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GradShares: How to Detect AI Hype
by GradFUTURES
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Details
GradShares Series Overview: GradShares is a research communication and networking series developed through collaboration between Princeton Area Alumni Association (PA3), Association of Princeton Graduate Alumni and GradFUTURES initiative in Princeton’s Graduate School. Through GradShares, Princeton Graduate Students communicate their research and connect with Princeton alums
The primary goal of the series are:
- enhance engagement and connections between local alums (both graduate and undergraduate) and current graduate students.
- provide graduate students opportunities to communicate their research in accessible ways and receive feedback
- expand avenues for local alumni to stay connected with research in Princeton
Sayash Kapoor, GS CS and CITP will serve as the first speaker of GradShares and discuss AI and surrounding hype.
Session Description: What makes AI work? What makes it fail? And how to tell the difference? In this talk, we'll dive deep into the opportunities, challenges and false promises of AI.
A networking reception will follow the talk.
Food Provided
Where
Princeton University Press Lounge
41 William Street , Princeton 08540 , United States
Speakers
Sayash Kapoor
Graduate Student, CS, CITP
Sayash Kapoor is a Ph.D. candidate at Princeton University's Center for Information Technology Policy. His research examines the societal impacts of artificial intelligence, with a focus on reproducibility, transparency, and accountability in AI systems. Kapoor's research provides insights into challenges in responsible computing, such as algorithmic legitimacy, privacy, and disinformation. He has previously worked on AI at Facebook, Columbia University, and EPFL Switzerland. He is currently co-authoring a book titled AI Snake Oil with Arvind Narayanan, which provides a critical analysis of AI capabilities, separating the hype from the true advances. Kapoor has been recognized with various awards, including a best paper award at ACM FAccT, an impact recognition award at ACM CSCW, and inclusion in TIME's inaugural list of the 100 Most Influential People in AI.