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?
- Lecture: Introduce the Q1 (replication) project objectives, the AI Fairness 360 model overview, and the medical expenditure tutorial
- Workshop: Initiate logistics for the replication project: datasets, code repo, and setup. A brief overview of EDA.
Pre-Class Readings
Please read the following:
- Inherent Trade-Offs in the Fair Determination of Risk Scores (Kleinberg et al.)
- Who Audits the Auditors? (Costanza-Chock et al.)
- 2023 AI Now Report (read pg. 34-42)
Participation Questions
- Submit default participation to gradescope by 2:00pm Monday October 14th.
- Complete the below write up #3 assignment MINUS the writing portion. No writing needed.
- Write up #3
- Send screenshots of a set up environment or you pulling in the data in a notebook.
- Note: These tasks will be difficult, and will potentially take a while to compute, so start early!
This Week’s Slides
Replication Project
- Review Replication Part 01 and complete “Section 1,” which contains discussion questions at the end.
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Try to get EDA done and get started on the rest of section 1 if you have time. Deadline is October 22 by class.
Assigned for Week 03
- EDA on data - submit notebook to mentors.
- Default participation assignments due following monday.
- Spend time reviewing EDA and meeting with your group.
- Prepare your team to collect meeting notes, we will be asking for recaps in class.
- Note: These tasks will be difficult, and will potentially take a while to compute, so start early!