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Arvind Narayanan

Professor of Computer Science; Director, Center for Information Technology Policy, Princeton University

Search every verified Arvind Narayanan interview, podcast appearance, and on-the-record quote — each transcript cross-checked by AI and human review to confirm speaker identity. Arvind Narayanan, professor of computer science at Princeton University and director of the Center for Information Technology Policy, has delivered several talks and appearances in recent months. At the Computation + Journalism 2026 Symposium, he gave a keynote on AI and journalism, suggesting that journalists prepare for a future where most technical limitations of AI are overcome but human factors, such as building trust with sources, gain importance. He also referenced an article by Julia Angwin that argues social media content creators treat "getting the story" as part of the story, a norm he suggested mainstream journalism might adopt when AI writing becomes undetectable. In a CITP seminar, Narayanan argued that the dominant "automation agenda" in AI research is struggling commercially, given margin compression makes automated tasks hard to monetize, and advocated for investing in "augmentation"—building agents that collaborate with and amplify human potential rather than replace workers. Narayanan also participated in a discussion on measuring AI effectiveness for government use, stating that capability benchmarks and procurement-based evaluations are inadequate because models are constantly updated and reliability, not just capability, matters in public-sector settings. In an appearance on a podcast about Meta's $17 billion settlement, he commented on data centers, arguing that banning their construction would not meaningfully slow AI progress because efficiency gains from hardware and software improvements far outpace capacity losses from new buildings. He also remarked on industry claims about AGI, describing it as an arbitrary and untestable threshold, though he noted OpenAI's people are "more right than wrong" about recent progress.

Recent appearances

  • C+J 2026: Keynote: Arvind Narayanan: AI and journalism: skating where the puck is going

    October 20, 2026 · 📺 Knight Lab

    Keynote address, Computation + Journalism 2026 Symposium, Northwestern University Saturday, October 3, 2026 Arvind Naryanan, Princeton University “How should journalists prepare for the threats and opportunities likely to be presented by AI not just today but in five or ten years? I suggest that the best approach is to assume that most technical limitations of current AI will have been overcome, such as hallucination, writing style, memory, personalization, cost, speed, and usability, but human factors will remain and grow in importance, such as the need to build trust with sources or problem…

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  • CITP Seminar Arvind Narayanan - AI Agents and the Augmentation Agenda

    September 21, 2026 · 📺 CITP Princeton

    The dominant paradigm in AI research and development envisions the goal as automation of tasks and entire jobs. But another, comparatively marginalized vision has existed since the beginning of AI — that of augmenting workers and amplifying human potential. In this talk, it is argued that the automation agenda is struggling even on purely commercial grounds, and it is time to invest more into augmentation. Building agents for collaboration instead of automation requires elevating a set of underexplored research challenges in human-computer interaction. Such agents can better serve human flouri…

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  • Sep 8, 2026 - Why Measuring AI Is Hard - with Arvind Narayanan and Beth Simone Noveck

    September 09, 2026 · 📺 InnovateUS

    Why don’t AI benchmark scores always tell us how well a tool will perform in government? Explore the challenges of measuring AI effectiveness, reliability, and public value in real-world settings with Arvind Narayanan, Professor at Princeton University & Director of the Center for Information Technology Policy and Beth Simone Noveck, Founder of InnovateUS and Director, Burnes Center for Change and the GovLab

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  • What Meta's $17 Billion Settlement Means for TikTok and YouTube

    August 28, 2026 · 📺 Hard Fork

    Meta reached a landmark settlement this week, agreeing to pay up to $17.1 billion and make major changes to Facebook and Instagram over claims it endangered children with addictive social media platforms. We discuss why Meta capitulated and what it means for the entire social media industry. Then, Princeton computer science professor Arvind Narayanan returns to offer his thoughts on why banning data centers won’t slow down A.I. progress. And finally, it’s all hats on deck for the final HatGPT. Guest: Arvind Narayanan, professor of computer science at Princeton, and co-author of the “A.I. as N…

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  • Arvind Narayanan on Why AI Isn’t All That Revolutionary

    July 07, 2026 · 📺 Persuasion

    Arvind Narayanan is a professor of computer science at Princeton University. In this week’s conversation, Yascha Mounk and Arvind Narayanan discuss why AI’s transformative impact will unfold over decades rather than months, whether human accountability can survive the rise of AI agents in the workplace, and what the economy will look like once AI has automated every task that can be precisely specified. Please do listen and spread the word about The Good Fight. Podcast production by Mickey Freeland. Email: [email protected] Website: http://www.persuasion.community Spotify: htt…

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  • Arvind Narayanan: Adapting to the Transformation of Knowledge Work

