Race and Technologies of Surveillance

(3 Credit Hours) · Undergraduate

The United States has a long history of using its most cutting-edge science and technology to discriminate, marginalize, oppress, and surveil. The poorhouse and scientific charity of an earlier era have been replaced by digital tracking and automated decision-making systems like facial recognition and risk prediction algorithms. This course focuses on how automated systems are tasked with making life-and-death choices: which neighborhoods get policed, which families get food, who has housing, and who remains homeless. This course will examine black box tools used in K-12 education, social services, and the criminal justice system to better understand how these technologies reinforce and worsen existing structural inequalities and systems of oppression. Class meetings will be split between discussions of conceptual readings and applied work with technology systems. Readings for this course will draw on texts that include Safiya Noble's Algorithms of Oppression: How Search Engines Reinforce Racism (2018), Virginia Eubanks' Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor (2018), Catherine D'Ignazio and Lauren Klein's Data Feminism (2020), and Meredith Broussard's Artificial Unintelligence: How Computers Misunderstand the World (2019). This course will also examine the advocacy and activism work undertaken by groups like Our Data Bodies, Data 4 Black Lives, Algorithmic Justice League, Auditing Algorithms, Big Brother Watch, and Chicago-based Citizens Police Data Project. Coursework may include response papers, hands-on work, and a final project. Familiarity with statistical analysis, data science, or computer science tools and methods is NOT a prerequisite for this course.