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I feel the publishing industry has created a model where they try to extract maximum value out of their human bloggers and treat them like assembly-line workers. There's not a lot of value in "aggregating" stories. It's just publishers trying to eek out a slice of the pie. A lot of this work will certainly be automated in the future. I feel like the quantity over quality model that Internet publishers have fallen into is flawed for the business and the consumer because there is so much replicated work and it does not take advantage of economies of scale very well. In the future, there may be fewer overall writing jobs, but they will leverage human creativity much more than the current landscape. Before the content-farming blog jobs totally go away, they will trend in the direction of editorial oversight into a more automated process. This part will probably vanish eventually as well. Ben Halpren
National Novel Generating Month is phenomenal, and I fully endorse the idea of AI-written novels. I think there are some human truths out there that might not be unearthed until we have a non-human bring it to our attention. You can't compare it to the imagination and complexity of human-generated literature (and personally, I don't think you ever really will) but these algorithms give us a fantastic insight into how computers CAN contribute to the artistic community. Audrey Greathouse
Darius Kazemi is an internet artist under the moniker Tiny Subversions. His best known works are the Random Shopper (a program that bought him random stuff from Amazon each month) and Content, Forever (a tool to generate rambling thinkpieces of arbitrary length). He has a small army of Twitter and Tumblr bots that he builds because they make him laugh. He founded NaNoGenMo, where participants spend a month writing algorithms to generate 50,000 word novels, and Bot Summit, a yearly gathering of people who make art bots. He cofounded Feel Train, a creative technology cooperative. MirrorConf
Here's a twist on NaNoWriMo: NaNoGenMo. Isn't it everyone's dream to write the Great American Computer Program to write the Great American Novel? ‎Bill Kronholm
Is the future of novel-writing #NaNoGenMo?... (We hope not, but we also hope that research is collated from this that can be used to analyse trends and contribute to the future of publishing debate). The Literacy Consultancy
This month, several thousand aspiring authors are attempting to write a novel in 30 days. They are taking part in an annual event known as NaNoWriMo, National Novel Writing Month, in the hope that the time pressure will spur them on. For a small community of computer programmers, though, NaNoWriMo has a lighthearted sister competition: National Novel Generating Month, the goal of which is to teach a computer to write a novel for you. However, finished NaNoGenMo projects are unlikely to trouble Booker judges. They include a version of Moby-Dick in which the words have been [swapped for meows]( of the same length (immortal opening line: Meow me Meeeeow); another version in which a few key words have been swapped out for emoji; and a novel made up of unconnected excerpts from an online database of [teenage girls’ accounts of their dreams]( "Can Computers Write Artifical Fiction?", The Guardian
“It’s not hard to generate a story,” says [Dr. Mark Riedl]. “It’s not hard to tell a story. It’s hard to tell good stories. How do you get a computer to understand what good means?” Figuring this out involves stripping human creativity down into its numerous constituent parts, devising algorithms for every device an author might deploy. In building a computer that can write, we are exposing the computer within the writer. "Can Computers Write Artifical Fiction?", The Guardian
Novels generated by computers. I'm pretty sure this is blasphemy. And I don't believe in the concept of blasphemy. Texasbooklover
If you think your creative arts job is safe, you haven't heard of things like [The Grid, a computer program that makes websites]. There are so many web sites that are "good enough," that this product is not only plausible, but inevitable. And then there are the AI novels, paintings, and music. ... It's not there, of course. Not yet. But a lot of this is surprisingly close to something entertaining, and I'd be very surprised if, by 2100, we aren't immersed in computer generated creative content. Eliot H Hochberg
I looked at a few of these computer generated novels. Let’s just say that James Patterson isn’t in any danger from AI yet. Andi Lutz
I’ve been familiar with “National Novel Writing Month” for a while now, but I found out about “National Novel Generation Month” just a few days ago. Like all great projects it came from an idea tweeted on a whim. Instead of spending the month laboring over a novel, why not spend the month writing some code, and have a computer generate the novel for you? All of the generated projects are open source and shared on github. Some of them are a little too data-sciencey (a word i just made up) for my tastes, but others are pretty great. I’m posting my favs in the comment thread below. I think that [Steve Kemple]( (creator of the amazing [Dada News Daily](, artist, librarian, and one of the [CONSENSUSCON 2014 - rewrite the book on writing books guest speakers]( HAPPENING IN JUST TEN DAYS) is really gonna love this. Chris Collins
I think [NaNoGenMo] stretches the definition of "novel" just a wee bit. The Writer's Ally
NaNoWriMo asks you to write a novel in a month. They didn't say anything about using models to generate the writing Data Science Retreat
First came traditionally published authors, then indie writers arrived on the scene, and now computers are getting in on the act. Maybe all writers will be replaced in the future by computer generated ebooks. Published Authors
Computers are coming for our jobs, as writers. Spooky. Tom Trimbath
Novelists, at least, have nothing to fear. Or so you might think. In George Orwell’s 1984, the ‘proles’ read books generated by a machine, but a machine is hardly going to able to replace Margaret Atwood. After all, we turn to literature in part to deepen our understanding of the human condition, and its magic derives as much from the writer’s own lived experience – emotional, sensory or otherwise – as from their creativity. Even if a string of zeroes and ones evolves to understand what it means to taste a childhood food in later life, or to feel the first splash of spring sunshine as a long winter loosens its grip, that algorithm won’t truly be able to know such experiences. For all these reasons and more, a robot could never rival a flesh-and-blood novelist. Could it? "Could A Robot Write a Novel?" BBC
To date, our ideas about AI have been shaped largely by fiction writers. The very word 'robot' was first introduced in Karel Čapek's 1920 play, Rossum's Universal Robots. Whether or not algorithmic authors are shooting up the bestseller lists by 2020, human writers have an ever more critical role to play in navigating the implications of a brave new world that’s finally catching up with the literary imagination. The answers that computer scientists are coming up with raise ethical, philosophical and legal questions – not to mention security concerns – that we’ve barely begun to fathom. Now surely there’s a novel in that? "Could A Robot Write a Novel?" BBC
So does [Darius Kazemi] believe a machine could write a truly great novel – one that transcends its own novelty? “I think bots and the meaning of what a good novel is will converge”, he says. “I don’t think we’ll have something that looks like Moby Dick but I do think we’re already writing code that is generating really excellent conceptual novels. And I’m actually excited about novels that are co-authored between humans and code. That would be really cool.” So far, he’s yet to be approached by any professional novelists, just kids wanting the code to write their homework. For now, the real challenge for developers is length. “Once you hit that 3,000-word barrier, it starts to get very difficult to sustain people’s attention”, Kazemi says and [futurist Kevin Warrick] agrees. "Could A Robot Write a Novel?" BBC
