Arvind Narayanan
Computer scientist, Princeton University
Signed the letter · Academia · United States
Professor of computer science at Princeton University and director of Princeton's Center for Information Technology Policy. Co-author, with Sayash Kapoor, of the book 'AI Snake Oil: What Artificial Intelligence Can Do, What It Can't, and How to Tell the Difference' (Princeton University Press, 2024) and a newsletter of the same name. Co-author of the textbook 'Bitcoin and Cryptocurrency Technologies' and of a textbook on fairness in machine learning. Led the Princeton Web Transparency and Accountability Project on online tracking, and is a co-author of 'Leakage and the reproducibility crisis in machine-learning-based science'. Signed the wemustactnow.ai open letter.
AI-written Documented facts only, from the sources below.
15 works in the co-authorship map · 6,029 citations across them
Sources
In the network
6 co-authors on the map · PageRank #53 of 400 · bridge #48 of 400 · 2 steps from Erik Brynjolfsson · cluster: Foundation models and society.
Measured on this map only, which grows out of the letter's signatories; what these numbers mean. See Arvind Narayanan on the map
Documented positions
Will AI actually boost productivity and growth? leans disagree
Prominent AI-hype skeptic ('AI Snake Oil'): argues claimed efficiency gains often fail to materialize automatically in real deployments.
Will AI destroy more jobs than it creates? unknown
No documented evidence reviewed yet.
Will AI widen inequality? unknown
No documented evidence reviewed yet.
Should governments act on AI now? it's complicated
Supports evidence-based governance but pushes back on restrictive rules driven by speculative risks, e.g. defending open foundation models.
How fast will the impact arrive? leans disagree
Argues AI diffuses like a normal technology — slowly, unevenly, and with institutional friction — rather than transforming the economy within a few years.
Selected work
- AI Snake Oil: What Artificial Intelligence Can Do, What It Can't, and How to Tell the Difference
- Leakage and the reproducibility crisis in machine-learning-based science
- Online Tracking
Writes with
Sayash Kapoor (4), Andrew Miller (3), Edward W. Felten (3), Joseph Bonneau (3), Michiel Bakker (1), Rishi Bommasani (1)
Co-authors on the map, by papers written together (6 of 6 shown).
Heard on
Podcast episodes that name Arvind Narayanan in their title or description (1 of 1 shown).
- The Single Smartest Case Against AI Doom
Plain English with Derek Thompson · 25 Sep 2026
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