:33,240 --> 00:19:35,900
Buying and selling these assets, whether 
centralized or decentralized and so on.

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00:19:35,900 --> 00:19:43,570
So, we asked, okay, how can we leverage some
of these concepts to make Ocean more interoperable?

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And we realize, something very straightforward
is in the world of data, if I publish a dataset

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then, and maybe there might be 10 or a thousand
people that want to license that dataset,

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that want to use it.

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So that's a fungible concept, if you've got
a license and I've got a license, I could

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swap my license with you, you could send yours
to me and we're just as happy, because it

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means the same thing.

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We can each use that dataset.

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Yeah.

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00:20:09,409 --> 00:20:15,948
It's like, if you and I each own the same Michael Jackson 
Thriller CD, we could swap them, not a big deal.

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So same thing here, they're fungible, they're
swappable and with that then, we said, okay,

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00:20:22,730 --> 00:20:28,770
well, there's an existing standard out there,
called ERC20 and it's a standard for fungible

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tokens and Ocean token itself is fungible.

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And there's, all the tokens out there, Bitcoin
token, Ethereum, all those, they're all fungible

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and beyond a few of the ones that have their
own base chain like, Bitcoin and Ethereum,

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the vast majority of tokens follow the standard.

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So, we said, well what if each dataset had
its own ERC20 token that followed the standard?

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So let's say, I published 
a dataset for, say, my DNA.

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What if that DNA got its own data token, 
its own ERC20 token center?

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00:21:01,461 --> 00:21:02,562
Oh. Okay.

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00:21:02,562 --> 00:21:03,062
Yeah.

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So, it's following the standard.

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00:21:04,931 --> 00:21:08,310
So I might say, okay, I'm gonna 
publish Trent's dataset.

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Maybe some CSV and I'm gonna 
mint a thousand tokens of this.

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00:21:13,650 --> 00:21:19,312
So now, I could send 1.0 tokens to you and
now you have the right to consume that and use it.

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I can send another 1.0 tokens to Alice and
Alice can then consume it etc, right?

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00:21:28,580 --> 00:21:31,070
And so, basically, that is 
the idea of a data token.

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00:21:31,070 --> 00:21:41,050
An Ocean data token is a fungible token, following
the ERC20 token standard and with great benefits,

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00:21:41,050 --> 00:21:44,470
in terms of interoperability and simplicity.

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Interoperability because out of the box, all
those wallets that people are already using

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00:21:50,320 --> 00:21:55,290
to hold their Bitcoin, their ETH, their Ocean,
etc, can now hold data tokens.

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00:21:55,290 --> 00:21:58,350
And, not only hold them but manage them.

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00:21:58,350 --> 00:22:05,750
So, if I have, 20 of these Trent DNA tokens
in my Metamask, sitting on my phone, I can

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use my phone to share access to that to others,
I could send 1.0 tokens to you, from my phone,

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00:22:12,520 --> 00:22:19,130
using Metamask so Metamask becomes 
a data sharing platform.

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00:22:19,130 --> 00:22:21,080
And any crypto wallet does.

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00:22:21,080 --> 00:22:25,750
And how about one that is bank grade 
security for data sharing?

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00:22:25,750 --> 00:22:30,583
Trezor or Ledger, hardware wallets and these
hardware wallets are known to have bank rate security.

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And this is, compare that to the status quo.

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Every month, or three, you hear about another
hack of Equifax, or Bitcoin, or otherwise.

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I saw one in, last week, I think there was
one where the CIA got hacked and there was,

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00:22:46,100 --> 00:22:47,560
like thousands of people’s…

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00:22:47,560 --> 00:22:48,790
I know, right?

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00:22:48,790 --> 00:22:51,410
So there was, thousands of people's 
addresses from the CIA, right?

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00:22:51,410 --> 00:22:53,300
And that's going to be sensitive data.

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00:22:53,300 --> 00:22:54,300
Yeah.

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00:22:54,300 --> 00:22:58,340
So, that's kind of been the status quo, 
and it's like, okay, here we go again.

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00:22:58,340 --> 00:23:01,070
And this is a big problem, right?

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00:23:01,070 --> 00:23:05,590
And a cool thing about blockchain, like you
might say, okay, bank rate security.

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00:23:05,590 --> 00:23:08,830
And maybe I'll just elaborate like how that
could possibly be like, how can it be bank

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rate security, even though it's on you?

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00:23:10,640 --> 00:23:13,790
And the answer is, it flips 
around the security model.

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00:23:13,790 --> 00:23:19,480
So the traditional security model is M&M,
where you have lots and lots of super valuable

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00:23:19,480 --> 00:23:23,390
data sitting inside, that's all the yummy
chocolate and then you've got this hard shell

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00:23:23,390 --> 00:23:28,950
around, but if anyone is able to come along
and pierce any tiny bit of that hard shell,

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00:23:28,950 --> 00:23:32,000
then they can go in and 
eat all the yummy chocolate.

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00:23:32,000 --> 00:23:35,880
And that's the traditional security model,
so when Equifax got hacked, some hacker found

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00:23:35,880 --> 00:23:40,630
their way in and basically got access to those
700 million people's worth of records, I think

317
00:23:40,630 --> 00:23:43,490
of 700 million, 300 million, or 
700 million people, I forget.

318
00:23:43,490 --> 00:23:45,630
And same thing with CIA or otherwise.

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00:23:45,630 --> 00:23:49,130
So, that's the traditional model.

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00:23:49,130 --> 00:23:54,100
What blockchain does, it says, what is the
most valuable thing, it's this much smaller

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00:23:54,100 --> 00:23:58,710
set of data, which is a list of transactions
of what has been sent where.

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00:23:58,710 --> 00:24:02,030
And that is basically the data on the blockchain.

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00:24:02,030 --> 00:24:08,720
And imagine if you have 10.000 copies of that
data, among 10.000 people and those people

324
00:24:08,720 --> 00:24:11,120
are incentivized to keep those copies together.

325
00:24:11,120 --> 00:24:15,770
So that's basically the list of transactions
and that's the 10.000, miners running Bitcoin,

326
00:24:15,770 --> 00:24:18,230
etc, or Ethereum etc.

327
00:24:18,230 --> 00:24:23,720
And so, basically, now, if I'm so, that's
how the security model gets inverted.

328
00:24:23,720 --> 00:24:27,490
So you've got this rock hard center, it’s
sort of like a nut and then around that it's

329
00:24:27,490 --> 00:24:31,580
semi-malleable, but never, 
it doesn't compromise the core chain.

330
00:24:31,580 --> 00:24:35,200
So maybe an exchange gets hacked now and then,
but that doesn't affect the integrity of the

331
00:24:35,200 --> 00:24:36,840
rest of the system.

332
00:24:36,840 --> 00:24:41,080
And so it really flips it around, so now imagine,
you can take and insert into this rock-hard

333
00:24:41,080 --> 00:24:47,020
nugget of the system in the very center ways
to manage data, by using the existing infrastructure

334
00:24:47,020 --> 00:24:48,470
and that's exactly what Ocean is doing.

335
00:24:48,470 --> 00:24:52,890
So we're using the existing infrastructure
of the chains, as well as one level up, all

336
00:24:52,890 --> 00:24:58,250
this infrastructure that has really gotten
a lot hardened for ERC20 tokens, for these

337
00:24:58,250 --> 00:25:00,660
fungible tokens and for the wallets.

338
00:25:00,660 --> 00:25:05,010
So now we basically are inheriting all of
this, yeah, really great infrastructure from

339
00:25:05,010 --> 00:25:09,640
the world of blockchain bankrate security
etc, but now we are porting it over to the

340
00:25:09,640 --> 00:25:13,420
world of data management, for custody of data
and for management of data.

341
00:25:13,420 --> 00:25:18,710
So that's basically the essence of data tokens,
it's really this idea, sort of leveraging

342
00:25:18,710 --> 00:25:21,410
all the existing infrastructure for more.

343
00:25:21,410 --> 00:25:27,820
And then, markets basically, it kind of extends
on this, so in the world of blockchain, there's

344
00:25:27,820 --> 00:25:30,610
also centralized exchanges 
and decentralized exchanges.

345
00:25:30,610 --> 00:25:31,610
Yes.

346
00:25:31,610 --> 00:25:34,560
You've got Coinbase, you've got Binance, 
etc, for centralized.

347
00:25:34,560 --> 00:25:35,560
True.

348
00:25:35,560 --> 00:25:38,642
Decentralized you've got Balancer, Uniswap
etc, but, you know what they're exchanging?

349
00:25:38,642 --> 00:25:40,530
They're exchanging fungible tokens.

350
00:25:40,530 --> 00:25:42,030
ERC20 etc.

351
00:25:42,030 --> 00:25:47,620
So, you can actually, if you want, I know
the decentralized ones are permissionless,

352
00:25:47,620 --> 00:25:51,040
like you can go in and create your own swap
between, say you know Ocean and ETH, if you

353
00:25:51,040 --> 00:25:56,650
want, but then given that data tokens are
already ERC20 functional, you can go into

354
00:25:56,650 --> 00:26:03,870
Uniswap and create your own pool, that swaps
ETH to data tokens, or create a Balancer pool

355
00:26:03,870 --> 00:26:08,210
that swaps Ocean to data tokens, or 
like for a particular data token.

356
00:26:08,210 --> 00:26:09,530
And that's exactly what we do.

357
00:26:09,530 --> 00:26:17,960
So Ocean market is a data marketplace, where
you go there and people can publish their

358
00:26:17,960 --> 00:26:22,680
data assets to create these 
fungible token contracts.

359
00:26:22,680 --> 00:26:27,810
And then, others can go on there and they
can buy and sell data sets and under the hood,

360
00:26:27,810 --> 00:26:33,000
it's using exchange technology, you know,
specifically it's using decentralized exchange

361
00:26:33,000 --> 00:26:34,390
technology from Balancer.

362
00:26:34,390 --> 00:26:40,260
So, once again, we're able to leverage off-the-shelf
technology that has been developed for crypto

363
00:26:40,260 --> 00:26:46,940
and we are basically leveraging it to solve
long-standing problems in the world of data.

364
00:26:46,940 --> 00:26:53,740
So basically, for data custody and data management
that's wallets and then for buying and selling

365
00:26:53,740 --> 00:26:59,420
of data, you can have a fixed price and we
just have simple contracts for that, or you

366
00:26:59,420 --> 00:27:05,260
can even have automatic pricing of data, automatic
discovery of data and that's really what these

367
00:27:05,260 --> 00:27:07,120
decentralized exchanges are for.

368
00:27:07,120 --> 00:27:08,250
And that was always a big question too.

369
00:27:08,250 --> 00:27:09,250
How do you price data?

370
00:27:09,250 --> 00:27:10,670
Well, how do you price Ocean?

371
00:27:10,670 --> 00:27:14,510
You have these decentralized exchanges, 
so same thing with data tokens.