Technology would seem to be levelling the playing field by shortening our attention spans, but plenty of obstacles still separate bots from the Booker. They’re not good with characters vanishing then reappearing 78 pages later, for instance, and without regurgitating from a database, they can’t convincingly integrate sensory detail. Yet they will get there, [futurist Kevin Warwick] insists – if not winning over book prize judges then certainly fooling them. “If it hasn’t been done within about ten years, then I would be very surprised”, he adds. "Could A Robot Write a Novel?" BBC
... [Darius Kazemi], a Thomas Pynchon fan, is also the originator of National Novel Generation Month or NaNoGenMo – the techy riposte to National Novel Writing Month in the US. He suggested it via Twitter in 2013 and it promptly took off, its only rules being that entrants must share a novel of more 50,000 words along with the code that generated it. The NaNoGenMo works require varying degrees of human input, though Kazemi admits that the most successful ones involve a considerable amount. One of his favourites is [The Seeker]( by thricedotted, which cannily casts the narrator as a robot trawling WikiHow to learn to become more human. “There was a lot of human input, sourcing from WikiHow which is full of human text,” he tells me via Skype from Boston. He also points out that the writers of the algorithms bring their own human experiences to bear on their coding, adding a necessarily human element. "Could A Robot Write a Novel?" BBC
From ["The Computer Will Learn To Write Novels"]( -- It is possible that computer-generated novels may be customized "in accordance with the preferences of a particular reader". And text generation alerady being used today - from chatbots for online stores to automated journalistic articles created by Narrative Science and Yandex. However, machines cannot deliver the same "experience" that a human author can provide. When humans write, they do so "based on their own feelings, emotions and thoughts", while machines must rely on the "experience" in "already known texts". It would be impossible to for a computer to generate great works of arts like "War and Peace","Anna Karenina"," Childhood "," Adolescence "," Youth "," Kreutzer Sonata ", etc. Clearly, computer-generated novels will still be massively in demand...just not in the near-future. Companies are more intrigued at the potential for text mining at the present-day.
From ["The Computer Will Learn To Write Novels"](, -- In 2016, Google began training a machine learning algorithm on 2865 romance novels to understand English and generate a novel. The lead programmer of the project, Andrew Dai, states that they are doing this to improve search engine results by ensuring that machines are able to understand the nuances of the English language. Google is not the first entity to experiment with novel generation. In 2013, during the first NaNoGenMo competition, the computer-generated novel "Teenagers walking around the house" was created. AI entities take a virtual walk around a house, and the actions of these teenagers and their dialogue ("created from tweets") are recorded in text.
It’s November and aspiring writers are plugging away at their novels for National Novel Writing Month, or NaNoWriMo, an annual event that encourages people to churn out a 50,000-word book on deadline. But a hundred or so people are taking a very different approach to the challenge, writing computer programs that will write their texts for them. It’s called NaNoGenMo, for National Novel Generation Month, and the results are a strange, often funny look at what automatic text generation can do. "The strange world of computer-generated novels", The Verge
The developer and artist Darius Kazemi started NaNoGenMo [in 2013], when he tweeted out an off-the-cuff idea. "Hey, who wants to join me in NaNoGenMo: spend the month writing code that generates a 50k word novel, share the novel & the code at the end?" "I got a ton of people responding saying ‘Oh my god, I’d totally do that,’" Kazemi says. The next day, he opened up a repository on Github where people could post their projects. "The strange world of computer-generated novels", The Verge
Nick Montfort’s World Clock was the breakout hit of [2013]. A poet and professor of digital media at MIT, Montfort used 165 lines of Python code to arrange a new sequence of characters, locations, and actions for each minute in a day. He gave readings, and the book was later printed by the Harvard Book Store’s press. Still, Kazemi says reading an entire generated novel is more a feat of endurance than a testament to the quality of the story, which tends to be choppy, flat, or incoherent by the standards of human writing. "Even Nick expects you to maybe read a chapter of it or flip to a random page," Kazemi says. "The strange world of computer-generated novels", The Verge
For [2013]’s NaNoGenMo [Darius] Kazemi generated "Teens Wander Around a House." He made a bunch of artificial intelligence agents and had them meander through a house at random, his program narrating their actions. When two characters ended up in a room together, he pulled dialogue from Twitter. One tweet could be a question — "What’s for dinner tomorrow?" — and the next, a statement that also contained the word "dinner" — "Dinner is my favorite meal of the day," for example. "The result was a conversation that sort of stayed on topic but didn’t make much sense," he says. "The strange world of computer-generated novels", The Verge
[In 2014], [Darius Kazemi] design[ed] a program that interprets an online step-by-step guide to novel writing extremely literally. "It starts with ‘establish a day-to-day routine’ then ‘show the characters’ wants and dreams’ then ‘give them a call to action,’ all that stuff," Kazemi says. "It reads like crap but it actually does have a forward sense of narrative." "The strange world of computer-generated novels", The Verge
Michelle Fullwood made Twide and Twejudice: Pride and Prejudice but with each word of dialogue substituted for a word used in a similar context on Twitter. The result is delightfully absurd, a normal-seeming Austen novel where characters break out in almost-intelligible gobbledegook. For instance, here is Mr. Bennett telling Mrs. Bennett that plenty more wealthy young men will move to town for their daughters to marry. "But I hope you willl get ovaaa it, whereby live to see manyy young snowmobilers ofthe four karat a yearrr comeeee into tje neighbourhood." And in an earlier version: "But I hopee yiou willllll gget ovaaa itttttttttt , aand livee to seee meny peppy cyborgs ofv umpteen luft awhole mnth coem intoo tthe neighbourhood." "The strange world of computer-generated novels", The Verge
Liza Daly made her own version of the [Voynich Manuscript](, a 15th century codex written in an unknown script and illustrated with elaborate and perplexing diagrams. Daly wrote a program that took words from the codex, randomized them, and placed them on a page along with old alchemical and botanical images from the Internet Archive. The result is quite beautiful, and no more or less bewildering than the source codex. "The strange world of computer-generated novels", The Verge
Then there’s Greg Borenstein’s Generated Detective, a noir comic. Borenstein’s program searches old detective novels on Project Gutenberg for sentences that include a series of words. [:question, :murderer, :witness, :saw, :scene, :killer, :weapon, :clue, :accuse, :reveal] ![Form Generated Detective: Picture of Clown - Of course, that man is the actual murderer.]( He then searches Flickr for each sentence plucked by the program, runs the resulting image through a manga app, and ends up with an eerily inscrutable noir story. Borenstein does the Flickr search himself, but he’s working on automating the whole process, as well as incorporating image recognition so that the program can add dialogue bubbles. "The comics that come out give me chills sometimes," [Darius] Kazemi says. "It’s a very disjointed, dream-like narrative, like most NaNoGenMo narratives." (UPDATE: Borenstein has automated Generated Detective's sentence and image selection, as well as modified the script to pull sentences from different genres, including sci-fi,romance, and horror.) "The strange world of computer-generated novels", The Verge
