A Multi-Stakeholder Perspective on Ethical AI

Class Coverage

• What are the main doctrines and frameworks of AI fairness?
• How does responsible AI affect different fields?
• How do ethical considerations affect different stakeholders?
• What are some limitations to ethical AI?

Pre-Class Readings

Please read the following:

• Inherent Trade-Offs in the Fair Determination of Risk Scores (Kleinberg et al.)
• Machine Bias (ProPublica)
• Response to ProPublica (Northpointe)
• Who Audits the Auditors? (Costanza-Chock et al.)
• 2019 Report (AI Now)
  • You don’t have to read the whole thing - just pick one section and use it to answer the participation questions

Participation Questions

Submit to Gradescope by 10AM PT on Thursday, October 6

• Provide an example (other than COMPAS) of a classification use case where a false negative and a false positive have different impacts on different groups. Describe the impacts.
• Select one of the use cases discussed in AI Now’s 2019 report. Describe as many stakeholders as you can think of (they may not be mentioned in the report) and what impact the AI use case may have on them.

This Week’s Slides

• Week 02: A Multi-Stakeholder Perspective on Ethical AI

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Assigned for Week 03

• Sign up for an in-class brief if you haven’t already
• Complete next week’s readings
  • If you signed up to present on “Datasheets for Datasets” (Gebru et al.) or “AI Fairness 360” (Bellamy et al.) come prepared to present next week and submit your presentation on Gradescope by 10AM PT on Friday, October 14
• Submit your answers to next week’s participation questions to Gradescope by 10AM PT on Thursday, October 13
• Submit your response to Writeup #2 to Gradescope by 10AM PT on Friday, October 14 Wednesday, October 19

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