372
00:27:14,510 --> 00:27:15,690
How do you price data tokens?

373
00:27:15,690 --> 00:27:19,340
You have these decentralized 
exchanges that do it automatically.

374
00:27:19,340 --> 00:27:24,410
So yeah, that's I guess a summary, it was
a longer answer, but I hope I downloaded a

375
00:27:24,410 --> 00:27:26,980
mental model for your audience.

376
00:27:26,980 --> 00:27:27,980
Yeah.

377
00:27:27,980 --> 00:27:28,980
It was amazing actually.

378
00:27:28,980 --> 00:27:34,640
And also, it sort of answers the question
to a lot of things we have been discussing

379
00:27:34,640 --> 00:27:40,150
in the past episode and episodes and it makes
me happy that actually, there is a possibility

380
00:27:40,150 --> 00:27:46,930
of this happening, or it's already happening,
which leads me to my next follow-up is that,

381
00:27:46,930 --> 00:27:52,730
how far are we with Ocean v4 
in actually solving this?

382
00:27:52,730 --> 00:28:00,390
I mean, are there any successful use cases
already with people using the Ocean marketplace

383
00:28:00,390 --> 00:28:02,020
and going with this?

384
00:28:02,020 --> 00:28:03,020
Yeah.

385
00:28:03,020 --> 00:28:09,000
So, the timeline for Ocean is, the project
started really in earnest in mid-2017 and

386
00:28:09,000 --> 00:28:16,200
Ocean v1 and v2, we laid out, you can view
Ocean v1 to v4 as each one a succession of

387
00:28:16,200 --> 00:28:19,060
solving sort of one big problem at a time.

388
00:28:19,060 --> 00:28:31,160
So Ocean v1 basically said, let's have sovereign
data and Ocean v2, it says, so Ocean v1 is,

389
00:28:31,160 --> 00:28:35,710
how do you solve the issue of people owning
their own data, rather than some centralized

390
00:28:35,710 --> 00:28:37,820
bank or something holding the data?

391
00:28:37,820 --> 00:28:39,200
So, that's Ocean v1.

392
00:28:39,200 --> 00:28:46,030
v2 is, people said, okay, well if I'm going
to download my data, sorry, if I'm going to

393
00:28:46,030 --> 00:28:50,029
publish data, what if other people can download it, 
can't they copy and paste it won't that kill privacy?

394
00:28:50,050 --> 00:28:53,590
So Ocean v2 said, that's true.

395
00:28:53,590 --> 00:28:57,660
And so let's leverage some 
privacy preserving technology.

396
00:28:57,660 --> 00:29:01,890
We did a survey, we looked around at all the
different approaches, everything from differential

397
00:29:01,890 --> 00:29:06,190
privacy to homework encryption and they're
all at different levels of maturity, but by

398
00:29:06,190 --> 00:29:14,153
far the simplest is simply let compute sit next to 
the data itself and then people buy access to results.

399
00:29:14,170 --> 00:29:19,510
So instead of me selling, imagine I'm selling
my DNA data, well if someone downloads that,

400
00:29:19,510 --> 00:29:23,660
then they've got that and maybe they can,
that can be problematic, because that's pretty

401
00:29:23,660 --> 00:29:29,850
sensitive data, but instead what if they just
say, okay, I want to compute some average

402
00:29:29,850 --> 00:29:35,930
across my DNA data, or compare Trent’s DNA
data with five other DNA datas and just look

403
00:29:35,930 --> 00:29:38,711
at like one or two fields of that DNA data.

404
00:29:40,710 --> 00:29:45,300
That is basically much simpler, so that's
what Ocean v2 was, was compute-to-data.

405
00:29:45,300 --> 00:29:54,420
So Ocean v2 came out in early 2020, Ocean
v1 came the year before and so Ocean v1 solved

406
00:29:54,420 --> 00:29:57,000
data sovereignty, Ocean v2 cell privacy.

407
00:29:57,000 --> 00:30:02,470
Ocean v3 basically said, how do, 
it actually solved a few things at once.

408
00:30:02,470 --> 00:30:03,960
How do we make the thing simpler?

409
00:30:03,960 --> 00:30:10,420
How do we have really crazy interoperability
for custody and management of data, as well

410
00:30:10,420 --> 00:30:12,950
as, how do we automatically, how do we price data?

411
00:30:12,950 --> 00:30:18,750
And so, it's all those things, interoperability,
simplicity and automatic pricing.

412
00:30:18,750 --> 00:30:24,870
And then, when we shipped Ocean v3, that was
last fall, so like about October, you know,

413
00:30:24,870 --> 00:30:31,060
we had there was, people kind of really got
excited and a lot of people piled in and published

414
00:30:31,060 --> 00:30:38,170
hundreds of datasets, millions of dollars 
of value locked up etc and really, really promising.

415
00:30:38,190 --> 00:30:43,360
And a couple things then 
slowed the traction there.

416
00:30:43,360 --> 00:30:51,170
One was, the gas fees on Ethereum mainnet
went kind of crazy, sort of with the, basically

417
00:30:51,170 --> 00:30:54,950
that was at the beginning of this year and
the second thing was, there was a small fraction

418
00:30:54,950 --> 00:31:02,100
of users that took advantage of some special
dynamics of these automated exchanges, where

419
00:31:02,100 --> 00:31:03,100
they could rug pulls.

420
00:31:03,100 --> 00:31:08,260
So they would publish a dataset, pump it up,
get other people to start buying in and then

421
00:31:08,260 --> 00:31:09,620
they would dump on them.

422
00:31:09,620 --> 00:31:12,480
So that's called a rug pull in cryptospeak.

423
00:31:12,480 --> 00:31:15,840
And so it was basically not 
quite as safe as it could be.

424
00:31:15,840 --> 00:31:23,590
So, what we're doing for Ocean v4 is solving
rug pulls and also we're doing the data NFTs

425
00:31:23,590 --> 00:31:24,630
and I can get to that.

426
00:31:24,630 --> 00:31:27,930
And also, I guess one more thing which is,
help people monetize even further.

427
00:31:27,930 --> 00:31:30,240
So basically Ocean v3 added a few things.

428
00:31:30,240 --> 00:31:36,070
It added, like I mentioned, better management
of data with sovereign data with the wallets,

429
00:31:36,070 --> 00:31:38,140
automatic pricing of data and simplicity.

430
00:31:38,140 --> 00:31:45,304
Ocean v4 adds three specific things, solve rug pulls, 
data NFTs and help the community monetize.

431
00:31:45,330 --> 00:31:48,800
And the timing is we're targeting mid-January next year.

432
00:31:48,800 --> 00:31:55,900
We're hoping to have it this year, but we prefer quality 
over rushing things by a month or two.

433
00:31:56,900 --> 00:32:03,789
Okay and if you have to pick the best, your favorite 
use case out of it, which one would you pick up?

434
00:32:03,810 --> 00:32:12,430
Yeah, so I mean, Ocean v4, each of these sort
of big bullet points addresses particular

435
00:32:12,430 --> 00:32:13,570
issues that we encountered.

436
00:32:13,570 --> 00:32:17,780
So, for us, it's sort of, 
ship relation often, keep learning.

437
00:32:17,780 --> 00:32:22,510
And between the big releases, we always have
steady small point releases and stuff, like sub points.

438
00:32:23,510 --> 00:32:31,440
So the rug pulls was an issue we encountered
from v3 and we solved that, the problem to

439
00:32:31,440 --> 00:32:38,250
solve is, solve rug pulls and the feature
that we're solving it with is making it basically

440
00:32:38,250 --> 00:32:40,270
impossible to become a data token whale.

441
00:32:40,270 --> 00:32:45,481
So, when you publish a dataset, you no longer
own 100 of those tokens up front, rather they

442
00:32:45,481 --> 00:32:54,680
are controlled by the exchange, the decentralized
exchange and then, whenever people stake,

443
00:32:54,680 --> 00:32:58,820
into that decentralized exchange, into that
pool, then it's minting more tokens.

444
00:32:58,820 --> 00:33:03,139
So, basically you are incentivized to get
people like, how do you make money as a publisher,

445
00:33:03,139 --> 00:33:07,059
it's whenever people buy and consume those
data assets, then you're going to get those

446
00:33:07,059 --> 00:33:11,540
data assets back like each of those tokens,
so that basically, it flips it around.

447
00:33:11,540 --> 00:33:19,300
It means, there's no longer sort of data token
whales and instead it is incentivizing people,

448
00:33:19,300 --> 00:33:21,620
the publishers, to really 
get consumption happening.

449
00:33:21,620 --> 00:33:27,550
And so that is pretty big on its own and by
doing that, it allows us to also ship something

450
00:33:27,550 --> 00:33:30,300
on the heels of v4, called data farming.

451
00:33:30,300 --> 00:33:34,880
And to summarize, it's sort of an incentive program 
running on this blockchain, incentivize things.

452
00:33:34,880 --> 00:33:36,640
I'll get into that later.

453
00:33:36,640 --> 00:33:39,380
To your question, then though, like, 
what are the other use cases?

454
00:33:39,380 --> 00:33:44,490
So there's, solve rug pulls, data NFTs 
and help the community monetize.

455
00:33:44,490 --> 00:33:55,500
So data NFTs are basically a refinement of what we 
had in Ocean v3 to serve particular more use cases.

456
00:33:55,520 --> 00:34:02,407
So in Ocean v3, what we learned from ascribe
days and so on is, what does it mean to own something?

457
00:34:02,420 --> 00:34:05,170
And the word ownership is really a red herring.

458
00:34:05,170 --> 00:34:06,940
It's sort of like the word consciousness.

459
00:34:06,940 --> 00:34:08,179
What does it mean to be conscious?

460
00:34:08,179 --> 00:34:10,590
Or AI, what does AI mean and stuff?

461
00:34:10,590 --> 00:34:14,800
And I've always found that it's really useful
if you can discover some pragmatic definition,

462
00:34:14,800 --> 00:34:18,520
usually someone else has come up 
with a pragmatic definition.

463
00:34:18,520 --> 00:34:22,227
And also acknowledging that there's always going to 
be many many definitions for any of these things.

464
00:34:22,230 --> 00:34:26,832
You know, there's 20 different definitions for AI, 
there's 20 definitions for consciousness etc.

465
00:34:26,860 --> 00:34:28,240
And there's 20 definitions for NFTs.

466
00:34:28,240 --> 00:34:29,310
That's okay.

467
00:34:29,310 --> 00:34:32,820
So, what is… ownership, actually I should
say too.

468
00:34:32,820 --> 00:34:34,770
So what is a pragmatic definition for ownership?

469
00:34:34,770 --> 00:34:42,881
And over the… one that I've discovered is, a pragmatic 
definition for ownership is a bundle of rights.

470
00:34:42,889 --> 00:34:45,560
To own something is to have 
a particular bundle of rights.