Ultimately, [Darius] Kazemi says, the point is to have fun, to flex your coding muscles a bit, and maybe leave thinking about text a little differently. He points to the strange cadence of [Definition Book]( a program that parenthetically defines a word from an initial eight-word sentence, and defines a word from that definition, and so on, recursively for 50,000 words. The first half of the book is all the beginning of sentences and the second half is the end. "I’ve never thought about a text that way," Kazemi says. "It sort of turned on a lightbulb in my head." "The strange world of computer-generated novels", The Verge
Narrative is one of the great challenges of artificial intelligence. Companies and researchers are working to create programs that can generate intelligible narratives, but most of them are restricted to short snippets of text. The company Narrative Science, for example, makes programs that take data from sporting events or financial reports, highlight the most significant information, and arrange it using templates pre-written by humans. It’s not the loveliest prose, but it’s fairly accurate and very fast. NaNoGenMo, [Darius] Kazemi says,"is more about doing something that is entertaining to yourself and possibly to other people." "The strange world of computer-generated novels", The Verge
While [Darius] Kazemi prefers pieces that make sense, he isn’t gunning for literature. In fact, he thinks the less human the output, the more intriguing. “What I want to see is code that produces alien novels that astound us with their sheer alienness,” Kazemi says. “Computers writing novels for computers, in a sense.” "Computers Are Writing Novels, But Do You Really Want To Read Them?", SingularityHub
In the future, evolutionary algorithms (or some other form of self-reproducing code) might generate themselves, removing the human step and developing into something altogether new and undirected. If such programs decided to write, what would their prose look like? Probably, as [Darius] Kazemi says, astoundingly alien. Or there's another possibility. Such extremely advanced programs might find writing charming, quaint, and utterly useless. We tend to anthropomorphize artificial intelligence. Like Pinocchio, Star Trek's Lieutenant Commander Data tries to be more human, learning violin or painting and never quite replicating the intangibles characteristic of fine art. But maybe art will forever remain a human endeavor, not because machines can't master it—but because they just don't give a damn. "Computers Are Writing Novels, But Do You Really Want To Read Them?", SingularityHub
Beyond the (likely significant) blood, sweat, and tears spent coding the program—there isn’t, in theory, any particular factor limiting the quality of computer-generated prose. It might eventually be indistinguishable from a human product. However, even if such prose is beautiful, artistic, and coherent—a human is still pulling the strings, writing the program, feeding it information, and hitting the ‘start’ button. The program is a vastly complicated mechanism for pulling phrases from a hat. Just another tool used by humans to make art, like a paint brush, pottery wheel, or guitar amplifier. "Computers Are Writing Novels, But Do You Really Want To Read Them?", SingularityHub
Some of our most beloved and timeless works are, for example, quite formulaic. Joseph Campbell’s famed Hero With a Thousand Faces outlines consistent elements in the classic hero’s journey, evident in ancient and modern stories alike. Perhaps most famously, George Lucas said Campbell’s work was a driving force behind Star Wars. Why couldn't the structure of the hero's journey, our favorite fairy tales, or best sellers be employed by algorithm? "Computers Are Writing Novels, But Do You Really Want To Read Them?", SingularityHub
William S. Burroughs ... championed algorithmic prose and poetry with his cut-up technique—a method where the artist slices and rearranges sentences or even entire scenes, often with little regard for meaning or flow. Burroughs inspired musicians like David Bowie and REM’s Michael Stipe to make lyrics from cut-ups. Radiohead’s front man Thom Yorke has said he pulled phrases from a hat while recording the groundbreaking album, Kid A. Burroughs inspired musicians like David Bowie and REM’s Michael Stipe to make lyrics from cut-ups. Radiohead’s front man Thom Yorke has said he pulled phrases from a hat while recording the groundbreaking album, Kid A. Curious, I separated the lyrics to REM’s “Ignoreland” into a list and, successively pairing the top and bottom words, made new lyrics. With a few minor rearrangements to fulfill basic grammar and syntax rules, the result was surprisingly passable, and of course, a computer, using the same algorithm and rules could also have performed the task. "Computers Are Writing Novels, But Do You Really Want To Read Them?", SingularityHub
[C]omputers have been ... constructing algorithmic sentences since 1952. A machine from that era, the Ferranti Mark 1, constructed love letters from a static list of words, a very simple version of the way modern newsbots build articles from preprogrammed phrases. “Dear Honey, my avid appetite lusts after your anxious desire. You are my beautiful tenderness my adorable longing,” begins one such letter signed, “Yours seductively—MUC.” Modern news writing algorithms are more complex, faster, can analyze data, and peruse sizable lists of styles, angles, and phrases. But their advantage over the Ferranti Mark 1 is almost as much about computing power as it is about method. "Computers Are Writing Novels, But Do You Really Want To Read Them?", SingularityHub
IBM, Google, and others are currently pouring resources into natural language processing research. What is natural language processing? IBM's Watson, for example, understands questions phrased in plain english, pours over millions of pages related to the query, and provides conversational, self-generated answers. Next generation newsbots will likely look more like Watson—able to draw upon both quantitative and qualitative information to inform their articles and reports. A capability that will be useful from journalism to medicine to business. "Computers Are Writing Novels, But Do You Really Want To Read Them?", SingularityHub
Many of [[2013]’s submissions]( used source content by humans—dream journals, tweets, fan fiction, Jane Austen, Homer. One is 50,000 words of roommates arguing about cleaning the apartment. Another has the simplistic feel of a reading primer. While the results aren’t exactly Shakespeare or Hemingway, they are, with few exceptions comical. "Computers Are Writing Novels, But Do You Really Want To Read Them?", SingularityHub
Kazemi’s contribution, [Teens Wander Around a House](, begins, “Philomena, Dita, Vivianna, Darby, Kiah, and Gale found themselves dropped off at the same party at the same time by the irrespective mothers. How awkward." Indeed. "Computers Are Writing Novels, But Do You Really Want To Read Them?", SingularityHub
Emulating National Novel Writing Month (NaNoWriMo)—a November tradition where authors attempt to complete an entire novel (start to finish) in a month—developer and internet artist Darius Kazemi started NaNoGenMo last year. Like NaNoWriMo, NaNoGenMo offers no prizes. Unlike NaNoWriMo, the computer-generated novels need not make one whit of sense (though many do). There are few rules beyond submission of the book and the code responsible for writing it. "Computers Are Writing Novels, But Do You Really Want To Read Them?", SingularityHub
So how do you win NanNoGenMo? You don't, really. "There are no prizes in NaNoWriMo; similarly there are no prizes in NaNoGenMo," says Kazemi. "The way you win is to write code that writes 50,000 words. That's it. Really, it's up to individual participants to decide whether they've won." "Will The Next Great American Novel Be Generated By Code?", FastCompany
[In 2013], a developer named Leonard Richardson created a script called [In Dialogue]( that automatically takes the dialogue in one book and swaps it out with that of another. "I love it because it's a very simple task, computationally, but does a wonderful job of generating a surprising and funny novel that reads like a new text," says [Darius] Kazemi. "Will The Next Great American Novel Be Generated By Code?", FastCompany
