Algorithms and Social Justice

Algorithms and Social Justice (WGSS/ISE 260) explores how algorithms—which drive everything from Internet search engines to predictive policing software and generative AI—reflect and magnify social inequality. Topics include race, gender, sexuality, and class in the context of policing and punishment, search engines and social media, and ranking and rating. A key goal of the course is to instill in students from technical fields an awareness of how social structures are a part of their work, so that their design choices are informed, from the ground up, by humanistic inquiry. Conversely, the course provides humanists with deeper awareness of how technical tools shape—and are shaped by—humanistic thought. Readings, discussions, and assignments are designed to cultivate transdisciplinary competence in the history of science and technology, feminist/critical race theory, machine learning (ML), and artificial intelligence (AI) and to encourage peer-to-peer learning across the humanities, social science, and engineering.

This course was developed and is taught by Professors Suzanne Edwards and Larry Snyder. It is cross-listed between Women, Gender, and Sexuality Studies (WGSS) and Industrial and Systems Engineering (ISE) at Lehigh University.

Course Outline

• Introduction
  • Why algorithms and social justice now?
  • Systemic inequalities
  • Intro to algorithms and AI
  • Intro to Jupyter notebooks
• Algorithms and Policing
  • Biometric normativity and The Gaze
  • Predictive policing and feedback loops
  • Recidivism models
  • Measures of fairness
• Interlude: Visionary Futures
• Algorithmic Epistemologies
  • Searching
  • Digital selves
  • US News rankings
• Data Labor and Ways Forward

Books

The readings change somewhat each time we teach the course. Some of the main books we discuss are:

• Meredith Broussard, Artificial Unintelligence
• Ruha Benjamin, Race After Technology
• Cathy O’Neil, Weapons of Math Destruction
• Catherine D’Ignazio and Lauren F. Klein, Data Feminism
• Safiya Umoja Noble, Algorithms of Oppression
• Sarah Brayne, Predict and Surveil
• Virginia Eubanks, Automating Inequality
• adrienne maree brown and Walidah Imarisha (eds.), Octavia’s Brood
• John Cheney-Lippold, We Are Data
• Thomas S. Mullaney, et al. (eds.), Your Computer Is On Fire

GitHub Repository

Many of the Jupyter notebooks and other materials from the course are available on our GitHub repo.

Discussions about the Course

• Larry discussed the course on The GE Spot, a podcast by students at Lehigh University’s Center for Gender Equity. Catch the episode, hosted by Sammy Haggert, here.
• We gave a presentation about teaching the course at Penn State–Berks in November 2023 [slides], and another at the University of Minnesota ISyE department in February 2024.
• See the article about the course in the Lehigh Brown and White, October 10, 2023.

Acknowlegments

This course was developed with partial support from a grant from the Lehigh University Humanities Lab. This support is gratefully acknowledged.

We also received substantial assistance from Lehigh’s Center for Innovation in Teaching and Learning (CITL), especially Rob Weidman and Jeremy Mack, who built some of the digital tools we use in the course.