471
00:34:45,560 --> 00:34:50,090
Let me elaborate, so, let's talk about music.

472
00:34:50,090 --> 00:34:57,190
Michael Jackson, he, I guess I'm under a Michael
Jackson kick today, so he wrote the songs

473
00:34:57,190 --> 00:35:06,380
around the Thriller album and then he recorded
them and once he recorded them, he sold those

474
00:35:06,380 --> 00:35:12,750
master recordings and some associated rights
around that to a big music label, I forget which.

475
00:35:13,750 --> 00:35:15,350
Let's say Universal for fun.

476
00:35:15,350 --> 00:35:22,700
And then Universal, then licensed those, they
manufactured CDs etc and then people could

477
00:35:22,700 --> 00:35:25,290
go and buy a CD and listen to them.

478
00:35:25,290 --> 00:35:30,996
Actually back then it wasn't even CDs, it
was tapes and LPs and then radio stations too.

479
00:35:31,010 --> 00:35:38,670
So, if I bought a tape from Michael Jackson
Thriller in the year 1987, do I own Thriller?

480
00:35:38,670 --> 00:35:42,369
Or does Universal own Thriller?

481
00:35:42,369 --> 00:35:46,320
So the word ownership, it's kind of meaningless,
because well, Universal owns Thriller, if

482
00:35:46,320 --> 00:35:50,020
you define it in a certain way or I own Thriller
if you define it in a certain way etc, or

483
00:35:50,020 --> 00:35:51,440
the radio station owns Thriller.

484
00:35:51,440 --> 00:35:56,600
What is more productive, is to say 
what rights does each party have.

485
00:35:56,600 --> 00:36:03,770
So Universal has the right to 
publish tapes and sell those.

486
00:36:03,770 --> 00:36:07,810
Universal has the right to publish LPs.

487
00:36:07,810 --> 00:36:13,080
Universal has the right to sublet, to give
licenses to radio stations to play Michael

488
00:36:13,080 --> 00:36:15,730
Jackson songs and the Thriller album.

489
00:36:15,730 --> 00:36:21,600
So those are some of the rights that Universal
has and for that set of rights it paid a large

490
00:36:21,600 --> 00:36:26,870
fee, millions of dollars for 
the Michael Jackson master etc.

491
00:36:26,870 --> 00:36:31,280
And yeah, it probably wasn't Universal, 
I remember Michael Jackson had his own company

492
00:36:31,280 --> 00:36:34,480
for a while called Apple Recordings, nothing
to do with Apple the company.

493
00:36:34,480 --> 00:36:38,030
And then they were sold and stuff, but, I'm
just using that as an example of course.

494
00:36:38,030 --> 00:36:39,030
Okay.

495
00:36:39,030 --> 00:36:43,441
So, and then myself, if I buy a tape from
Michael Jackson, Thriller, I have the right

496
00:36:43,441 --> 00:36:44,970
to listen to that myself.

497
00:36:44,970 --> 00:36:49,360
I might and depending on what tape I buy I
might not even have the right to resell that

498
00:36:49,360 --> 00:36:52,800
tape, although there is, you know, 
small secondary markets for tapes.

499
00:36:52,800 --> 00:36:57,500
So it's a similar thing with 
data and with digital art.

500
00:36:57,500 --> 00:37:01,550
So with ascribe, when we did digital art,
it's like, okay, when you're publishing that

501
00:37:01,550 --> 00:37:05,600
initial work, you are claiming that you have
all the rights around it, either copyright,

502
00:37:05,600 --> 00:37:11,596
which is the main thing you get as a creator, which means 
all other rights derive from that baseline copyright.

503
00:37:11,610 --> 00:37:15,060
So you either have copyright, or some sort
of exclusive license against that copyrighted

504
00:37:15,060 --> 00:37:16,440
work that no one else can do anything.

505
00:37:16,440 --> 00:37:19,040
So you have all the rights to sublicense.

506
00:37:19,040 --> 00:37:26,830
And so, when you're publishing a digital work
in ascribe, you claim that and then in ascribe

507
00:37:26,830 --> 00:37:33,790
there is, different editions, each basically
is a sublicense to be able to buy and sell

508
00:37:33,790 --> 00:37:35,220
that sublicense to others.

509
00:37:35,220 --> 00:37:37,020
So edition one, edition two etc.

510
00:37:37,020 --> 00:37:41,140
And I could sell to a museum, 
museum A can sell to museum B etc.

511
00:37:41,140 --> 00:37:44,730
And they have the right to publicly display,
they have their right to resell basically.

512
00:37:44,730 --> 00:37:47,560
And it's a similar thing for data.

513
00:37:47,560 --> 00:37:55,420
So when I publish my CSV file, holding my
DNA, then I am claiming that I have copyright

514
00:37:55,420 --> 00:38:02,280
on that and I do, being a human being, I have
copyright on my DNA, unless some nefarious

515
00:38:02,280 --> 00:38:07,970
person has somehow asserted that against me
and there are games like that, by the way,

516
00:38:07,970 --> 00:38:10,570
and I'm looking at you 23andMe, anyway.

517
00:38:10,570 --> 00:38:12,630
That was funny.

518
00:38:12,630 --> 00:38:18,360
And yeah, no, actually as a quick aside this
kind of points to the problem of data.

519
00:38:18,360 --> 00:38:23,440
So 23andMe, I signed up for them many years
ago, I got them to do a DNA test on my data

520
00:38:23,440 --> 00:38:26,520
and they promised, promised, promised they
would never ever, ever sell my data.

521
00:38:26,520 --> 00:38:30,910
I'm like, great, I'll learn some stuff about
me and then a few years ago, they sent an

522
00:38:30,910 --> 00:38:35,146
email to everyone, hey we're changing our
terms and conditions, can you please check here?

523
00:38:35,700 --> 00:38:39,060
And they didn't say what they're changing,
but basically what they changed, if you looked

524
00:38:39,060 --> 00:38:43,020
at the news reports at the time, or you read
the new updates, they basically said, we're

525
00:38:43,020 --> 00:38:45,230
going to have the right to 
sell your data from now on.

526
00:38:45,230 --> 00:38:49,320
And you have like three 
weeks to comply basically.

527
00:38:49,320 --> 00:38:50,910
And so, I'm like, no way.

528
00:38:50,910 --> 00:38:51,910
So I basically…

529
00:38:51,910 --> 00:38:52,910
That's scary.

530
00:38:52,910 --> 00:38:57,320
Yeah and basically they discovered that they
couldn't basically get any other business

531
00:38:57,320 --> 00:39:01,250
models at the time, so they're like, let's
sell this data that we don't really own, but

532
00:39:01,250 --> 00:39:04,950
we're going to buy, basically try 
to sneak it through and they did.

533
00:39:04,950 --> 00:39:07,920
So 23andMe is now selling your data.

534
00:39:07,920 --> 00:39:12,160
And to me it's like that is yet 
another reason we're doing Ocean.

535
00:39:12,160 --> 00:39:19,700
As an example and what's crazy, I think GDPR
was already there and so I filed a report

536
00:39:19,700 --> 00:39:24,529
saying, I would like to be able to download
my data please and then I want to shut down my account.

537
00:39:24,529 --> 00:39:30,068
It took them several weeks, I think like four or five 
weeks to line it up for me to be able to download the data.

538
00:39:30,080 --> 00:39:33,350
And by the time I had my data downloaded,
it had already crossed the threshold into

539
00:39:33,350 --> 00:39:37,180
them being able to sell my data, 
which is like, super uncool too.

540
00:39:37,180 --> 00:39:39,410
So I couldn't even download 
data that I own myself.

541
00:39:39,410 --> 00:39:40,410
Oh, God.

542
00:39:41,410 --> 00:39:44,570
Yeah. So my data is probably now held by a bunch
of big pharma companies etc, throughout the

543
00:39:44,570 --> 00:39:52,560
world, even though it was, really, there's
obviously a very ambiguous gray area there

544
00:39:52,560 --> 00:39:54,350
about what is right or not.

545
00:39:54,350 --> 00:39:57,670
And what is legal and not, so anyway, that's
an example.

546
00:39:57,670 --> 00:40:02,290
So going back to my 
example here, with ownership.

547
00:40:02,290 --> 00:40:08,330
So I publish the DNA data that I own or I
should have all the rights to and as I'm claiming

548
00:40:08,330 --> 00:40:14,230
that I have the rights to that and then I
publish one of these data tokens that says

549
00:40:14,230 --> 00:40:19,369
like, when I'm publishing it, it creates 
a data token, this fungible thing.

550
00:40:19,369 --> 00:40:23,131
And then everyone's getting licenses to that,
whenever I send them, the licenses, or it

551
00:40:23,131 --> 00:40:24,560
can be compute-to-data.

552
00:40:24,560 --> 00:40:26,220
So that's basically the basic idea.

553
00:40:26,220 --> 00:40:31,290
Now what Ocean v4 does is, saying when you
publish just this claim initially that is

554
00:40:31,290 --> 00:40:36,340
a single NFT, it's a non-fungible token, because
you can't make copyright fungible, there's

555
00:40:36,340 --> 00:40:38,560
only one entity that has control.

556
00:40:38,560 --> 00:40:39,560
Awesome.

557
00:40:39,560 --> 00:40:44,180
And so we're gonna explicitly have it where
it's represented as a token, rather than sort

558
00:40:44,180 --> 00:40:46,570
of implicitly with whoever published the contract.

559
00:40:46,570 --> 00:40:47,970
And that's what Ocean v4 does.

560
00:40:47,970 --> 00:40:53,785
But what that also does and then you can still have 
the sublicenses against that, the fungible tokens.

561
00:40:53,810 --> 00:40:59,800
And so basically, Ocean v4 pulls this apart,
it's explicitly representing who has copyright

562
00:40:59,800 --> 00:41:04,900
and making that separate from who has licenses
and then, by explicitly representing his copyright

563
00:41:04,900 --> 00:41:10,000
or the IP, what you can do is, before you
even publish any licenses or anything, you

564
00:41:10,000 --> 00:41:13,160
can basically start accruing 
more and more value to that.

565
00:41:13,160 --> 00:41:20,240
So you can be doing research on drug design
or otherwise, making a better dataset, you've

566
00:41:20,240 --> 00:41:23,280
already claimed that initial thing, but 
you keep improving and improving it.

567
00:41:23,280 --> 00:41:30,655
And then, you could, some fungible sublicense
against it and that's a first set of ERC20 licenses.

568
00:41:30,680 --> 00:41:33,720
And then, you can even make a second and a
third, maybe one license is to use for a day

569
00:41:33,720 --> 00:41:36,870
and other licenses to use for 
a month, another one's for a year.

570
00:41:36,870 --> 00:41:39,260
And maybe another one is 
for compute-to-data against it.

571
00:41:39,260 --> 00:41:43,580
And all of those can be against that 
same single base piece of IP.

