Princeton professor and CITP director, AI policy and evaluation researcher
Arvind Narayanan
Professor of Computer Science, Director of Center for Information Technology Policy — Princeton UniversityFaculty Associate — Harvard Berkman Klein CenterCo-author, AI Snake Oil (with Sayash Kapoor) — Princeton University Press
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Profile
Arvind Narayanan is a computer science professor at Princeton and director of the university’s Center for Information Technology Policy. If you want someone who actually reads the papers, understands the math, and will still tell you the emperor has no clothes, this is your guy. His work is the single best counterweight to AI marketing currently in circulation — not because he dismisses the technology, but because he takes it seriously enough to demand evidence.
Before AI became his main beat, Narayanan was already a force in technical privacy and security research. His 2008 paper with Vitaly Shmatikov on de-anonymizing the Netflix Prize dataset is a classic — showing that “anonymized” data often isn’t, using nothing more than public IMDb ratings as a side channel. He later co-authored Bitcoin and Cryptocurrency Technologies, the Princeton textbook that many developers still cite as the cleanest technical introduction to the field.
Today his focus is AI hype and accountability, mostly with his PhD student and co-author Sayash Kapoor. Together they wrote AI Snake Oil — the book and the Substack — and in 2025 published AI as Normal Technology, a long essay arguing that AI is a general-purpose technology like electricity or the internet, not a superintelligent alien. The piece is worth reading even if you disagree with it: it’s the most rigorous articulation of the “moderate optimist” position out there, and it directly engages with both the doomers and the accelerationists on their own terms.
For developers, Narayanan’s value is simple. When you see a breathless claim — “AI predicts crime,” “AI screens resumes better than humans,” “AI will collapse the economy in 18 months” — his writing is where you go to figure out what’s actually being measured, what the benchmark is hiding, and whether anyone has reproduced the result. He and Kapoor made the TIME100 AI list in 2023 for exactly this reason: evidence-based criticism is scarce, and theirs is the best.
Arvind Narayanan on Why AI Isn’t All That Revolutionary
The Good Fight
2026
Debunking AI’s “Existential Risk” with Arvind Narayanan and Sayash Kapoor
Factually! with Adam Conover
2026
AI DEBATE: Runaway Superintelligence or Normal Technology? | Daniel Kokotajlo vs Arvind Narayanan
Limitless: An AI Podcast
2025
AI Snake Oil by Sayash Kapoor & Arvind Narayanan (English) Full Podcast
Penplexity English
2025
Ep 54: Princeton Researcher Arvind Narayanan on the Limitations of Agent Evals, AI’s Societal Impact & Important Lessons from History
Unsupervised Learning with Jacob Effron
2025
Two Computer Scientists Debunk A.I. Hype with Arvind Narayanan and Sayash Kapoor (Adam Conover)
KEEP MOVING FORWARD
2025
AI Agents: Substance or Snake Oil with Arvind Narayanan - #704
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
2024
Two Computer Scientists Debunk A.I. Hype with Arvind Narayanan and Sayash Kapoor
Factually! with Adam Conover
2024
20VC: AI Scaling Myths: More Compute is not the Answer | The Core Bottlenecks in AI Today: Data, Algorithms and Compute | The Future of Models: Open vs Closed, Small vs Large with Arvind Narayanan, Professor of Computer Science @ Princeton
The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch
2024
#9 – Arvind Narayanan: Myths and Policies in Scaling AI
