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)
Algorithms of Oppression: How Search Engines Reinforce Racism, by Dr. Safiya Umoja Noble (NYU Press, 2018)
Invisible Women: Data Bias in a World Designed for Men, by Caroline Criado Perez (Abrams Press, 2019)
Other Reads and Resources
- “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)
- 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