Critical Approaches to Artificial Intelligence

In this graduate seminar, students read, discuss, and evaluate relatively recent critiques of AI from a variety of perspectives — historical, ethical/philosophical, sociopolitical, and ecological. While the focus is on discourse, rhetoric, and critique (leading to student research presentations), the course also includes small-scale in-class tutorials using Python and PyTorch to make concepts like training, loss, epochs, and optimization concrete from an AI literacy standpoint. No prior technical experience is required.

Critical Discourses

Throughout the semester, we engage with several critical themes that shape how artificial intelligence is made, received, and historicized:

• Models of Mind / Intelligence
• Resistance / Reform
• Race / Nationality
• Open vs. Closed Source
• Data Representation / Compression
• Territoriality
• Energy / Ecology
• Sociopolitical Impacts

Selected Readings

• Ramon Amaro, The Black Technical Object: On Machine Learning and the Aspiration of Black Being (MIT Press, 2023)
• Neda Atanasoski & Kalindi Vora, Surrogate Humanity: Race, Robots, and the Politics of Technological Futures (Duke, 2019)
• Wendy Chun, Discriminating Data: Correlation, Neighborhoods, and the New Politics of Recognition (MIT Press, 2024)
• Kate Crawford, Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence (Yale UP, 2021)
• Elena Esposito, Artificial Communication: How Algorithms Produce Social Intelligence (MIT Press, 2022)
• Justin Joque, Revolutionary Mathematics: Artificial Intelligence, Statistics, and the Logic of Capitalism (Verso, 2022)
• Dan McQuillan, Resisting AI: An Anti-fascist Approach to Artificial Intelligence (Bristol UP, 2022)
• Cathy O’Neil, Weapons of Math Destruction (Crown, 2016)
• Matteo Pasquinelli, The Eye of the Master: A Social History of Artificial Intelligence (Verso, 2023)
• Stuart Russell & Peter Norvig, Artificial Intelligence: A Modern Approach, 4th ed. (Pearson, 2022)
• Shannon Vallor, The AI Mirror: How to Reclaim Our Humanity in an Age of Machine Thinking (Oxford UP, 2024)
• Amanda Wasielewski, Computational Formalism: Art History and Machine Learning (MIT Press, 2023)