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%
AI Tool Policy. You may use generative AI tools such as Co-Pilot and ChatGPT in the same manner as an Internet resource. You must credit the interaction source. You are not allowed to solicit direct answers or duplicate responses from these tools. You may not use any generative AI writing assistants to create the "written aspects" of the assignments and final project.