Lecture 09: Ethics (FSDL 2022)
In this lecture, we cover the ethical dimensions of building ML-powered products: past and present tech ethics, present and near future ML ethics, and future AI ethics.
0:00:00 Overview and Context
0:05:32 Themes: Alignment, Trade-Offs, Humility
0:13:04 The Tech Industry's Ethical Crisis
0:19:00 Tracking carbon emissions
0:22:35 Deceptive design and dark patterns
0:29:51 Why is ethics more salient in ML?
0:32:50 Is the model fair?
0:42:39 Representation and ML
0:47:08 Is the system accountable?
0:52:59 Who owns the data?
0:57:10 Should this be built at all?
1:01:03 Medicine leads the way on responsible ML
1:10:09 AI Snake Oil and AI Ethics
1:14:32 Frontiers: AI Rights and x-risk
1:19:35 What is to be done?
1:21:59 Coda: building ML well and building ML for good
Detailed notes and slides: https://fullstackdeeplearning.com/cou...
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