572
00:41:43,580 --> 00:41:47,401
So there's a bunch of use cases there, another
big use case is and this is a big reason we

573
00:41:47,401 --> 00:41:49,800
did it now versus a year or two ago.

574
00:41:49,800 --> 00:41:56,270
In 2021 it's pretty clear, NFTs took off right,
mostly NFTs for digital art, which makes me

575
00:41:56,270 --> 00:41:58,490
very happy like artists are getting paid.

576
00:41:58,490 --> 00:41:59,500
Hooray!

577
00:41:59,500 --> 00:42:06,369
But also, what benefit we realized, okay,
as because this is blowing up, then the tooling

578
00:42:06,369 --> 00:42:08,660
around NFTs is exploding too.

579
00:42:08,660 --> 00:42:13,300
So there's way more wallets that have really
good support for these NFTs, these non-fungible

580
00:42:13,300 --> 00:42:17,830
tokens, there's way more exchanges that have
buying and selling, the Open Seas of the world,

581
00:42:17,830 --> 00:42:19,900
even Binance and others have exchanges for it now.

582
00:42:19,900 --> 00:42:20,950
So we're like, great, cool.

583
00:42:20,950 --> 00:42:26,090
So, if we actually explicitly represent copyright
as this NFT then, now there's really great

584
00:42:26,090 --> 00:42:27,620
wallet support for this too.

585
00:42:27,620 --> 00:42:33,751
So data NFTs have now, thanks to the explosion of NFTs, 
they have great support and wallets exchanges etc.

586
00:42:33,780 --> 00:42:36,790
So that's the summary of that 
and many many benefits of course.

587
00:42:36,790 --> 00:42:40,190
The final one is, help the community 
monetize, it's just that.

588
00:42:40,190 --> 00:42:47,332
In v3, if you're running a market, you could only 
get 0.1 cut of the, consume volume, of the sales.

589
00:42:47,350 --> 00:42:51,050
In v4, you can set whatever percentage you
want and not just for consume, but also for

590
00:42:51,050 --> 00:42:52,530
swap and for publish.

591
00:42:52,530 --> 00:42:56,020
So basically it makes it easier for more 
people to create their own marketplaces.

592
00:42:56,020 --> 00:42:58,720
And we have, there’s about 10 teams or so
making their own marketplaces, instead of

593
00:42:58,720 --> 00:43:02,070
using Ocean market, you can create your own.

594
00:43:02,070 --> 00:43:08,920
I can't believe so much has happened since
v3 last time when we interviewed Bruce.

595
00:43:08,920 --> 00:43:14,990
So, I see a lot of things are happening for
Ocean and it's great to see that one day all

596
00:43:14,990 --> 00:43:20,520
these use cases will have mass 
adoption, at least the idea of it.

597
00:43:20,520 --> 00:43:29,060
So within all this, there's also a lot of
noise around Ocean DAO and particularly we

598
00:43:29,060 --> 00:43:34,210
have spoken about DAOs also in the past in
one episode with Alex I think, it was 3rd, 4th.

599
00:43:35,210 --> 00:43:39,460
So tell us the entire process 
of setting up Ocean DAO.

600
00:43:39,460 --> 00:43:47,558
Where you are right now, what are your expectations
out of it and how's the whole experience going with that?

601
00:43:47,570 --> 00:43:48,640
Yeah.

602
00:43:48,640 --> 00:43:49,960
Happy to share.

603
00:43:49,960 --> 00:43:59,550
So, at a 10.000 review, Ocean DAO is a critical
piece of Ocean decentralizing and it is the

604
00:43:59,550 --> 00:44:04,570
foundation of, sort of a fully 
decentralized Ocean ecosystem.

605
00:44:04,570 --> 00:44:06,477
So let's unpack that.

606
00:44:09,140 --> 00:44:14,710
So over time, we keep iterating with our users
and with our community and learning about

607
00:44:14,710 --> 00:44:18,450
what makes sense and what doesn't make sense
and so on and as we were going down the path

608
00:44:18,450 --> 00:44:23,490
of designing v3, we saw that we also had an
opportunity, not just to simplify how we did

609
00:44:23,490 --> 00:44:29,410
data sharing and all that, but to improve
the macro level token design of Ocean itself,

610
00:44:29,410 --> 00:44:34,850
towards long-term sustainability etc, based
on observing learnings of many token projects

611
00:44:34,850 --> 00:44:37,109
over the previous couple years.

612
00:44:37,109 --> 00:44:40,760
And we also saw, we were like okay, well,
what pattern makes sense as sort of this macro

613
00:44:40,760 --> 00:44:43,490
level design for long-term sustainability.

614
00:44:43,490 --> 00:44:50,988
And if you think about it a DAO is sort of like 
a huge co-op, that's one way to think about it.

615
00:44:51,010 --> 00:44:54,350
And most DAOs you see now, they're kind of
like Dunbar DAOs, they're maybe scaled to

616
00:44:54,350 --> 00:44:58,820
150 people, but you can have co-ops, that
scale to 10.000 or 100.000 people and going

617
00:44:58,820 --> 00:45:04,260
back to Saskatchewan growing up, Saskatchewan
Wheat Pool had tens of thousands of farmers,

618
00:45:04,260 --> 00:45:05,910
it had scaled.

619
00:45:05,910 --> 00:45:12,340
It had imposed a little bit of hierarchy,
it had 300 elected delegates, who would meet,

620
00:45:12,340 --> 00:45:16,130
probably 30 times a year to meet and plan
things and then there was an executive that

621
00:45:16,130 --> 00:45:18,680
was elected from the delegates etc.

622
00:45:18,680 --> 00:45:22,910
And then, all the members, all the 
different farmers could vote etc.

623
00:45:22,910 --> 00:45:25,780
And this was a co-op, this wasn't 
a company per se, it was a co-op.

624
00:45:25,780 --> 00:45:30,510
So each, a member, owned a share like a piece
of this co-op, but it was basically serving

625
00:45:30,510 --> 00:45:31,750
its members.

626
00:45:31,750 --> 00:45:37,780
So we can think of DAOs like that too and
communities around DAOs and so on.

627
00:45:37,780 --> 00:45:43,600
And so you can even view right now Ocean itself,
you can view as some co-op, but it's very

628
00:45:43,600 --> 00:45:48,170
loosely structured, because it's just the
Ocean token holders and the Ocean DAO itself

629
00:45:48,170 --> 00:45:53,750
has a piece of this, but then you can ask,
okay, how can you leverage the learnings of

630
00:45:53,750 --> 00:46:01,851
co-ops that have scaled and the learnings
of other sort of organizations in the last

631
00:46:01,851 --> 00:46:03,830
few years towards Ocean?

632
00:46:03,830 --> 00:46:08,930
So there's another learning, 
too and that is co-ops.

633
00:46:08,930 --> 00:46:12,790
If you're a co-op, you're allowed 
to make money and commons too.

634
00:46:12,790 --> 00:46:14,990
Like a common, there's 
sometimes a misconception.

635
00:46:14,990 --> 00:46:20,945
The idea of a commons isn't necessarily something
that is fully public, it's actually serving a community.

636
00:46:20,970 --> 00:46:25,101
Like this is Elinor Ostrom, who won a Nobel
prize, around researching commons and so on.

637
00:46:25,101 --> 00:46:30,109
So it might be serving a group of fishermen
off the coast of Tahiti, or it might be serving

638
00:46:30,109 --> 00:46:34,590
a group of tens of thousands of farmers helping
them to market and distribute grain.

639
00:46:34,590 --> 00:46:44,035
So the Saskatchewan Wheat Pool is a co-op, a commons 
to serve farmers and it's accessible to them etc.

640
00:46:44,040 --> 00:46:46,900
But it's okay for co-op commons 
or co-ops to make money.

641
00:46:46,900 --> 00:46:51,740
Looking around, what other businesses make
tons of money and are sustainable and which

642
00:46:51,740 --> 00:46:56,760
ones are growing and I've been a long time
admirer of Amazon in their ability to grow

643
00:46:56,760 --> 00:46:58,960
and discover new markets.

644
00:46:58,960 --> 00:47:05,600
And obviously it has its negative flaws, but
as a design, like Jeff Bezos is an amazing

645
00:47:05,600 --> 00:47:08,920
token designer basically or 
dynamical system designer.

646
00:47:08,920 --> 00:47:16,460
And basically Amazon has this flywheel at
the heart of it, which is towards growth and

647
00:47:16,460 --> 00:47:23,090
how it works is, if they have more selection
of products in the market, then more people

648
00:47:23,090 --> 00:47:27,040
will come to the market, which means more
revenue coming from the market and more revenue

649
00:47:27,040 --> 00:47:30,700
means more sellers will sell in the market,
which means better selection, which means

650
00:47:30,700 --> 00:47:33,560
more people coming and the loop 
goes round and round and round.

651
00:47:33,560 --> 00:47:34,900
This is assuming you have good discovery.

652
00:47:34,900 --> 00:47:37,250
But basically, it's this engine of growths.

653
00:47:37,250 --> 00:47:42,810
So once again, if you have lots of items in
the market, you can't help, but sell more,

654
00:47:42,810 --> 00:47:48,740
if you can't help but sell more, you can't
help but have more people selling on your

655
00:47:48,740 --> 00:47:52,870
market and if you have more people selling
your market, you can't help but have more variety.

656
00:47:52,900 --> 00:47:58,476
And if you have more variety and good discovery tools, 
you can't help but sell more and it loops round and round.

657
00:47:58,480 --> 00:48:04,740
And this concept was, Jeff Bezos, as he was
designing Amazon, he took the idea from Jim

658
00:48:04,740 --> 00:48:06,780
Collins, the author of Good to Great and so on.

659
00:48:06,780 --> 00:48:10,930
And loved the concept so much, that he put
Jim Collins on his board and Jim has been

660
00:48:10,930 --> 00:48:13,580
on that board for like two decades now.

661
00:48:13,580 --> 00:48:17,000
And that's basically how Amazon grew 
and grew and grew over the years.

662
00:48:17,000 --> 00:48:21,910
And it's also the model for it to sort of
expand into other businesses, because Amazon

663
00:48:21,910 --> 00:48:26,240
is willing to learn with this 
underlying dynamical model.

664
00:48:26,240 --> 00:48:31,420
And so the dynamical model for Ocean is similar
actually, but targeted towards this massive

665
00:48:31,420 --> 00:48:38,290
commons around this mission of unlocking an
open data economy, while preserving privacy,

666
00:48:38,290 --> 00:48:39,740
subject to that mission.

667
00:48:39,740 --> 00:48:41,190
So what does this mean?

668
00:48:41,190 --> 00:48:45,369
We want there to be tons and tons of data
available in the Ocean ecosystem, on Ocean

669
00:48:45,369 --> 00:48:48,520
Market and a thousand other markets.

670
00:48:48,520 --> 00:48:53,540
And if you have more of this data available,
from a marketplace perspective, you can't

671
00:48:53,540 --> 00:48:56,290
help, but have more people 
supplying and it growing etc.

