Algorithmic decision making for social good

IEOR E8100 • Spring 2026 • Columbia University

Introduction

AI and algorithmic decision-making systems are increasingly built and deployed in practice, with many purporting to “do good”. In this course, we’ll investigate what “good” looks like, what the right problems are to work on, and discuss considerations for the effective design and deployment of algorithmic decision-making systems. We'll look at both avoiding unintended harms as well as moving towards desirable, socially beneficial outcomes. Along the way, we’ll study algorithms across machine learning, optimization, market design, and reinforcement learning applied to societal problems spanning sustainability, education, healthcare, and government operations.

Course details

Instructor:
Lectures:
Mon/Wed 11:40-12:55pm
Location:
Mudd 327
Office hours:
Mon 1–2pm in Mudd 312

Grading

There are no formal prerequisites, but this course expects mathematical maturity and ability to engage with state-of-the-art research from operations research, computer science, and other disciplines.

Schedule

Please note that this schedule is subject to change.

Week Date Topic & readings
Introduction
Week 1 Wed Jan 21
What problems to work on? and course introduction
Bonus:
Week 2 Mon Jan 26
Whom to involve?
Building the right model
Wed Jan 28
Modeling decisions
Week 3 Mon Feb 2
Modeling potential
Wed Feb 4
Modeling pitfalls
Week 4 Mon Feb 9
Modeling with foundation models
Application domains: Sustainability
Wed Feb 11
Sustainability I: Optimization
Bonus:
Week 5 Mon Feb 16
Sustainability II: Mechanism design
Considerations for decision making
Wed Feb 18
Allocative harm, representational harm, and procedural harm
Bonus:
Week 6 Mon Feb 23
OR for fairness
Wed Feb 25
Deliberative processes
Bonus:
Application domains: Healthcare
Week 7 Mon Mar 2
Healthcare I: Optimization
Wed Mar 4
Healthcare II: Online learning and reinforcement learning
Bonus:
Week 8 Mon Mar 9
No class
Wed Mar 11
Project pitches
Mar 16–20
Spring break
Deployment
Week 9 Mon Mar 23
Designing for people
Wed Mar 25
Human-AI complementarity
Week 10 Mon Mar 30
Working with practitioners
Wed Apr 1
Sustaining a deployment
  • TBD
  • TBD
Application domains: Nonprofit & government
Week 11 Mon Apr 6
Nonprofit operations
Wed Apr 8
Government operations
Evaluation
Week 12 Mon Apr 13
Claiming causality
Wed Apr 15
Claiming generalizability
Week 13 Mon Apr 20
Evaluations and impact
Application domains: Education
Wed Apr 22
Education I: Optimization
Week 14 Mon Apr 27
Education II: Prediction and mechanism design
Bonus:
Wed Apr 29
Project presentations
Week 15 Mon May 4
Project presentations

Resources

Relevant organizations

Additional readings