November is National Novel Writing Month (aka NaNoWriMo). You're probably thinking: Write a book in a month? Are you kidding? Such an endeavor would require an attention span of the sort we possessed before Twitter, not to mention the ability to... what was I talking about again? There is a more efficient way to write a novel. And if Vim or Emacs is your word processor of choice, then you're in luck. November also happens to be National Novel Generation Month (aka NaNoGenMo). It's a call for developers to build apps capable of automatically generating at least 50,000 words. Started via GitHub last year by Boston-based developer and self-proclaimed "Internet artist" Darius Kazemi, the projects don't necessarily need to be hosted on GitHub, but that's where Kazemi is encouraging participants to share their initial ideas and progress. "I decided on a whim [in 2013] that it would be fun to do their event but by writing code that writes novels," says Kazemi. The rules of the competition are pretty loose: Coders need only submit a sample book and their source code when finished. The book doesn't even have to make sense. It can be a massive vat of "Lorem ipsum" soup or an attempt to get a machine to churn out something coherent. "Will The Next Great American Novel Be Generated By Code?", FastCompany
[NaNoGenMo](, or [National Novel Generation Month](, may sound like a parody of NaNoWriMo at first: write code that generates a novel of 50,000+ words. However, it’s a great way to engage in coding and try something new: creator Darius Kazemi noted that a novel could be defined however you want, including “50,000 repetitions of the word ‘meow’”, a concept taken literally in this [Meow edition of Moby Dick]( Exploring the code and resources from the community offers some very cool models of playing with language and procedural generation. "#AcWriMo, #DigiWriMo, #NaNoGenMo and November Writing Sprints", Chronicle of Higher Education
Just wrapped up National Novel Writing Month? Take a breather — your marathon's finally finished. But, as [the Verge observes](, if only you'd followed [this guy's suggestion](, you might never have had to run it in the first place. Welcome to National Novel Generation Month, a challenge not to write a book, but to write a computer program that will write that book for you. To give you an idea: Participant Michelle Fullwood generated [Twide and Twejudice]( — "Pride and Prejudice but with each word of dialogue substituted for a word used in a similar context on Twitter." "Book News: Files Said To Contradict 'In Cold Blood' May See Light Of Day", NPR
Creative and artistic feats are often seen as the last refuge for human endeavor from the coming robot apocalypse. But if NaNoGenMo gains a foothold and improves, at least we'll all be well entertained in our unemployment. "Computers Write Novels Faster Than You Do", Smithsonian Maganize
“[R]eading an entire generated novel is more a feat of endurance than a testament to the quality of the story, which tends to be choppy, flat, or incoherent by the standards of human writing,” says the Verge. But there's no guarantee of quality in NaNoWriMo proper, either, and there's probably less risk of emergent [cryptozoological erotica]( "Computers Write Novels Faster Than You Do", Smithsonian Maganize
Now I have a creeping feeling that all *Stranger* staff will be replaced by bots within the year. I think I'm looking forward to early retirement; maybe then I can finally participate in NaNoWriMo. "Sure, You've Heard of NaNoWriMo, but What About NaNoGenMo?", The Stranger
I wouldn't read the whole thing, but it is fascinating to watch the logic work. More code-generated novels are [right over here]( Or check out the [#NaNoGenMo hashtag]( on Twitter, where people are also discussing their progress. Some of them seem virtually indistinguishable from a certain kind of contemporary novel, à la Tao Lin. Others read remarkably like a sentient person's dream journal. "Sure, You've Heard of NaNoWriMo, but What About NaNoGenMo?", The Stranger
'It's 6:00AM and I'm wide awake. Good friday morning peeps'. This is how the computer-generated 'novel' All the Minutes begins. Programmed by developer Jonathan Puckey, the book documents every minute throughout a 24-hour day by breaking down the giant global stream of peoples' tweets—there are some 6,000 per second—into an automatically-generated collective diary. ... For Puckey, the idea of building a 'novel' out of the Twitter bot's stream was the result of a happy coincidence. When the team caught wind of NaNoGenMo, the National Novel Generation Month, a event organized by the developer Darius Kazemi that's timed to coincide with November's National Novel Writing Month, they decided to jump in. All The Minutes doesn't actually hit NaNoGenMo's goal of 50,000 words: It currently clocks in somewhere around a more novella-like 20,000 words. ... [T]here's something oddly satisfying, hypnotic even, about the project. It doesn't flow from beginning to end, but the text still intrigues, pulling you forward with the steady beat of the clock and the strange rhythm and repetition of thousands of peoples' thoughts. Think of it as an unknowing, crowdsourced version of The Hours—maybe, The Minutes—a portrait of humanity in the midst of its everyday, sometimes mindless moments, and a remarkable testament to the ceaseless stream of data that keeps those of us on the Internet scrolling down. 'It's 2:40 PM And I'm Drunk': The Strange, Voyeuristic Novel Mined From Twitter
NaNoGenMo is not ... truly about trying to replace the human author. Rather, its entries draw their strange beauty and humour from their failure to be human, from their almost-but-not-quite humanity and their utter inhumanity: most of them are transparently machine-made, but this lends their glitches, coincidences and almost-epiphanies even more fascinating. The writing they produce is closest to is the flattened affect and repetitions of alt-lit, with dashes of uncreative writing, flarf and other post-internet poetics. In other words: as humans increasingly write in dialogue with the internet and machine automations, machines are increasingly being written in dialogue with human literature. 9 Computer-Generated Novels You Should Read, or Attempt To, or At Least Look At In Wonderment
November is, of course, National Novel Writing Month. It’s hard to be in any way involved in literature and miss out on all the people updating the world on their wordcounts, their character arcs, their late night coffee binges as they attempt to hammer out 50,000 words of prose in 30 days. But now NaNoWriMo has another competitor: National Novel Generation Month. Because why spend a month writing words when you could instead spend a month writing a computer programme that would write them for you? 9 Computer-Generated Novels You Should Read, or Attempt To, or At Least Look At In Wonderment
NaNoGenMo happens where tech and literature overlap: the strange venn intersection that houses [computer poetry](, [electronic literature](, and [twitterbots]( Novel generation draws from artificial intelligence and the quest to create computers that talk or write like people, but it’s also part of the Oulipian tradition of writing from constraint: if you make such-and-such a ruleset, what kind of writing might happen? Computer generation renders Raymond Queneau’s [Cent mille milliards de poèmes]( beautiful but obsolete, and to my mind [poem.exe]( can hold a 1000 Watt LED candle to Bashō. 9 Computer-Generated Novels You Should Read, or Attempt To, or At Least Look At In Wonderment
NATIONAL NOVEL WRITING MONTH (often abbreviated NaNoWriMo) is an activity [Leon] Wieseltier would likely celebrate — so much human creativity! But what about NaNoGenMo? The programmer and [digital humanist]( Darius Kazemi proposed that instead of writing novels themselves, participants should write algorithmic code that could generate a novel from a given set of parameters. The beautiful results include Liza Daly’s[generated version of the Voynich Manuscript](, an icon of literally untranslatable human achievement. Daly’s creation is a unique book that never existed, was assembled instantly, and will never exist again. How much more human could it be? I would argue that in our supposedly post-human time, poetry is often found in the depths of technology. Who’s Afraid of Robot Culture?