672
00:48:56,290 --> 00:49:01,359
But then, also in terms of the growth engine,
the more sales you have on it, if you take

673
00:49:01,359 --> 00:49:06,490
a cut of those sales and you feed those towards
the community for growth, like, where the

674
00:49:06,490 --> 00:49:09,070
community itself finds ways 
to grow, then it loops around.

675
00:49:09,070 --> 00:49:11,090
And this is exactly what Amazon is doing.

676
00:49:11,090 --> 00:49:18,410
Amazon takes a cut of its sales and it takes
that cut and puts it into R&D etc to grow faster.

677
00:49:19,550 --> 00:49:23,609
And so, this is sort of part of the playbook
from Amazon that we're using for Ocean and

678
00:49:23,609 --> 00:49:25,480
that's the macro system level design.

679
00:49:25,480 --> 00:49:30,390
So it's taking this idea of the Amazon flywheel
and turning it into something we call the

680
00:49:30,390 --> 00:49:32,480
web3 sustainability loop.

681
00:49:32,480 --> 00:49:34,980
And then, we've applied that to Ocean.

682
00:49:34,980 --> 00:49:42,330
And if you think about that then so, as there's
more and more sales happening on Ocean market

683
00:49:42,330 --> 00:49:46,250
and other markets, then there's more and 
more money flowing to the community.

684
00:49:46,250 --> 00:49:50,521
How do you allocate that money flowing to the 
community to actually projects that help to grow?

685
00:49:51,170 --> 00:49:52,340
In a scalable fashion.

686
00:49:52,340 --> 00:49:53,340
That is the big question.

687
00:49:53,340 --> 00:49:57,760
Amazon does it with Jeff Bezos and his lieutenants
and they have basically a resource allocation

688
00:49:57,760 --> 00:49:59,849
algorithm that they designed.

689
00:49:59,849 --> 00:50:04,250
So what would the resource allocation 
algorithm look like for Ocean?

690
00:50:04,250 --> 00:50:10,630
And the answer is, Ocean DAO 
and other related items.

691
00:50:10,630 --> 00:50:15,460
So Ocean DAO basically says, okay, a bunch
of people can propose different ways of how

692
00:50:15,460 --> 00:50:19,590
Ocean can grow and then the community can
say okay, well I'm going to vote on these,

693
00:50:19,590 --> 00:50:22,490
on which ones I think will 
help, will do the best.

694
00:50:22,490 --> 00:50:28,860
And so the proposals that have the most votes,
then they get selected and they get funding.

695
00:50:28,860 --> 00:50:32,460
And the other projects, people can pursue
them, but they just won't get funding.

696
00:50:32,460 --> 00:50:38,602
And so in that way and incentives are aligned, because 
you're voting as a function of how much Ocean you hold.

697
00:50:38,630 --> 00:50:43,620
So you don't want your Ocean to be spent on
projects that don't help to fundamentally

698
00:50:43,620 --> 00:50:47,170
help the health of Ocean.

699
00:50:47,170 --> 00:50:49,710
And so basically it's aligned that way.

700
00:50:49,710 --> 00:50:51,540
And so that's what Ocean DAO is about.

701
00:50:51,540 --> 00:51:00,060
And then it started off just as a very streamlined
grants DAO just around that, around driving

702
00:51:00,060 --> 00:51:03,660
and trying to ensure that the ROI is greater
than one such that you have this snowball

703
00:51:03,660 --> 00:51:06,110
effect, it just grows.

704
00:51:06,110 --> 00:51:09,720
Sort of an update and by the way, with that,
it's been running for about a year.

705
00:51:09,720 --> 00:51:15,380
It started off the first month, 
it had 25.000 US dollars worth of grants.

706
00:51:15,380 --> 00:51:18,470
These days it has about 500.000 dollars 
worth of grants, so it's grown a lot.

707
00:51:18,470 --> 00:51:22,480
There's about 100 teams that have got grants.

708
00:51:22,480 --> 00:51:26,440
And yeah, there's been basically a whole ecosystem
that has flourished around it and a whole

709
00:51:26,440 --> 00:51:30,990
community and that to me is like a big part
of the beating heart of the Ocean ecosystem

710
00:51:30,990 --> 00:51:33,020
now, propelled by the DAO.

711
00:51:33,020 --> 00:51:37,760
Now we've discovered that okay, the DAO as
is, has been pretty good, how can we make

712
00:51:37,760 --> 00:51:42,950
it even more accessible, a little less harsh,
a little more around growing community etc.

713
00:51:42,950 --> 00:51:48,440
So instead of just saying ROI greater than
one, focusing on that, we're saying okay,

714
00:51:48,440 --> 00:51:52,140
for any given project how much 
does it help to grow Ocean?

715
00:51:52,140 --> 00:51:53,720
How viable is the project?

716
00:51:53,720 --> 00:51:57,490
But also, how much is the team 
doing to help grow community?

717
00:51:57,490 --> 00:52:01,940
And how much does the project 
itself help to grow community?

718
00:52:01,940 --> 00:52:06,380
And so, we're using these factors as sort
of an update to the criteria to make Ocean

719
00:52:06,380 --> 00:52:08,869
DAO a little softer and gentler.

720
00:52:08,869 --> 00:52:12,810
And then, in combination with that, we have
just introduced the idea of working groups.

721
00:52:12,810 --> 00:52:17,640
So we've started with five working groups
and basically it's little modules, little

722
00:52:17,640 --> 00:52:21,660
pieces of people working on aspects 
of Ocean DAO that will extend.

723
00:52:21,660 --> 00:52:24,210
So there's a group working 
on the roadmap for Ocean DAO.

724
00:52:24,210 --> 00:52:30,190
There's a group working on what sort of projects
do we want to earmark to sort of incentivize

725
00:52:30,190 --> 00:52:36,754
for, do we want to have an incentive to have
a first class integration with Arweave for example.

726
00:52:36,780 --> 00:52:39,590
And there's other projects around driving,
data consumed volume and so on.

727
00:52:39,590 --> 00:52:45,990
So, basically there's this new concept of
working groups and it sort of runs complementary

728
00:52:45,990 --> 00:52:49,960
to the grounds and over time this working
group, these working groups will grow from

729
00:52:49,960 --> 00:52:53,980
like 5 working groups 
to 10 then 15 and so on.

730
00:52:53,980 --> 00:52:56,180
So that's Ocean DAO basically.

731
00:52:56,180 --> 00:53:01,190
And by the way, as the working groups grow
in number and in size for each working group,

732
00:53:01,190 --> 00:53:04,030
that is how Ocean itself gets 
more and more decentralized.

733
00:53:04,030 --> 00:53:09,490
Because it means these teams can get grants,
but also people that are in the teams as well

734
00:53:09,490 --> 00:53:12,840
as others in the community, can participate
in these working groups to basically help

735
00:53:12,840 --> 00:53:17,140
to grow, Ocean ecosystem in various ways 
that suits their skills and passion.

736
00:53:17,140 --> 00:53:22,440
Yeah, so I'm just, as you're speaking, I'm
just soaking in all the knowledge and I'm

737
00:53:22,440 --> 00:53:27,040
thinking okay, it looks like a lot of different
projects when you look from the outside, but

738
00:53:27,040 --> 00:53:32,900
actually it's also beautifully linked that
it would just not exist without the other,

739
00:53:32,900 --> 00:53:37,320
as we spoke about all these initiatives.

740
00:53:37,320 --> 00:53:42,270
And Ocean DAO I mean it's a win-win 
for everybody, seems like so.

741
00:53:42,270 --> 00:53:48,760
You said it's been over a year and you've
also raised, like the funding.

742
00:53:48,760 --> 00:53:55,510
So how big is the community per se you could
say or how has it been growing?

743
00:53:55,510 --> 00:53:57,830
Is there a number you could share with us?

744
00:53:57,830 --> 00:54:05,809
Yeah, so two things on the question of raising the funding, 
like so, a wonderful, going back to blockchain benefits.

745
00:54:05,810 --> 00:54:08,870
Decentralized immutable assets and incentives.

746
00:54:08,870 --> 00:54:15,030
So, when we were designing the Ocean token,
back in the day before the token launch, we

747
00:54:15,030 --> 00:54:21,430
said let's hold back the majority of tokens
for the community to drive growth.

748
00:54:21,430 --> 00:54:27,720
And so we've always had 51% held back just
for that, plus within Ocean Protocol Foundation

749
00:54:27,720 --> 00:54:32,500
we've had on the order of 15-20% also sitting
in there, so it's on the order of 65-70% of

750
00:54:32,500 --> 00:54:38,591
the Ocean token supply is basically earmarked
for deployment to the community and we have

751
00:54:38,591 --> 00:54:42,840
been deploying as aggressively as possible
and scaling up as we can go.

752
00:54:42,840 --> 00:54:49,420
So Ocean DAO gets a chunk of that, basically
about a quarter of that, so we announced that

753
00:54:49,420 --> 00:54:56,980
the number for that, which is more than 100
million dollars worth of funding to teams,

754
00:54:56,980 --> 00:54:59,320
over the next number of years.

755
00:54:59,320 --> 00:55:04,968
And so, that's pretty generous on its own and 
then data farming, which is, I'll just elaborate here.

756
00:55:04,980 --> 00:55:09,120
It's liquidity mining, it's basically an incentive
program to help encourage people to publish

757
00:55:09,120 --> 00:55:16,547
datasets that get consumed and to encourage
people to stake in datasets towards getting consumed.

758
00:55:16,560 --> 00:55:19,940
It's all basically towards driving consumed
volume, which is where the rubber hits the

759
00:55:19,940 --> 00:55:23,609
road for value creation in Ocean.

760
00:55:23,609 --> 00:55:30,170
A dataset gets published and someone else
buys it and then that buyer consumes it.

761
00:55:30,170 --> 00:55:32,630
When they're consuming it, 
they're using it to create value.

762
00:55:32,630 --> 00:55:37,339
Maybe it's to make predictions, predicting
the stock market, or maybe it's to make predictions

763
00:55:37,339 --> 00:55:43,474
for predicting cancer or otherwise, but that's where the 
value capture happens is when the dataset is being consumed.

764
00:55:43,500 --> 00:55:49,369
And that's sort of a key performance indicator
for Ocean overall, a metric to optimize for.

765
00:55:49,369 --> 00:55:51,580
So, I'll answer your question, don't worry.

766
00:55:51,580 --> 00:55:55,240
So that's basically in terms of money allocated.

767
00:55:55,240 --> 00:56:00,450
The majority of Ocean tokens are allocated
to growth over time and Ocean DAO and data

768
00:56:00,450 --> 00:56:05,109
farming etc are the key vehicles by which
we do that, they're complementary as well,

769
00:56:05,109 --> 00:56:10,260
the DAO, there's much more subjective human
judgment on who's getting what based on their

770
00:56:10,260 --> 00:56:15,400
track record etc, whereas the data farming
is very objective, it's measurable just the

771
00:56:15,400 --> 00:56:20,811
same way that Bitcoin is very objective, it's like you're 
either contributing to security or not. Bitcoin knows.

