Ethical Issues in AI

A CMU Osher Course

John Hooker, Study leader

Tuesdays 12:45 – 2:15 pm
6 classes: Jan 14 – Feb 18
Online via Zoom

Course description Study leader bio

Course Outline

Click the links to view or download slides (as pdf files) used in class.
Links are added a day or two before the class in which the slides are used.

	Slides	Topics
Module 1	Introduction	Course objectives
Module 2	What is AI?	Essence of AI; AI hype; Beneath the hype; AI technologies; ML is not magic; Overfitting; Trial and error
Module 3	Why ethics?	Ethics as a negotiation tool; Ethics and religion; Ethics and rationality; Facts and values
Module 4	Ethical principles	Basic assumptions; Generalization principle; Human decision making; Utilitarian principle; Autonomy principle; Case study: Ford Pinto
Module 5	Self-driving cars	The future of cars; AVs on the road; The Moral Machine and value alignment
Module 6	Content moderation	Recommender systems; Case study: Inciting violence; Case study: Impact on young people
Module 7	Bias in AI systems	Example: Mortgage decisions; What to do about bias? Assessing bias metrics
Module 8	Online privacy	Surveillance; Privacy and utility; Privacy and generalizability; Privacy and culture; Privacy and autonomy
Module 9	Generative AI	Language models; Generative adversarial networks; ChatGPT etc.; Ethics of GPTs
Module 10	AI and intellectual property	Plagiarism; Intellectual property; Natural property rights; Ethical analysis of IP; Movement away from IP
Module 11	Technological unemployment	Future of employment; Wealth distribution; Worker ownership; Augmentation; A firm’s ethical dilemma
Module 12	Robots as agents	Autonomous robots; Duties to machines; Duties of machines; Robot masters? Responsibility; Living with machines; Robots vs androids; Robots as agents