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Overview and Context
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Classroom Contents
Ethics - FSDL 2022
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- 1 Overview and Context
- 2 Themes: Alignment, Trade-Offs, Humility
- 3 The Tech Industry's Ethical Crisis
- 4 Tracking carbon emissions
- 5 Deceptive design and dark patterns
- 6 Why is ethics more salient in ML?
- 7 Is the model fair?
- 8 Representation and ML
- 9 Is the system accountable?
- 10 Who owns the data?
- 11 Should this be built at all?
- 12 Medicine leads the way on responsible ML
- 13 AI Snake Oil and AI Ethics
- 14 Frontiers: AI Rights and x-risk
- 15 What is to be done?
- 16 Coda: building ML well and building ML for good
