Data Ethics Markmap

markmap.md

Data Science and Ethics

1. Fundamentals

1.1 What is Ethics?

1.2 Why is it needed?

1.3 History of Ethics

1.4 Ethics Concepts

1.5 Ethics Principles

1.6 Explore: Responsible AI

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2. Data Collection

2.1 Ethics & Data Ownership

2.2 Intellectual Property & Rights

2.3 Human Consent & Oversight

2.4 Data Validity (Quality)

2.5 Data Diversity (Representation)

2.6 Explore: The 5Cs Framework

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3. Data Privacy

3.1 Ethics & Data Privacy

3.2 Degrees of Data Privacy

3.3 Anonymity & De-Identification

3.4 Data Leakage & Misuse

3.5 Transparency & Regulation

3.6 Explore: Case Studies

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4. Algorithm Fairness

4.1 Fairness & Bias (Types)

4.2 Unfairness & Harm (Types)

4.3 Data Misrepresentation

4.4 Algorithm Explainability

4.5 Mitigating Bias

4.6 Explore: Case Studies

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5. Tools & Frameworks

5.1 Ethics-Driven Culture

5.2 Code of Conduct

5.3 Ethics Checklists

5.4 Industry Frameworks (AI)

5.5 Regulatory Frameworks (Governance)

5.6 Explore: 97 Things About Ethics

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6. Summary & Resources

6.1 Learn: Data Lifecycle

6.2 Apply: Ethical Principles

6.3 Adopt: Ethical Culture

6.4 Verify: Ethics Checklists

6.5 Explore: Case Studies

6.6 Explore: Research Projects