What is interesting about [National Novel Writing Month] is that the novel writing month, acting prophylactically against procrastination, uses two types of constraint: the time limit and the word target. These are reminiscent of the self-limitations typical of conceptual literature. However, these constraints don’t touch upon the formal aspects of the novels, which often end up as fan fiction things or – more augustly – as exactly that type of realism the ‘great novel’ is meant to achieve, even if in reality it is nothing but a simulation of the gestures of seriousness that the literary field considers exemplary of ‘high’ fiction. ... Of course, this form of literature is conceptual in potential only. One could simply add on formal limitations, so as to encourage a flurry of conceptual novels, a yet-to-be founded NaCoNoWriMo. Or one could limit the means of production itself, as did code artist Darius Kazemi. His version is called NaNoGenMo – National Novel Generation Month. Transferring the “creative” from the novel to a novel making code, it lets the machine do the writing. Already for the second time, hundreds of code savvy writers pledged to design scripts and programs that would generate just that 50,000 word novel instead of writing it themselves. (‘Novel’ is understood pragmatically, paratextually: If it’s called a novel, it is one.) The results have been surprisingly varied, and some of them quite extraordinary. In the coming weeks, I would like to look at some of them, hoping to find out something about digital literature, what it is, how it works – and, above all, what it can do for the novel. Algorithmic Empathy: Nick Montfort’s ‘Megawatt’
Some forms of journalism are trivially automated, and these are precisely the kinds that are automated. However, the variety of journalism that journalists are increasingly reaching for (beautiful, literary longform nonfiction, which thrives on the web because of the comparatively low cost of distribution and which stands out heavily from the landscape of low-quality under-considered short posts) is both far from the grasp of the current generation of text generators and far from the aim of NaNoGenMo in specific. The hidden benefits of NaNoGenMo
On November 1st of 2015, NaNoGenMo begins its third year. It’ll be the third year that I’ve participated, and the third year that it’s spawned articles in legitimate paper magazines and newspapers, none of which are, unfortunately, particularly distinct from the coverage of the story generator Brutus in 1999 in the New York Times or similar projects from years prior. Media coverage seems to circle around the spectre of wholesale automation of authorship the way that hapless space-ships circle around a black hole. (Because we, as a community, have an interest in corpora — the ability to access and analyse data makes inserting variety into generative writing convenient — we have kept track of these articles.) Perhaps, being written by journalists, these articles are justified in having a bit of a hysterical bias. After all, certain classes of news stories are already being written mostly by software, and fear-mongering about automation has been a lucrative staple of the press since the invention of the automatic loom. The hidden benefits of NaNoGenMo
NaNoGenMo produces, quite consistency, a flurry of extreme creativity and a wide variety of aims, styles, and implementation techniques; many people start several entries with extremely different approaches and goals, and many people do not end up producing a novel-length text despite the utterly trivial requirements, because their amazingly creative techniques were unable to produce a novel whose originality they could be proud of. In its first year, we had (among other entries) a novel composed of a supercut of similar tweets, a novel composed of a supercut of Homeric fight scenes, and a mystery novel composed of the belabored meanderings of Alice and Bob in a labyrinthine house; in its second year, we got a deeply atmospheric comic book composed by pulling images from flickr, post-processing them, and superimposing thematically related lines from detective novels, as well as a wonderful book-length piece of asemic writing. This year — who knows? The hidden benefits of NaNoGenMo
The Royal Society of London in the 17th and 18th centuries independently rediscovered many of the things already known to professional craftsmen of the physical sciences like doctors, midwives, miners, and sailors; nevertheless, by aiming to measure and control their experiments, they became the vanguard of systematic knowledge of the physical world, which made later developments easier to isolate and demonstrate. NaNoGenMo can be seen as doing the same for the craft of literature: by producing machinery that consistently executes particular literary techniques, we can produce large amounts of stylistically consistent text; we can perform systematic mutations of text; we can isolate important elements by seeing how text affects people with a level of purity and consistency and volume not possible with human-written text. The hidden benefits of NaNoGenMo
Explicitly experimental techniques appear to produce the best results. This makes sense — experimental techniques tend to be very well-defined, and the results of experimental techniques in literature as executed by human beings tend to be dominated by the attributes of the techniques themselves (meaning that, were a machine to execute those same techniques, the results would be superficially very similar). We haven’t progressed to a level of understanding of the craft of writing that allows us to automate good, readable, page-turning fiction — and I doubt that even an author of best-selling potboilers has such an explicit model. As a result, our community is less Clairion and more Oulipo. Nevertheless, each year, we produce works that inch closer and closer to readable. We produce vast novelty with the (eventual) aim of mundane novelty. As a result, it may be most sensible to consider NaNoGenMo to be an amateur expedition into the greater control and quantification of literature. The hidden benefits of NaNoGenMo
[We are ... holding engineering discussions about things like plot and style.](!topic/generativetext/hMy90EyKVrA) We’re determining whether, given some N major plot events, any ordering of those N events can be made sensible via transitions. We’re determining whether macro-level plot beats produce a greater impression of novelty than sentence- and paragraph-level variation in structure, and whether either of them produce a greater impression of novelty in human readers than variation in word frequency. We’re trying to figure out how much novelty is not enough and how much is too much in the context of texts of different lengths. We’re talking about how to engineer the eliza effect in readers. We’re figuring out whether or not readers can identify descriptive fluff, and whether or not they care — and whether or not Ray Chandler was lying about how he structured detective novels, whether the Hero’s Journey really is too vague, and whether the beats in Save the Cat can truly produce compelling stories with minute-by-minute granularity at a feature-film scale. The hidden benefits of NaNoGenMo
