Daring to DAIR: Distributed AI Research with Timnit Gebru - #568
Analysis
This podcast episode from Practical AI features Timnit Gebru, founder of the Distributed Artificial Intelligence Research Institute (DAIR). The discussion centers on Gebru's journey, including her departure from Google after publishing a paper on the risks of large language models, and the subsequent founding of DAIR. The episode explores DAIR's goals, its distributed research model, the challenges of defining its research scope, and the importance of independent AI research. It also touches upon the effectiveness of internal ethics teams within the industry and examples of institutional pitfalls to avoid. The episode promises a comprehensive look at DAIR's mission and Gebru's perspective on the future of AI research.
Key Takeaways
- •The episode focuses on the founding and goals of DAIR.
- •It highlights the importance of independent AI research.
- •It discusses the challenges and considerations in building a research institute.
“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.”