Tag: AI
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Princeton’s CITP and the NJ Office of the Public Defender Launch an AI-powered Resource Library
Authors: Dominik Stammbach, Peter Henderson In a speech at the NJ AI Summit on April 11, 2024, Phil Murphy, then-Governor of New Jersey, announced his support for a new partnership between Princeton University and New Jersey’s Office of the Public Defender (NJOPD). “Together, they are working to build an AI-powered resource that will help our…
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Facts & Fictions: Is AI-Assisted Oral Argument Preparation Worth the Hype?
Authored by Kylie Zhang, Nimra Nadeem, Lucia Zheng, Dominik Stammbach, Peter HendersonIn a recent TED Talk, Supreme Court attorney Neal Katyal describes how he prepared for his Supreme Court oral arguments in Learning Resources v. Trump, the 2025 tariffs case. Katyal says that he was guided in his journey by four mentors: sports coach Bob,…
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Can AI reduce burdens on courts by automatically verifying citations?
Authored by : Patty Liu, Dominik Stammbach, Peter Henderson Fabricated case citations generated by AI are appearing in court filings at an accelerating rate. Combined with other tracking efforts, we have identified over 1,000 filings containing hallucinated citations from self-represented (pro se) litigants and lawyers alike. Fabricating citations, or misrepresenting the content of those citations,…
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AI Chip Lifespans: A Note on the Secondary Market
Two months ago, I wrote about the competition concerns with the GenAI infrastructure boom. One of my provocative claims was that the lifespan of the chips may be significantly shorter than the accounting treatment given to them. Others like David Rosenthal, Ed Zitron, Michael Burry and Olga Usvyatsky have raised similar concerns. NVIDIA has a…
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The Limits of Data Filtering in Bio-Foundation Models
Blog Authors: Boyi Wei, Matthew Siegel, and Peter Henderson Paper Authors: Boyi Wei*, Zora Che*, Nathaniel Li, Udari Madhushani Sehwag, Jasper Götting, Samira Nedungadi, Julian Michael, Summer Yue, Dan Hendrycks, Peter Henderson, Zifan Wang, Seth Donoughe, Mantas Mazeika This post is modified and cross-posted between Scale AI and Princeton University. The original post can be…
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Why the GenAI Infrastructure Boom May Break Historical Patterns
Authored by Mihir Kshirsagar Observers invoke railroad, electricity, and telecom precedents when contextualizing the current generative artificial intelligence (GenAI) infrastructure boom—usually to debate whether or when we are heading for a crash. But these discussions miss an important pattern that held across all three prior cycles: when the bubbles burst, investors lost money but society…
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Meet the Researcher: Varun Satish
Varun Satish is a Ph.D. student in demography at Princeton University. His current projects include using language models to study the life course, and using machine learning to uncover shifting perceptions of social class in the United States over the last 50 years. Satish is originally from Western Sydney, Australia. Princeton undergraduate Jason Persaud ‘27…
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AI “Born Secret”? The Atomic Energy Act, AI, and Federalism
Authored by: Kylie Zhang and Peter Henderson Tl;dr: Can states regulate AI risks of disclosing nuclear secrets? This post will explore the Atomic Energy Act, its applicability to AI, the potential impacts on state efforts, and potential policy recommendations for guiding AI safety evaluations and model releases. If an advanced AI system can figure out…
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CITP Comments on AI Accountability
Recently, the White House opened a number of opportunities for the public to comment on the growing field of accountability for artificial intelligence (AI) systems. The National Telecommunications and Information Administration (NTIA), the Executive Branch agency that is principally responsible for advising the President on telecommunications and information policy issues, launched a comment process that…
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How the National AI Research Resource can steward the datasets it hosts
Last week I participated on a panel about the National AI Research Resource (NAIRR), a proposed computing and data resource for academic AI researchers. The NAIRR’s goal is to subsidize the spiraling costs of many types of AI research that have put them out of reach of most academic groups. My comments on the panel…