    May 19, 2026 · 📺 Stanford Digital Economy Lab

    For our last seminar of the quarter, the Lab welcomed Arvind Narayanan, Professor of Computer Science at Princeton University, to give his talk, "Adapting to the Transformation of Knowledge Work." Abstract The possibility that AI will automate most cognitive labor is worth taking seriously. How should we adapt to this transformation? I start from the perspective, articulated in the essay “AI as normal technology”, that the true bottlenecks lie downstream of capabilities and that AI’s impacts will unfold gradually over decades. If this is true, there are major gaps in our current evidence infr…

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  • Debunking AI’s “Existential Risk” with Arvind Narayanan and Sayash Kapoor

    March 18, 2026 · 📺 Adam Conover

    Will AI obliterate all of humanity? Will it destroy all of our jobs? There are so many questions swirling around the existential threat that AI poses, and even more completely hypothetical answers. This week, Adam brings back past guests Arvind Narayanan, professor of Computer Science at Princeton, and Princeton PhD student Sayash Kapoor to give expert perspective on our current moment. Their newest essay, AI as Normal Technology, is a rational and evidence-based exploration of AI that offers an alternative vision to the idea of AI as a potential superintelligence. Get 20% off DeleteMe by go…

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  • Arvind Narayanan - Conference on Society-Centered AI (Keynote)

    March 05, 2026 · 📺 Society-Centered AI at Duke University

    The Conference on Society-Centered AI (#SCAI2026) brought together more than 950 attendees from 80+ companies and 50+ universities for Duke University’s largest gathering yet focused on the impact of artificial intelligence on society. Held February 12–14, 2026 at the Fuqua School of Business, the conference featured three keynote talks, expert panels, 14 spotlight research presentations, 40 research posters and art exhibits, and multiple community-building events that highlighted the breadth of society-centered AI work happening across Duke and beyond. Keynote from Thursday February 12: Arvi…

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  • The AI job apocalypse narrative is flawed. Here’s what we’re missing (with Arvind Narayanan)

    March 03, 2026 · 📺 Our Lives With Bots

    AI will NOT take all our jobs, if only we learn from the mistakes of the past. Welcome to the FINAL episode of our AI and Work series with Our Lives With Bots! In this episode, Arvind Narayanan (https://www.cs.princeton.edu/~arvindn/), professor of computer science and director of the Center for Information Technology Policy at Princeton University, shares a grounded perspective on what AI means for work. Leveraging lessons from past technological advancements and responses, Arvind shows us just how many misconceptions there are about AI replacing workers and explains how we can approach a…

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  • FARI Brussels Conference 2025 - Arvind Narayanan | Keynote Speech

    December 08, 2025 · 📺 FARI - AI for the Common Good Institute

    Keynote speech of Arvind Narayanan, professor of computer science at Princeton University and the director of the Center for Information Technology Policy. He is a co-author of the book AI Snake Oil and a newsletter of the same name which is read by 60,000 researchers, policy makers, journalists, and AI enthusiasts. He previously co-authored two widely used computer science textbooks: Bitcoin and Cryptocurrency Technologies and Fairness in Machine Learning. Narayanan led the Princeton Web Transparency and Accountability Project to uncover how companies collect and use our personal information.…

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  • What Everyone’s Getting Wrong About AI - ft. Arvind Narayanan | Capitalisn't

    October 30, 2025 · 📺 Capitalisn't

    Will the AI bubble be bigger than the dot-com crash? The numbers are staggering: NVIDIA's market cap recently hit $5 trillion, and a report from J.P. Morgan Chase shows that AI-related stocks account for 75% of S&P 500 returns since ChatGPT launched. What happens if it all comes crashing down? Princeton computer science professor Arvind Narayanan, author of "AI Snake Oil," joins Luigi Zingales and Bethany McLean to cut through the hype. He explains why AI's transformative impact is massively overstated, how capitalism's incentives are pushing technology faster than reality can deliver, and w…

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  • CITP Seminar Arvind Narayanan - Could AI Get Worse? Bracing for Enshittification

    September 15, 2025 · 📺 CITP Princeton

    It’s a truism that AI is the worst it will ever be. But while model capabilities do tend to improve over time, users’ experience of AI as a consumer product is affected by many other factors. In a draft paper, Akash Kapur and Arvind Narayanan adapt Cory Doctorow’s enshittification thesis to AI, and argue that degradation of quality is possible or even likely. Some of the reasons why AI products might get worse are familiar ones, such as market power due to user lock-in, while others are new, arising from geopolitical pressures on AI companies. The talk will discuss the symptoms of enshittifica…

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