772
00:56:21,820 --> 00:56:33,090
And then, to your question then, on specific numbers for 
the Ocean DAO community and so on, let's see here.

773
00:56:33,100 --> 00:56:38,359
So there's about 100 teams that have got funding
in Ocean DAO, as of October 6 there was 80

774
00:56:38,359 --> 00:56:41,040
plus so that's why I'm guessing a hundred
plus now, because there's one more round.

775
00:56:41,040 --> 00:56:48,360
There's about 10 teams that are building third-party
data markets, some of these larger projects,

776
00:56:48,360 --> 00:56:49,720
publicly traded companies like WIseKey.

777
00:56:49,720 --> 00:56:54,810
Some of them, more small startups and stuff.

778
00:56:54,810 --> 00:57:01,040
There's several teams that have some product
contracts with Ocean to build very specific

779
00:57:01,040 --> 00:57:05,940
functionality such as Raven Protocol 
for decentralized federated learning and more.

780
00:57:05,940 --> 00:57:11,480
And then within Ocean DAO itself on those
numbers I'm just going to pull up some numbers

781
00:57:11,480 --> 00:57:15,799
from a month ago, because I don't know if I have 
a more recent one, so just give me a second here.

782
00:57:15,830 --> 00:57:16,830
Sure.

783
00:57:16,830 --> 00:57:20,160
So this is numbers from October 6th or so.

784
00:57:20,160 --> 00:57:27,830
At the time there was a 947 
different wallets that had voted.

785
00:57:27,830 --> 00:57:29,810
178 proposals submitted.

786
00:57:29,810 --> 00:57:34,970
120 million Ocean tokens that have been voted.

787
00:57:34,970 --> 00:57:37,040
And 40 community town halls held.

788
00:57:37,040 --> 00:57:41,910
So those are some numbers, in terms of the
people in the ecosystem, the town halls typically

789
00:57:41,910 --> 00:57:46,690
have 15 to 35 or 50 even people 
show up at any given week.

790
00:57:46,690 --> 00:57:51,040
They are every Wednesday at 5 PM Berlin time.

791
00:57:51,040 --> 00:57:57,640
And if you go into the Ocean Discord, there's,
I don't even know how many, but there's many

792
00:57:57,640 --> 00:58:01,940
active channels now, the Telegram is even
more the Twitter you can look at the Twitter

793
00:58:01,940 --> 00:58:05,119
follower account all that, it's more than
100.000 for example there.

794
00:58:05,119 --> 00:58:08,370
So there's social media metrics, but even
more interesting than social media metrics

795
00:58:08,370 --> 00:58:12,270
is really what is the number 
of teams building the ecosystem.

796
00:58:12,270 --> 00:58:17,180
So we're on the order of 100 teams that have
got grants, of those what fraction is active.

797
00:58:17,180 --> 00:58:22,299
There's probably at least 20 or 30 that are really truly 
active in a really great way building really great projects.

798
00:58:22,320 --> 00:58:25,619
Maybe it's higher, but I'm trying 
to be a bit conservative here.

799
00:58:25,619 --> 00:58:27,480
So yeah, that's kind of where Ocean's at.

800
00:58:27,480 --> 00:58:28,480
Yeah.

801
00:58:28,480 --> 00:58:32,720
You compare it to a year ago, a year ago maybe
there was, three or five teams, so, it's really

802
00:58:32,720 --> 00:58:37,840
grown in the last year and the big driver
of that has been the vehicle of Ocean DAO.

803
00:58:37,840 --> 00:58:40,410
Really grown, okay.

804
00:58:40,410 --> 00:58:46,130
So I think we just have like six minutes,
but I have one follow-up on Ocean DAO.

805
00:58:46,130 --> 00:58:53,140
So how is it really decided that which projects
get funded or what is your voting system that

806
00:58:53,140 --> 00:58:56,980
goes around the Ocean DAO?

807
00:58:56,980 --> 00:59:05,060
Yeah, so, anyone can submit a proposal and
then depending, if you haven't submitted a

808
00:59:05,060 --> 00:59:10,050
proposal before, there's a funding limit, but 
if you've submitted proposals and successfully

809
00:59:10,050 --> 00:59:16,130
completed a past project, the funding can
be as high as 35000 euros, sorry dollars.

810
00:59:16,130 --> 00:59:18,440
Any given month, dollars worth of Ocean.

811
00:59:18,440 --> 00:59:21,720
And so we have several teams that are at that
level where they're making proposals on the

812
00:59:21,720 --> 00:59:26,390
order of 35000 US dollars and they 
can come back monthly if they want.

813
00:59:26,390 --> 00:59:34,050
And so anyone can submit and then how it's
decided is voting and it's a monthly cadence

814
00:59:34,050 --> 00:59:40,190
so right now, yeah, people are submitting
projects for the next round, which is R12

815
00:59:40,190 --> 00:59:43,410
and the voting for that 
will be in early December.

816
00:59:43,410 --> 00:59:46,849
And the voting is with Ocean token.

817
00:59:46,849 --> 00:59:54,490
So we have started out 
with one token, one vote.

818
00:59:54,490 --> 01:00:01,331
And initially it was one token, one vote and every given, 
every different project, you would vote differently.

819
01:00:01,340 --> 01:00:09,170
We've recently tweaked it, where now, you
can only spend that one token to vote on any

820
01:00:09,170 --> 01:00:14,380
one of the projects that have applied, so
if there's 20 projects that have applied,

821
01:00:14,380 --> 01:00:17,930
then you can only allocate that token vote
in one of those places, so if I've got 100

822
01:00:17,930 --> 01:00:23,520
tokens to vote, maybe I'll vote 20 yes votes
to project 1, 20 no votes to project 2 and

823
01:00:23,520 --> 01:00:25,330
60 yes votes to project 3.

824
01:00:25,330 --> 01:00:28,490
And that helps people to focus on which 
projects they care the most about.

825
01:00:28,490 --> 01:00:35,010
And now what we also see is that in governance
there's this long-standing question.

826
01:00:35,010 --> 01:00:41,330
There's this democratic ideal, which is one
human one vote and that's really nice, but

827
01:00:41,330 --> 01:00:43,240
it doesn't account for any skin in the game.

828
01:00:43,240 --> 01:00:46,660
What if someone has just one token and just
joined in the Ocean community yesterday.

829
01:00:46,660 --> 01:00:51,748
Should they have the same vote as someone who's really 
passionate about Ocean and owns a million tokens?

830
01:00:51,770 --> 01:00:54,150
So, but that's the democratic ideal.

831
01:00:54,150 --> 01:01:00,357
The flip side is, they're sort of the shareholder ideal or 
the skin in the game ideal, which is one token one vote.

832
01:01:00,380 --> 01:01:06,997
And one token one vote, it has the benefit of yeah, 
skin in the game all that, but neither is perfect.

833
01:01:07,020 --> 01:01:12,520
Ideally, you have some sort of 
way to reconcile these two things.

834
01:01:12,520 --> 01:01:18,050
And one way to reconcile is say okay, let's
allow you to weight your vote based on how

835
01:01:18,050 --> 01:01:20,160
many tokens you have, but not linearly.

836
01:01:20,160 --> 01:01:24,060
So you can scale it with a square 
root or with a log or something.

837
01:01:24,060 --> 01:01:27,089
And if you scale it with a square root 
that's called quadratic voting.

838
01:01:27,089 --> 01:01:31,190
And it's a popular idea and 
we are moving towards that.

839
01:01:31,190 --> 01:01:35,099
The reason we haven't implemented 
it yet is sybil attacks.

840
01:01:35,099 --> 01:01:39,930
Basically, if I, let's say that Ocean introduced
quadratic voting in the last round, well if

841
01:01:39,930 --> 01:01:43,619
I wanna and let's say I've got I don't know,
for fun, 100000 tokens.

842
01:01:43,619 --> 01:01:50,910
If I want to have a really big impact, I would
just split my 100000 tokens into say, a hundred

843
01:01:50,910 --> 01:01:53,740
different wallets and then vote with each
wallet separately and that would have way

844
01:01:53,740 --> 01:01:56,130
more impact than if I'm voting from a single wallet.

845
01:01:56,130 --> 01:02:01,084
So that's called a sybil attack, it's sort of like cloning 
myself a hundred times, attack of the clones if you will.

846
01:02:01,109 --> 01:02:06,470
And so, that's the thing to solve and there
has been really great progress in addressing

847
01:02:06,470 --> 01:02:10,680
sybil attacks from the DAO community over
the last 6 months, 12 months.

848
01:02:10,680 --> 01:02:13,650
And so, we're going to be leveraging 
that progress for Ocean.

849
01:02:13,650 --> 01:02:20,560
So in the meantime it's one token, one vote,
but with directing tokens soon it will reconcile

850
01:02:20,560 --> 01:02:24,950
more this nice trade-off between the democratic
ideal and the skin in the game ideal with

851
01:02:24,950 --> 01:02:27,744
quadratic voting and yeah that'll 
be in the next month or two.

852
01:02:28,612 --> 01:02:34,020
Okay and when does this, 
when's the last round of Ocean DAO?

853
01:02:34,020 --> 01:02:37,770
I mean does that make sense, the question?

854
01:02:37,770 --> 01:02:38,770
It happens every month.

855
01:02:38,770 --> 01:02:39,770
Okay.

856
01:02:39,770 --> 01:02:44,560
And so, every month there's, you know, 
these days, 500.000 Ocean is available.

857
01:02:44,560 --> 01:02:48,339
Each Ocean is worth about a dollar so it's
about half a million dollars worth of Ocean

858
01:02:48,339 --> 01:02:54,400
any given month and that increased, like I
said, from, initially it was 25.000 dollars,

859
01:02:54,400 --> 01:03:02,400
but, we grew it because we want to deploy
capital to teams that want to grow Ocean,

860
01:03:02,400 --> 01:03:04,110
who have this mission in value.

861
01:03:04,110 --> 01:03:09,440
So you can't just apply saying I want money,
it has to be I'd like to have money please,

862
01:03:09,440 --> 01:03:16,230
I subscribe to the mission and vision of Ocean
about unlocking this open data economy and

863
01:03:16,230 --> 01:03:21,570
here's how we think we can add value and maybe
your team that wants to do outreach in India.

864
01:03:21,570 --> 01:03:25,480
Great, then you can apply and get funding
and we have teams like that, we have ones

865
01:03:25,480 --> 01:03:27,160
for India and Japan and otherwise for that.

866
01:03:27,160 --> 01:03:34,778
We have other, you know, we have some people have said, 
hey I want to build a really great mobile first data wallet.

