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 and held the last Thursday of the month, the free-ranging conversations also explore societal ramifications and implications for researchers, educators and students. All OSU faculty, students and staff are welcome.
Join us for the next discussion!
Thursday, April 14, 4-5 p.m.
The Alignment Problem: Machine Learning and Human Values, by Brian Christian (W. W. Norton & Company)
Click here to join the Bias in AI book group listserv.
Previous Selections
Coded Bias, directed by Shalini Kantayya (2020)
Data Feminism, by Catherine D'Ignazio and Laura F. Klein (MIT Press, 2020)
Algorithms of Oppression: How Search Engines Reinforce Racism, by Dr. Safiya Umoja Noble (NYU Press, 2018)
The Ethical Algorithm: The Science of Socially Aware Algorithm Design, by Michael Kearns and Aaron Roth (Oxford University Press, 2020)
Invisible Women: Data Bias in a World Designed for Men, by Caroline Criado Perez (Abrams Press, 2019)
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