You can make the argument that [NaNoGenMo] will eventually lead to the possibility of fully automated journalism. But, being possible is not a particularly compelling argument for it to be likely. Even relatively crappy chess computers can now completely outclass chess grand-masters — and so we have augmented chess, wherein a human grand-master works hand in hand with a chess-playing machine to play against another grand-master-and-machine tag-team. Items like furniture are much better manufactured by machine (in terms of quality, price, and environmental impact), and yet we pay much more for artisanal furniture made by obsolete and wasteful processes because we value the idea of a human being doing something that doesn’t need to be done and doing it the hard way. The hidden benefits of NaNoGenMo
In the same way that there is a market for artisanal wicker chairs and artisanal bread, there will probably continue to be a market for artisanal journalism — and for the rest of us, human journalists may become symbiotes joined at the hip with machines that automate the less interesting parts of the job. We already have some such mechanisms — spell check, grammar check, layout tools, note-taking and mind-mapping and automatic summarization tools. Tools for augmenting creativity in authors aren’t new either — cut-ups pre-date digital computers, as do markov chains and bibliomancy, and oblique strategies are now half a century old. Cutups and markov chains actually produce text for you, to which you must act as editor; but all these ‘writing machines’ that augment creativity do so by acting as a source of semantic randomness, much as mind-warping drugs do. We accept the use of all these mechanisms already — we don’t criticize Thom Yorke or William S. Burroughs for using cut-ups any moreso than we criticize John Lennon or Hunter S. Thomson for using LSD. Automatic methods for the production of text will, if they gain acceptance among writers, gain as much acceptance among readers as spell check and LSD. NaNoGenMo probably won’t produce the future journalism-symbiote I describe, in the same way that NaNoWriMo has never produced the great american novel; but, just as NaNoWriMo produces novelists (and published novels), NaNoGenMo will produce some of the figures and technologies and domains of collective knowledge and culture that will inform text generation in creative fiction in the near future. The hidden benefits of NaNoGenMo
But business aside, did you know machines are also writing novels? [Darius Kazemi]( just posted an invite on github for this year's algorithmic writing contest, [National Novel Generation Month]( One 2014 highlight was [Twide and Twejudice](, with Jane Austen's original dialogue replaced by words from a similar context on Twitter. Modifying an existing novel is a far cry from writing a novel from scratch, but it seems possible that in 2016 or 2017, a machine may write a novel we want to read! We plan to play, so stay tuned for results! Fast Forward Labs Newsletter - November 2015
It is a commonplace that computers will only do what human beings tell them and that they require clear, unambiguous instructions. In practice, however, instructions that are simple and clear from a human perspective can be nearly impossible to translate into a form that a computer can execute. Nowhere is this truer than in the computational processing of language. It may seem like a simple matter, for instance, to split a document into sentences, but this turns out to be an enormously difficult programming problem when dealing with English prose. Since the period is used for multiple purposes—both ending sentences and indicating abbreviations like “Mr.”—it is necessary to come up with an algorithm for determining which periods indicate the end of a sentence. In general, it is not possible to do this with 100% accuracy; the best algorithms available can only guess. Quotation marks pose further issues. While humans can understand punctuation without much trouble, this sort of convention does not jibe at all well with the way computers work, making what seem like simple tasks require complex methodology. I encountered this sort of difficulty myself in a project that I did for [National Novel Generating Month]( This annual contest, a spin-off of [National Novel Writing Month](, challenges people to write a computer program that generates a novel of 50,000 words or more. While some entrants make earnest attempts to computationally generate plots, the entries are mostly more in the vein of conceptual art; texts that are not necessarily readable in a normal way, but that comment on the algorithms underlying them. The Complexity of Machine Writing
For my entry, I decided to do something that seems like it would be simple: take the text of an existing novel and replace every word with a synonym. I especially wanted to see what would happen if I did this with the work of an author known for being particularly precise in the choice of words; for this purpose, I chose the text of Henry James’s Portrait of a Lady. But what a human being, equipped with a thesaurus, could follow this procedure without much trouble, it turns out to be nearly impossible for a computer to get it exactly right. ... The comic effect of the errors computers make is, perhaps, the most original aesthetic contribution of digitally manipulated text. No computer-generated novel that I know of has come close to producing the sort of emotional effects of real fiction, but this peculiar form of art is much more effective as a means of commenting on the ways computers handle natural-language text. As much work has gone into these technologies there remains an immense and perhaps permanent gap between the way they work and the way language works in a literary text. Putting the two together reveals how funny, bizarre, and sometimes even scary machine intelligence can be. The Complexity of Machine Writing
Technical constraints explain why NaNoGenMo has come to align itself with poetics of recontextualization and reassembly. Indeed, genuine NLG algorithms, that is, those that can build words and syntax from the building blocks of letters and get smarter over time, are still very nascent. Most of the 2014 submissions instead use rules to transform former texts in creative ways, which also leads to topical similarities. NaNoGenMo: Dada 2.0
While open to anyone and, as in NaNoWriMo, governed by the single constraint that submissions contain at least 50,000 words, NaNoGenMo is gradually defining itself as a cohesive artistic movement that uses algorithms to experiment with literary form. The group’s identity is partly generated by ressentiment towards negative criticism that their “[disjointed, robotic scripts](” are “[unlikely to trouble Booker judges](” Last year, [one participant]( mocked how “futile it is to try to explain what we’re actually doing here, to the normals.” More positively, they are shaping identity through shared formal and critical resources. John Ohno (alias [enkiv2]( posted code to generate sestinas, haikus, and synonyms. Allison Parrish (alias [aparrish]( shared an interface to the [Carnegie Mellon Pronouncing Dictionary]( that enables users to do things like scrape the dictionary for rhymes for a given word. Finally, Isaac Karth (alias [ikarth]( explained to members how the group’s tendency to assemble new poetry from prior texts has intellectual roots in Dadaism, Burrough’s cut-up techniques, and the constraint-oriented works of Oulipo. When I spoke with Kazemi about the project, he said that Ken Goldsmith’s Uncreative Writing had inspired his thinking on how NaNoGenMo can challenge customary notions of authorship and creativity. NaNoGenMo: Dada 2.0
