TDAI hosts monthly informal discussions of books, articles and films that address racial and gender bias in algorithms and automated decision-making technologies. Led by Dr. Zahra Atiq, the free-ranging conversations also explore societal ramifications and implications for researchers, educators and students.
Current Selection
Data Feminism, by Catherine D'Ignazio and Laura F. Klein (MIT Press, 2020; open access edition available)
Next meeting: June 1, 12 p.m. - Chapters 4 through Conclusion
Join the Bias in AI book group listserv.
Previous Selections
Algorithms of Oppression: How Search Engines Reinforce Racism, by Dr. Safiya Umoja Noble (2018)
Coded Bias, directed by Shalini Kantayya (2020)
The Ethical Algorithm: The Science of Socially Aware Algorithm Design, by Michael Kearns and Aaron Roth (2020)
Other Reads and Resources
Webinar
- “Understanding Racial Bias in Algorithms,” hosted by OSU Program on Data and Governance, 9/25/20
Articles
- “Science-fiction master Ted Chiang explores the rights and wrongs of AI” (Science, 11/8/20)
- “Can We Make Our Robots Less Biased Than We Are?” (New York Times, 11/22/20)
- “Artificial Intelligence, Health Disparities, and COVID-19” (Undark, 7/27/20)
Reading Lists
- Readings and other resources on trustworthiness from trustworthyml.org
- Recommended books, podcasts and journals on ethics from aiethicist.org
- Bookclub on Data Science Ethics reading list from Teach Data Science
- 2020 recommended reads from Anthropology and Technology Conference organizers
