CS 512 - Ethics of Computing and AI
Graduate Course · Spring 2026 · Instructors: Judy Gichoya and Joyce Ho
Course Description
The rapid evolution of computing innovations from social networks and microblogging to artificial intelligence (AI), autonomous vehicles, and generative AI has ushered in transformative technologies that reshape our society. This graduate-level course examines the ethical, societal, and policy implications of emerging computing and AI technologies. Students will develop frameworks to critically assess whether these technologies create more benefit than harm by exploring fundamental principles from computing, AI, policy, ethics, medicine, and social sciences.
Course Philosophy
Ethical reasoning about technology must be practical, not purely theoretical. This course is anchored in the evolution of medical ethics, a field that has long grappled with questions of harm, consent, autonomy, and accountability, and uses it as a mental model for navigating the rapidly shifting landscape of AI and emerging technologies.
As ethical reasoning often necessitates dialogue, the course is structured to maximize it. Classes are flipped, with case-based studies not only grounding the context but serving as the mechanism for discussion and discourse. Students also take on the role of teachers to bring different perspectives to the course. This is complemented with direct engagement with the technologies themselves where students reflect critically on first-hand use.
Schedule
| Lesson | Readings | Assignments |
|---|---|---|
| Lesson 1Introduction | ||
| Lesson 2Virtue Ethics | ||
| Lesson 3Utilitarianism |
| |
| Lesson 4Utilitarianism & Deontology | Group Assignment on the advent of software company's annual year-end feature | |
| Lesson 5Additional Ethical Frameworks (e.g., Feminist, Communitarian) |
| |
| Lesson 6Fairness | ||
| Lesson 7Data Privacy / Data Consent | ||
| Lesson 8IP / Plagiarism | Group Assignment on creation of two AI-generated videos | |
| Lesson 9Accountability | ||
| Lesson 10Economic Sustainability | ||
| Lesson 11Environmental Sustainability | Final Project (AI co-scientist) Proposal | |
| Lesson 12Autonomy | ||
| Lesson 13Agency | ||
| Lesson 14Business of AI / Software | ||
| Lesson 15AI Safety and Alignment | Group Assignment on red teaming for mental health AI safety | |
| Lesson 16Taking Back Your Data | ||
| Lesson 17Re-visiting Data Consent | ||
| Lesson 18Class-Led Discussion | ||
| Lesson 19Class-Led Discussion | ||
| Lesson 20Class-Led Discussion | ||
| Lesson 21Class-Led Discussion | ||
| Lesson 22Class-Led Discussion | ||
| Lesson 23Class-Led Discussion | ||
| Lesson 24How Robots and Agents Changed in Two Months |
| Final Project Report |
| Lesson 25What Does it Mean to be Human in the Age of AI |
| |
| Lesson 26Final Project Presentations |
Assignments and Grading
The final grade will be determined by a weighted average of all the graded items.
| Component | Type | Weight |
|---|---|---|
| Participation + Reading Exercises | Individual | 20% |
| Leading In-Class Discussion | Group | 20% |
| Peer Evaluation of In-Class Discussion | Individual | 10% |
| 3 Assignments | Group | 24% |
| Final Project | Individual | 26% |