867
01:03:34,800 --> 01:03:36,220
Great, we have people doing that.

868
01:03:36,220 --> 01:03:40,050
We have teams that are adding to the core
with documentation or otherwise.

869
01:03:40,050 --> 01:03:44,280
We have teams that are building 
other integrations and more.

870
01:03:44,280 --> 01:03:49,426
So there's a wide variety of different things people 
can do whether it's technical, or outreach, or otherwise.

871
01:03:50,240 --> 01:03:55,750
And yeah, it's up to half a million and it's
going to keep growing as time goes on.

872
01:03:55,750 --> 01:03:56,750
Okay.

873
01:03:56,750 --> 01:04:02,820
So, I'm sure a lot of people are going to
apply after listening to this podcast as well

874
01:04:02,820 --> 01:04:07,750
and I think time is running 
out Trent, but on wrapping up.

875
01:04:07,750 --> 01:04:14,300
So 2021 was the year of scaling for Ocean
and you mentioned in one of your blogs that

876
01:04:14,300 --> 01:04:20,880
we will also share in the show notes of this
podcast, you mentioned that the coming years

877
01:04:20,880 --> 01:04:24,349
are also going to be the years of scaling.

878
01:04:24,349 --> 01:04:30,730
So if you have to really mention, or list
the three things that you plan to achieve

879
01:04:30,730 --> 01:04:37,660
in 2022 or rather plan to focus on, what would
you list as a concluding remark?

880
01:04:37,660 --> 01:04:44,240
Yeah, sure, so yeah, like, basically we view
2020 as the zero to one year, the year where

881
01:04:44,240 --> 01:04:49,349
we had initial product market fit and 
some early traction around that.

882
01:04:49,349 --> 01:04:56,040
And then 2021, 2022 etc is all the 1:N, so
you know 2020 0:1 and then after that it's

883
01:04:56,040 --> 01:05:05,320
1:N and that means, when you say 1:N traction,
it means more people, more transactions in

884
01:05:05,320 --> 01:05:07,900
Ocean, more data consumed volume etc.

885
01:05:07,900 --> 01:05:11,870
And data consumed volume is 
probably the best metric overall.

886
01:05:11,870 --> 01:05:17,310
And to grow, because it shows that there's
real value being created etc, but of course,

887
01:05:17,310 --> 01:05:19,651
we want to encourage free sharing 
of data etc, all that too.

888
01:05:19,651 --> 01:05:27,270
Then to your question, specifically, of, what
is it for 2022 that I see will have the big

889
01:05:27,270 --> 01:05:33,750
impact, I see, you know, in the early part
of 2022, we're going to be launching v4 and

890
01:05:33,750 --> 01:05:40,160
data farming and v4 is the solve rug pulls,
data NFTs and help community monetize.

891
01:05:40,160 --> 01:05:46,359
So that, once we release that and the data
farming it's going to be a lot of work and

892
01:05:46,359 --> 01:05:53,550
a very busy time and very exciting time for the community, 
because we see that this unlocks a lot of stuff, a lot of value.

893
01:05:53,560 --> 01:05:59,240
Data farming itself is going to be very generous,
so we expect that that's going to quite energize

894
01:05:59,240 --> 01:06:03,440
the community a lot and that's going to keep
our team quite busy throughout a lot of the year.

895
01:06:04,440 --> 01:06:09,000
Besides that, I also see that Ocean DAO itself
is going to keep getting bigger and scaling

896
01:06:09,000 --> 01:06:15,800
a lot more and that's very exciting, because
that's where the communities are really coming

897
01:06:15,800 --> 01:06:21,090
in fold and the importance of the core team
is already much lower than it was a year ago,

898
01:06:21,090 --> 01:06:24,820
because we've got this amazing 
community that has formed around Ocean.

899
01:06:24,820 --> 01:06:29,686
So Ocean DAO is basically going to keep growing
and evolving with these working groups and so on.

900
01:06:29,700 --> 01:06:34,500
And then beyond that, I see kind of related
to Ocean DAO, it's simply like the use cases

901
01:06:34,500 --> 01:06:39,740
and applications, we're starting to see more
applications from the top down perspective

902
01:06:39,740 --> 01:06:44,720
with consortia like Gaia-X from the bottom
up perspective with third-party marketplaces

903
01:06:44,720 --> 01:06:49,099
and other just really cool applications, whether
it's for data unions and otherwise and I see

904
01:06:49,099 --> 01:06:52,050
a lot more of that for 2021 as well.

905
01:06:52,050 --> 01:06:59,140
So to summarize, the three big pillars in
a sense are v4 data farming, Ocean DAO scaling

906
01:06:59,140 --> 01:07:06,242
and just a lot more real world use cases and
applications via top down and bottom up.

907
01:07:06,242 --> 01:07:10,660
Yeah and since you're growing so fast, now
the next time we need to have you before one

908
01:07:10,660 --> 01:07:13,070
year and not at a one year gap.

909
01:07:13,070 --> 01:07:14,070
Sure.

910
01:07:14,070 --> 01:07:16,480
And thank you Trent.

911
01:07:16,480 --> 01:07:22,800
This was so much fun and so much, for me,
also like an educational class so I really

912
01:07:22,800 --> 01:07:26,890
enjoyed it and thank you for joining us today.

913
01:07:26,890 --> 01:07:27,977
My pleasure, thank you for having me.

Tutorial | Algorithms and Compute Jobs live on Ocean Market.vtt

WEBVTT

00:01.280 --> 00:06.560
Welcome everyone to this first demo of
compute-to-data in the Ocean Market.

00:07.440 --> 00:11.600
Before we begin let's look at some concepts,
what we mean with compute-to-data.

00:11.600 --> 00:16.800
The value proposition is that it's buy and 
sell private data while preserving privacy.

00:17.760 --> 00:23.120
In the implementation this means there is a 
dataset, which is not allowed to leave the 

00:23.120 --> 00:30.720
premises of the respective data owner, while at 
the same time an algorithm, a small piece of code

00:30.720 --> 00:34.960
is allowed to run on this dataset under certain conditions.

00:35.840 --> 00:39.120
While we always had compute-to-data environments running

00:39.120 --> 00:44.320
in the wild, in marketplaces I'm not allowed to talk about.

00:44.320 --> 00:48.480
There was never the completely public use case of Ocean Market considered, 

00:49.360 --> 00:53.040
so the Ocean Market team set out to create a solution

00:54.240 --> 01:01.280
with the guiding principle that the data set is always going to be private.

01:02.720 --> 01:08.560
How we decided to do that technically, is 
essentially that we now have a new asset type,

01:09.520 --> 01:13.920
essentially algorithms and before that we only had datasets.

01:14.560 --> 01:21.120
So technically this means that in our DDO to the 
type dataset, we now have a type "algorithm".

01:22.000 --> 01:26.720
And as you see as an example, a dataset file for instance could be a CSV file

01:26.720 --> 01:32.240
and an algorithm could be in this case 
a small Node.js app, which does something.

01:33.520 --> 01:38.160
At the same time algorithms have a bit more rules attached to them.

01:38.160 --> 01:43.920
In this case we decided to allow algorithms 
to be either public or private.

01:44.800 --> 01:48.240
In the implementation this means that just like datasets, 

01:48.240 --> 01:51.440
when algorithms are public they can be downloaded,

01:51.440 --> 01:53.840
meaning bought for the set price.

01:55.040 --> 02:00.080
But when they're set to private, 
they're essentially not accessible.

02:00.080 --> 02:03.680
While technically this means in the 
background we set a compute service,

02:03.680 --> 02:08.960
we decided in the UI to not expose compute-to-data 

02:08.960 --> 02:13.280
onto an algorithm, to keep the use cases a bit more simple.

02:15.680 --> 02:19.360
When looking at this general data flow, this user flow,

02:19.360 --> 02:25.440
this means we are going to have a data set, 
which is published with a service,

02:26.080 --> 02:29.760
compute service and at the same time an algorithm,

02:29.760 --> 02:34.240
which is published as a type algorithm and the publisher can then 

02:34.240 --> 02:38.000
connect those two and from a general user perspective,

02:39.200 --> 02:46.240
they can then combine those, the dataset 
and the algorithm, and run a compute job.

02:47.040 --> 02:52.720
What we mean by that is essentially that the data consumer or 

02:52.720 --> 02:59.040
the person running the compute job 
will order the dataset and the algorithm,

02:59.040 --> 03:02.640
so we'll pay the sum of both prices.

03:02.640 --> 03:04.400
In that scenario this also means  

03:05.760 --> 03:11.920
that, just as datasets, algorithms can have both a pool 
or a fixed price.

03:13.600 --> 03:17.840
Essentially exposing small little algorithms to the same

03:18.480 --> 03:22.240
automated market maker use cases we have for datasets.

03:23.520 --> 03:28.800
Once a compute job starts, it means that there is a Kubernetes 

03:28.800 --> 03:34.000
environment, in which pot is spotting up.

03:35.840 --> 03:39.920
This also means that this is another centralized component, 

03:39.920 --> 03:42.880
where we already have our provider,

03:43.760 --> 03:46.880
where we now have the operator service and the operator engine 

03:46.880 --> 03:49.760
and the various other smaller microservices.

03:50.400 --> 03:54.160
And just as with the provider, this would be up to the 

03:55.040 --> 03:59.120
respective marketplace owner to properly control it

03:59.120 --> 04:03.360
and guarantee no data exposure.

04:03.360 --> 04:06.400
Continuing in our general user flow, when the compute job 

04:06.400 --> 04:13.680
is started and it's running, user 
can in the end access compute results,

04:13.680 --> 04:16.400
which are essentially log outputs,

04:16.400 --> 04:22.240
so every algorithm has certain access to the underlying parts.

04:22.240 --> 04:25.680
So in this case for instance, there could be an output directory 

04:26.320 --> 04:29.840
and in there the algorithm can write results

04:30.800 --> 04:33.920
and on the market we simply display them.

04:35.200 --> 04:42.160
As for a publisher, it essentially comes down to this process.

04:42.160 --> 04:45.600
Every publisher gets a new edit action on every dataset 

04:46.240 --> 04:52.720
with a compute service and on there, the publisher either

04:54.080 --> 04:58.720
allows selected algorithms, which is basically a list of all 

04:58.720 --> 05:03.680
algorithms published in the market 
or simply allows all published algorithms.

05:04.560 --> 05:07.360
We also decided for the private by default use case, 

05:07.360 --> 05:11.840
so every compute dataset by default

05:11.840 --> 05:18.480
has no permissions attached to it, so there is
simply an empty list of algorithms.

05:20.960 --> 05:25.600
And now let's look at all those concepts in reality.

05:26.720 --> 05:30.160
Let's look at the compute-to-data changes in the UI.

05:30.160 --> 05:32.800
We're currently looking at our staging version,

05:32.800 --> 05:35.600
where we put everything together for the last two months.