The latest developments in machine learning are enabling machines to develop models of us in turn, ever updating what information they present and how they present it to match the input we provide. Kazemi is addressing this new give and take between man and machine head on in his 2015 NaNoGenMo submission, “co-authoring” a novel with an algorithm where for every ten sentences the algorithm drafts, he only commits the one he, as human, likes best. “Who wrote the book?” he asks. “[The algorithm] wrote literally every word, but [I] dictated nearly the entire form of the novel.” This is the same kind of dynamic new research tools built on IBM Watson are presenting to lawyers and doctors: [ROSS](, a legal tool built on the Watson API, presents answers to research questions, and all the lawyer has to do is to commit the answer she likes best. If NaNoGenMo helps us think more deeply about that dynamic, it can offer very important insights on the overall future of AI. NaNoGenMo: Dada 2.0
Buckenham tells me that [an] aspect of Twitter bots is the enjoyment of play-acting that these bots are people. He tells me about the #botALLY hashtag, which draws members of the bot community under the playful banner of friends-of-bots. “I don't think it's as successfully impersonating a human, it's more just existing on an equal footing as a human – that the tweets are no less important than a human's tweets,” Buckenham tells me. “It's not a second class thing. The idea that Twitter is a commons that you can share with these alien, non-human entities that have their own rules. Where you treat them seriously as humans and play acting that they have rights and responsibilities. It's all tongue in cheek, but at the same time it's more interesting to engage with things that way than dismissively I think.” One project, NaNoGenMo, takes this playful approach and runs with it. Instead of NaNoWriMo (National Novel Writing Month), which aims to help people write a 50,000 word novel in one month, NaNoGenMo (National Novel Generation Month) encourages users to spend the whole of November writing code that generates a 50,000 word novel. The result is often a Borgesian cacophony of possible words and characters. One resulting project, [Alphabetical Order by Leonard Richardson](, was generated by searching 47,000 plain-text public domain works for lines that contained no alphanumeric characters. The art of the Twitter bot
NaNoGenMo is like NaNoWriMo, except instead of writing a book over the course of a month, programmers create a code that generates a novel. It’s not so much interactive fiction as fiction that has been pulled kicking and screaming from random repositories of information. If anything, it’s a good excuse to make some clever nonsense. Free Loaders: Requiem Flora Dream
[Cartography of Known Spaces]( by Loren Schmidt. Purveyor of tantalizing [work-in-progress tweets](, Loren Schmidt, has created some kind of astronomy and coding miscellany that has all its creator’s usual hallmarks of mystery and maths. I won’t pretend to understand the algorithms behind this composition, but it sure does look neat. One of the codes takes apart images of the moon’s surface (pictured above) and attempts to recombine them in a small scale simulation of “human memory”. Obviously, the moon soon dissolves. Free Loaders: Requiem Flora Dream
[Around the World in X Wikipedia Articles]( by Kevan. Kevan (of browser game Urban Dead fame) created a novel using Wikipedia’s API and Jules Verne’s Around the World in 80 Days. Here is an extract: “Passepartout and I walked to Metro Central Heights. Passepartout told me it was originally known as Alexander Fleming House. It was clearly not known at the time of construction. Passepartout was unimpressed by some 400 studio to three-bedroom flats which are in constant demand. We met Ernő, a college friend of mine who was passing by.” Free Loaders: Requiem Flora Dream
But maybe this contest just reflects our evolution towards a more technological society. For the last 16 years November has seen “National Novel Writing Month” (or NaNoWriMo), a free event challenging amateur writers to compose a 50,000-word novel before December 1st. But two years ago it was suddenly joined by this companion event for artistically-inclined computer programmers, dubbed NaNoGenMo — drawing some suitably geeky jokes on Twitter. It’s an irresistible challenge for a certain kind of creatively-inclined geek “This sounds like a great idea…” read one of the responses to the contest announcement. “How can anyone not take part?” Computers Get Busy for National Novel-Generating Month
For example, one AI-assisted author generated a narrative called “The Cover of The Sun Also Rises” that’s even more spare and concise than Ernest Hemingway’s original. “Brass. Brass. Brass. Brass. Brass. Drab. Drab. University of California Gold. Brass. Brass. Dark tan…” “I took a picture of the cover of “The Sun Also Rises,” converted it to a PNG and then decoded the PNG and for each pixel got the nearest named color,” the author wrote on [his novel’s official GitHub issue page]( “It’s 800 chapters long and 803,218 words (according to wc). There’s also an audiobook version that’s 173 hours and like 2.5 gigs.” You can hear a delightful sample on [the novel’s official web page]( And the first comment on GitHub pointed out that “Chapter 786 includes a sentence ‘Black, invisible.’… It looks like your image had exactly one transparent (alpha-channel=0) pixel! This may be the highlight of the entire novel. “I couldn’t read 800 chapters of this, so I coded a script to do it for me. Consider this the Cliff’s Notes version,” they wrote, posting an image of….the cover of “The Sun Also Rises.” Computers Get Busy for National Novel-Generating Month
Entries are made by opening an issue [on the event’s GitHub repository](, which in effect serves as an intention to participate. This year saw a total of 188 “issues,” with intriguing titles like “The Hero with Arbitrarily-Many Faces,” “THE CYBERWHALE – a cyberpunk version of Moby Dick,” and “Terms and Conditions – a Legal Thriller.” The publicly-readable works were then linked to within those comments — with much of the novel-generating code also hosted on GitHub — and some fascinatingly geeky discussions ensued, all taking place as GitHub comments. Computers Get Busy for National Novel-Generating Month
[P]erhaps the most iconic tweet came from a Python developer named Jason Veatch, who works at MailChimp. In a world where computers can now generate novels, he found himself torn between the fiction-writing event and the coding one! “I was planning to start the actual NaNoWriMo today! Now I don’t know.” “I can’t do both…!” Computers Get Busy for National Novel-Generating Month
Writing novels that change forever the face of literature, it is overrated: you only have to see the top sales in any Fnac to be convinced. But can we go so far as to do without writing and handing over literature to lines of code? This is the principle of NaNoGenMo, for National Novel Generation Month. Inspired by NaNoWriMo, a contest that invites authors every year to write a novel of 50,000 words in a month, NaNoGenMo reproduces the idea and applies it to content generated by programs. NaNoGenMo : pourra-t-on générer automatiquement le prochain prix Goncourt?
