Course Design and Outline

Tue, 11 Aug 2026 00:00:00 +0000

STOR 323I (Fall 2026)

Machine Learning: Ethics and Society

Course overview

This course examines the ethical, social, and technical challenges arising from modern machine learning (ML) and artificial intelligence (AI) systems. It connects technical foundations—including supervised learning, online learning, multi-agent modeling, and game theory—with philosophical frameworks such as consequentialism, deontology, and virtue ethics.

The course emphasizes the tension between algorithmic decisions and societal impact, training students to critically evaluate and design responsible ML systems.

Course website

for current materials, discussions, and course information. This page summarizes the course’s learning goals and design.

Learning goals

Analyze ethical dilemmas in ML and AI systems.
Understand technical tools used to address these issues.
Evaluate real-world deployments and their societal consequences.
Communicate technical and ethical arguments clearly.

Course structure

1. Moral pitfalls of machine learning

Introduction to moral philosophy
Foundations of machine learning
Bias, fairness, privacy, and accountability
Online learning and feedback loops

Human factors in ML systems
Game theory and strategic behavior
Social choice, equilibrium, and mechanism design
Platforms and recommender systems

3. Generative AI: challenges and opportunities

Generative AI and large language models
Aligning AI systems with human values
Ethical and societal implications of generative AI

Course design

This is an interactive, discussion-driven course. Students should expect structured debates, case studies, technical exercises, and a team project addressing a contemporary issue in responsible machine learning.

Tools and materials

Programming: Python
Writing: LaTeX (Overleaf recommended)
Materials: Open-source readings, lecture slides, and notes

Course materials and discussions are available through the ; some materials may require course access. Submissions and grades are provided through .

Policies and evaluation

For the current schedule, evaluation details, and course policies, consult the course website and Canvas.

STOR 323I -- Machine Learning: Ethics and Society (Fall 2026) |