Discrimination, Harms, and Measurement

Topics

• Discrimination, Harms, and power, and a brief history of race science.

Reading (Required)

• Data Feminism (Chapter 1: The Power Chapter) by Catherine D’Ignazio and Lauren F. Klein
• Physiognomy’s New Clothes by Blaise Aguera y Arcas, Margaret Mitchell, and Alexander Todorov
• The Raw and the Cooked: The Mythologies of Big Data by Kate Crawford (Video)
• Algorithms aren’t racist. Your skin is just too dark. by Joy Buolamwini

Reading (Optional)

• Coded Bias
• Fairness in Machine Learning: Lessons from PoliticalPhilosophy by Reuben Binns
• Machine Bias (Propublica)

Reading Responses

Choose one of the first two required readings and:

1. Summarize the main argument of the reading
2. Give a supporting argument the author uses
3. Discuss any objects you may have or subtleties the author must deal with.