05:36.560 --> 05:40.320
And as you see, pointed against Ethereum mainnet 

05:40.320 --> 05:43.680
there's not much going on regarding a compute-to-data,

05:43.680 --> 05:46.880
but you already see some differences on the asset teasers, 

05:46.880 --> 05:52.000
we now output the type of asset and the type of access on them.

05:53.760 --> 05:58.720
We ourselves use the Rinkeby to test our compute-to-data, 

05:59.280 --> 06:01.760
but for the sake of this demo we're going to

06:01.760 --> 06:07.200
Polygon (Matic), which we also suggest to use,
especially for computer data,

06:07.920 --> 06:11.840
considering there are a bunch of more transactions involved, 

06:11.840 --> 06:16.720
than for downloading, because essentially 
two assets are going to be ordered.

06:18.880 --> 06:22.560
If we look at the UI, you already see some changes here, 

06:22.560 --> 06:26.560
there is a dataset which telling us by this icon,

06:26.560 --> 06:34.240
that this is a compute asset and over here we
have another type of asset, this algorithm which,

06:35.040 --> 06:38.320
by this icon tells us it can be downloaded.

06:39.760 --> 06:42.240
When it comes to an algorithm and it's presentation, 

06:42.240 --> 06:45.440
it's not much different than from a dataset,

06:46.000 --> 06:50.080
same mechanisms regarding the pricing, in this case it's a pool.

06:50.960 --> 06:56.480
And one difference is that in this case we output the Docker image, 

06:57.520 --> 07:01.840
which is going to be used with this algorithm.

07:01.840 --> 07:12.080
When it then comes to the respective dataset, 
in this case this is our new compute UI and

07:13.120 --> 07:18.000
the state of this UI is basically that on this dataset, 

07:18.720 --> 07:23.760
this algorithm we just looked at has been allowed to run.

07:23.760 --> 07:25.840
Now let's look at the publisher perspective.

07:26.720 --> 07:30.000
So let's say I'm a publisher and I want to have this algorithm

07:30.000 --> 07:36.480
also run on my own dataset so, as before I would first come up with

07:36.480 --> 07:57.840
my dataset, I'm gonna copy that, some example dataset over.

07:57.840 --> 07:59.920
So this should work as is.

08:01.520 --> 08:06.960
And then, let's quickly fill out that.

08:08.240 --> 08:14.560
And, quickly put in our dataset file.

08:19.200 --> 08:20.800
And a sample file.

08:21.840 --> 08:29.120
And as you now see, to the access type,
we now also have a compute, in addition

08:29.120 --> 08:39.840
to download and just gonna go through with that.

08:42.960 --> 08:50.320
And now create the data token
and after that publish the metadata on-chain.

08:52.800 --> 09:07.840
And at the very end we're 
also gonna create some price for it.

09:19.760 --> 09:21.840
Okay, this was faster than expected.

09:26.960 --> 09:35.920
And I think we're already there.

09:35.920 --> 09:39.680
And should get the success message in a second.

09:40.960 --> 09:41.600
There we go.

09:43.680 --> 09:49.440
Now we have published this as a new asset and
a lot of compute on it and as you see, by default,

09:49.440 --> 09:54.960
nothing is allowed on it, but for now let's first
also create quickly a pool for it.

09:56.720 --> 10:00.880
Let's keep it cheap, put 50 Ocean in there.

10:02.560 --> 10:03.840
It's a higher swap fee.

10:08.160 --> 10:17.840
And create a pool for it.

10:21.920 --> 10:26.000
So nothing changed here, this is the flow as before, 

10:26.000 --> 10:29.280
except for this changed compute-to-data interface.

10:30.720 --> 10:33.040
Obviously it makes sense when allowing

10:33.040 --> 10:37.920
compute on one's asset to first have a price,
that's why I'm gonna do this all first.

10:44.480 --> 10:59.840
And after creating a pool and moving #OCEAN into it.

11:19.520 --> 11:20.320
Almost there.

11:25.040 --> 11:27.840
Approving to spend all the things.

11:41.120 --> 11:55.840
Now finally throwing everything into the pool.

12:08.640 --> 12:09.440
There we go.

12:09.440 --> 12:13.680
To be safe, reload the page and there we have it, we now have a pool.

12:15.680 --> 12:17.840
So far nothing new,

12:17.840 --> 12:23.200
but under the asset there is now a new setting 
called Edit Compute Settings.

12:23.200 --> 12:25.600
And as the publisher,

12:27.280 --> 12:33.840
you were then, on this new screen, 
allowed to set the allowed algorithms.

12:33.840 --> 12:36.080
So as you see, by default, nothing is selected.

12:36.080 --> 12:40.640
In this case we exactly wanted to have this data points algorithm,

12:41.280 --> 12:45.200
so we do that and allow it to be ran on it.

12:46.400 --> 13:05.840
This again is a metadata update transaction,
so, still have to use MetaMask for that.

13:09.040 --> 13:12.080
And after the dataset is updated, this  

13:12.640 --> 13:19.840
algorithm is now allowed to run on this dataset by everybody.

13:24.080 --> 13:26.800
Now let's do the same for an algorithm.

13:26.800 --> 13:31.600
Let's say I'm the publisher of this data set
and I want to have my own algorithm on here.

13:32.480 --> 13:34.880
Let's say as an example, we're gonna publish in  

13:35.600 --> 13:39.680
the same algorithm as this, but with a fixed price.

13:40.240 --> 13:44.960
So as before, but this time we go to Algorithm 

13:46.160 --> 13:54.560
and I'm gonna copy over all the data 
you need for that, to keep it quick.

13:57.280 --> 14:03.360
And in this case, I simply use a secret Gist  

14:05.360 --> 14:11.920
on GitHub for this algorithm, so it's worth quickly looking at that.

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So this is a typical algorithm,

14:13.920 --> 14:17.680
there are a bunch of rules around that,
which we're going to document in our docs,

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but the basic principle is that  

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the algorithm has an input folder and access to an output folder.

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And during the time of running it can 
simply write files only to this folder.

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And in this case we are ending up 
with a output log and a result log,

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which is essentially the console logs being output.

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So in this case I simply use the raw 
link for that and this is a secret Gist,

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so it's not so easy to access.

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This is just as an example, but typically the algorithm would be 

15:01.920 --> 15:06.000
hosted as a file somewhere, just for this example I used this.

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If we move on, we say okay, this is a Node.js app, 

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so we're going to use the latest node, it can be also used forever.

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We're going to allow downloading of it
to keep it simple and this was actually

15:26.480 --> 15:28.720
created by us, as an example.

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And we're quickly publishing this.

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Again, same thing as with datasets is happening.

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I'm going to create a data token, I will then encrypt the file URL, 

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put this all into a DDO, which is then ending up on-chain.

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And once we're finished, for this algorithm we're going to create

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simply a cheap fixed price, so it can be just used easily.

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And again, we should be actually already done.

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There we go, now we have our algorithm.

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Let's quickly create a fixed price,

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keep it cheap, 1 Ocean.

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In the background creating a fixed rate exchange for that.

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And now we are almost done in our pricing flow.

17:59.600 --> 18:03.840
And now we have it here for 1 Ocean, there we go.

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Now we're trying to find our recently published dataset, 

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where we now can simply go into Compute Settings.

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And the new one shows up, we allow it.

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Same thing again, updating the metadata.

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And after this transaction is done, we 
should be able to select two algorithms.

18:47.200 --> 18:49.280
There we go, here's our fixed price.

18:54.160 --> 18:57.920
And now let's look at actually starting a compute job on a dataset.

18:58.560 --> 18:59.760
Switch to a new account.

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Put some money into it.

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So, let's see.

19:07.840 --> 19:13.680
Let's first go to this dataset and we want to run this algorithm on it.

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All the prices are put together and because both of them 

19:18.560 --> 19:20.720
have a timeout, we're buying them for one hour.

19:22.800 --> 19:29.760
And we're going to buy both assets,
which means a lot of transactions in between.

19:30.560 --> 19:36.640
And with a fresh account, we're also getting all of them in one flow,

19:37.920 --> 19:42.240
because once you have bought it you can most likely, 

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in most circumstances, start a compute job again without paying again,

19:46.240 --> 19:53.120
this will be then also always reflected down here,
based on the timeout on each asset.

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Which is, by default, set to forever and 
it's up to the publisher setting that.

20:06.800 --> 20:15.200
Now, we already have bought the dataset token,
now we're buying the algorithm data token.

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And also allowing to spend multiple currencies.

20:34.320 --> 20:40.240
And by seeing this, you can probably imagine 
why we suggest doing this on Polygon.

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And after we have all those transactions.

20:49.040 --> 20:51.120
Okay, this was interesting, at the same time.

20:58.240 --> 21:15.840
The final step then will be to simply sign 
the compute job and then it's going to be ran.

21:15.840 --> 21:16.880
Not yet.

21:19.200 --> 21:29.840
Still interacting with the final dataset as it looks like, algorithm.

21:31.520 --> 21:34.880
And now we're signing to start the actual job.

21:37.040 --> 21:39.040
And there we see, okay, it started.

21:40.640 --> 21:50.000
And for now we can go to our History and 
there you see that our compute job is running.

21:51.840 --> 21:58.080
As it is right now, we don't have a smart refetch thingy going on here, 

21:58.080 --> 22:01.120
so for now it's all about switching the tabs.

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In general, everything regarding the

22:04.960 --> 22:08.320
outputs is definitely something we're going to look 

22:08.320 --> 22:11.840
into further, to improve on the usability,

22:12.960 --> 22:16.880
but as soon as this is 
basically finished you will get a button, 

22:17.600 --> 22:20.480
which upon clicking reveals the results.

22:20.480 --> 22:22.320
Again this also needs to be signed,

22:23.280 --> 22:29.440
so it's it's also not just a public link accessible for everybody, 

22:29.440 --> 22:40.080
so only for the consumer of the compute job.

22:40.080 --> 22:43.200
And we already see the results are already published.

22:47.760 --> 22:53.840
Which as of right now is not as smart, decentralized publishing, 

22:53.840 --> 22:58.320
it's simply put into an S3 bucket for now.

22:58.320 --> 23:01.440
And again this is the whole compute-to-data infrastructure, 

23:01.440 --> 23:06.080
which is up to the marketplace owner to run

23:06.080 --> 23:08.400
and maintain and this would be then also something.

23:09.520 --> 23:13.520
The marketplace owner would decide where to store those results.

23:14.720 --> 23:19.760
As it is right now, we now see, okay,
job finished, written about in a minute.

23:21.440 --> 23:23.520
And now the button becomes active.

23:27.440 --> 23:31.120
We sign it and there we have our log.

23:31.120 --> 23:44.240
As you see you can simply download it, it's also 
streamed down and you see we have 114191 lines.

23:45.280 --> 23:49.840
So this is coming directly as the output from the algorithm.

23:51.120 --> 24:03.840
And this so far is our first interface for compute-to-data.