Daring to DAIR: Distributed AI Research with Timnit Gebru
EPISODE 568
|
APRIL
18,
2022
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About this Episode
Today we’re joined by friend of the show Timnit Gebru, the founder and executive director of DAIR, the Distributed Artificial Intelligence Research Institute. In our conversation with Timnit, we discuss her journey to create DAIR, their goals and some of the challenges shes faced along the way. We start is the obvious place, Timnit being “resignated” from Google after writing and publishing a paper detailing the dangers of large language models, the fallout from that paper and her firing, and the eventual founding of DAIR. We discuss the importance of the “distributed” nature of the institute, how they’re going about figuring out what is in scope and out of scope for the institute’s research charter, and what building an institution means to her. We also explore the importance of independent alternatives to traditional research structures, if we should be pessimistic about the impact of internal ethics and responsible AI teams in industry due to the overwhelming power they wield, examples she looks to of what not to do when building out the institute, and much much more!
About the Guest
Timnit Gebru
Stanford University
Resources
- Paper: On the Dangers of Stochastic Parrots
- Paper: The Grey Hoodie Project: Big Tobacco, Big Tech, and the threat on academic integrity
- Paper: Toward a Critical Technical Practice: Lessons Learned in Trying to Reform AI
- Paper: Machine Learning that Matters - Kiri Wagstaff
- Paper: Fairness in Abstraction
- Paper: Data Voids: Where Missing Data Can Easily Be Exploited
- Paper: Constructing a Visual Dataset to Study the Effects of Spatial Apartheid in South Africa
- Article: Inside Facebook's African Sweatshop
- Article: Philip Agre predicted technology's pitfalls and then he disappeared - The Washington Post
- Article: Testing and Documentation (DataSheets for Datasets)
- Workshop: 2nd Workshop on Practical ML for Developing Countries: Learning Under Limited/low Resource Scenarios
- Mary L. Gray - Book: Ghost Work
- Masakhane
- Deep Learning Indaba
- Mijente
- The Deadly Digital Border Wall
- Gender Shades
- Africa Is a Country
- Can Language Model Be Too Big? w/ Emily Bender and Margaret Mitchell - #467
- A Future of Work for the Invisible Workers in AI with Saiph Savage - #447
- Trends in Fairness and AI Ethics with Timnit Gebru - #336
- Using Deep Learning and Google Street View to Estimate Demographics with Timnit Gebru - #88
- TWIML Online Meetup #5 - Presented by Timnit Gebru