[The Gamebook of Dungeon Tropes]( produced a totally plausible high fantasy choose-your-own-adventure book: 'Throughout your journey in these lands, you’ve heard subtle tales of a spreading shadow that grow more and more threatening as you get closer to the village of Nuria. The stories tell of Ir, a horrifying green dragon whose foul magic is spreading throughout the air and water and poisoning the countryside. The villagers beseech you to help fight this menace before the darkness takes its toll.' 500 computer-generated novels: the Nanogenmo 2015 entrants
Then there's The X Days of Christmas, a songbook with 165 verses, such as 'One hundred and sixty-one oblati in crackpottery Santas', and 'One hundred and twenty-eight acephala ventriloquizing'. 500 computer-generated novels: the Nanogenmo 2015 entrants
Other branches upon which I lit and flittered away some of my morning: [The Cyberpunk Corporation Generator]( ([50,000 words' worth of same](, [The Book of Eliza]( (plausible Old Testament tedium); [The Tale of the Github Repository]( (turning commit messages into a story); [Around the World in X Wikipedia Articles]( ('Drifting west-to-east through clusters of Wikipedia's geolocated articles, starting and ending at London's Reform Club, and describing locations using fragments of the text available in each article along the way'). For the Borges fan: [Encyclopedia Of The Useless]( ('Chapter I: Words Of The Useless,' 'Chapter II: Numbers Of The Useless,'' etc). [Waiting for Gobot]( Automated Twitter adaptation of Beckett. 500 computer-generated novels: the Nanogenmo 2015 entrants
For programmers, there are many interesting things about NaNoGenMo even if no breakthroughs in AI are expected. (The point of an exercise like this isn’t that it’s done well, but that it’s done at all. A month is not enough to build a robust system, but it is enough to experiment with and prototype new approaches for generating fifty thousand words of intelligible text. The value of a compressed time frame for experimentation is something that the participants of NaNoWriMo can well appreciate.) Another Word:Let's Write a Story Together, MacBook
It’s true that most of these novels are barely readable. Even the best entries are perhaps only interesting as “stories” because of our apophenia and our desire for the text to succeed—reading, after all, is a participatory exercise of joint meaning-creation between the reader and the text. ('Why is there an air conditioning unit floating in space? Never mind, I’ll just go with it.') But with these generated narratives, the reader usually gives up within a few paragraphs because the effort is too great and one-sided—the text does not read back. As Pressey notes in his project, “It is very difficult for the average person to read a typical NaNoGenMo-generated novel in its entirety, from beginning to end. It’s because the brain begins to tire, right? It gets all ‘I see what you did there’ and balks at facing yet more unpredictable stuff.” But being smug about our superiority as human writers isn’t the point. It’s true that machine novelists are unlikely to displace human writers any time soon (though news organizations like the AP have already been [using machines instead of humans]( to write data-driven financial news stories). But machine generation of text doesn’t have to be capable of replacing all human creativity to be interesting or useful. At its heart, NaNoGenMo is about play: playing with text, playing with notions of literature and narrative, playing with authorship and creativity and appropriation and recontextualization and the structures for constructing meaning. Another Word:Let's Write a Story Together, MacBook
Computer text generation, even in its present state, is quite capable of coming up with [fresh associations]( and almost-sensible ideas when seeded with human input. Freed from the constraints of “meaning,” the algorithm is capable of juxtapositions and combinations of styles and situations that would never occur to human authors. The human mind, on the other hand, can work with this raw material and provide creative and editorial direction. Indeed, this is gestured at by Darius Kazemi’s own entry in [2015]'s NaNoGenMo: [Co-authored Procedural Novel](, in which Kazemi proposed the following: 'Thought experiment: you and I are playing a game. I write ten opening sentences for a novel, and you pick the one you like best and let me know; that becomes the opener. Then I write ten second sentences for the novel. You pick what you like best and let me know. Et cetera. Who wrote the book? I wrote literally every word, but you dictated nearly the entire form of the novel. I plan to act as sentence-by-sentence editor for an algorithm (or set of algorithms) where I review something like 5,000 multiple choice questions and hand pick each sentence of the novel.' Ultimately, Kazemi chose to go in another direction, but the possibilities glimpsed in this thought experiment are very exciting. Computers may yet one day write The Great American Novel, but before then, they certainly can be partners for human authors as we write more interesting novels together. In fact, I think I’m going to propose a project like this to my editor (assuming my laptop agrees . . . ). Another Word:Let's Write a Story Together, MacBook
Many NaNoGenMo projects remind me of Oulipian techniques crossed with “found-language” conceptual works by artists like Kenneth Goldsmith, but as Isaac Karth points out in [Virgil’s Commonplace Book](, appropriation is at the foundation of the Western Classical tradition, and perhaps all literary traditions. Many of NaNoGenMo algorithms rely on large corpora of texts in the desired genre to provide the verisimilitude in style, diction, and structure in the output, but is that really so very different from how writers learn to write in a genre by reading widely in it? We absorb the rules of what a “good story” is by reading examples of such stories, and everything we write echoes our reading, consciously and unconsciously. It’s easy to wax philosophical about how reading machine-generated text changes how we think about literature, and there are many thoughtful pieces written on the subject already (I particularly recommend “[NaNoGenMo: Dada 2.0](” by Kathryn Hume). But I want to turn in a more practical (as well as appropriately speculative) direction: does NaNoGenMo offer any hints on how machines can perhaps help us write better novels? Many of us are deeply interested in the process of storytelling, and since the best way to understand a subject is to try to teach it, it stands to reason that in constructing narrative algorithms, we may also gain insight through modeling the writer’s process. Another Word:Let's Write a Story Together, MacBook
Every November (starting from 2013), programmers participate in a competition called National Novel Generation Month; the goal is to write a fictional novel of 50,000 words or more. Some of these generated novels are generally dull, but readable (examples: “[Around the World in X Wikipedia Articles](”, “[A Time of Destiny](”, “[Simulationist Fantasy Novel](”). They have the plot, characterization, and imagery that you would normally associate with a human-written work. Programmers will have to put in more effort for computer-generated novels to be on-par with human-produced literature, but there does not seem to be any inherent limit to algorithmic creativity. Why Robots Will Not (Fully) Replace Human Writers
Humans take for granted their ability to perceive the world. Their five senses gives a continual stream of data that humans are able to quickly process. Bots, on other hand, are only limited to the 'raw data' that we give them to process. They will not 'see' anything that is not in the dataset. As a result, how the bots understand our world will be very foreign to our own (human) understanding. For some people, this is actually a benefit that bots bring to writing. Bots will not have the same biases as human beings. They will therefore discover new insights and meanings that humans may have overlooked. However, bots will instead bring their own unique 'biases' and issues into their work, and humans may not tolerate the biases of algorithms as much as they would tolerate the biases of other humans. Humans will, of course, still happily read what the bots have to say. But they also want to read what humans have to say too. Why Robots Will Not (Fully) Replace Human Writers
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