It was a pleasure to attend the recent National Institute of Standards and Technology (@NIST) and Center for AI Standards and Innovation Workshop on AI Incident Management. I was especially keen to see Neil Thompson (@ProfNeilT) deliver the keynote, where he discussed some of our recent research on the gaps between expert AI risk prioritization and organizational responses to those risks. (Although my photograph won't do it much justice!) I’m excited to continue exploring how the MIT AI Risk Initiative can support practical work on AI incident response and risk management. Many thanks to Sanjay Rekhi, M S Raunak (@msraunak), Peter Cihon (@pcihon), Anita Rao, and others for the invitation and for organizing such a valuable event. nist.gov/news-events/events/… @MITFutureTech @MITAIRisk

📢 New paper: Prioritization of Risks from Artificial Intelligence: A Delphi Study of 272 International Experts AI creates many risks, from discrimination, privacy loss, and fraud to more emerging concerns such as overreliance, dangerous capabilities being misused in weapons or cyberattacks, and AI systems pursuing unintended goals. But which risks are most severe? Who is most vulnerable? And who is most responsible for addressing them? To answer these questions, we conducted a three-round expert consultation with 272 AI experts. 💡 Four insights from our findings: 1️⃣ If things continue as they are over the next 5 years, experts assigned ≥10% probability of catastrophic outcomes (e.g., >1 million deaths or >$100 billion in losses) to 18 of 24 risks. Top concerns: cyberattacks and weapons, dangerous AI capabilities, competitive dynamics, power centralization, and disinformation and influence at scale. 2️⃣ Even assuming pragmatic mitigations, 5 risks remained above the 10% catastrophic threshold: dangerous AI capabilities, cyberattacks and weapons, environmental harm, inequality, and power centralization. 3️⃣ Vulnerability is broadly distributed, but responsibility is concentrated. Experts assigned the highest vulnerability to AI users and the general public, while assigning primary responsibility for mitigation to frontier AI developers, governments, regulators, and standards bodies. 4️⃣ Information, finance, and national security were rated the sectors most vulnerable to AI risks. 🔗How can you engage? See our (fancy) new webpage for our interactive summaries of the findings and preprint, and please share with anyone working on AI risk, governance, or policy. airisk.mit.edu/priorities This research is part of the MIT AI Risk Initiative (@MITAIRisk), which aims to help society understand, prioritize, and manage risks from AI. The initiative includes the MIT AI Risk Repository, a living database of more than 1,700 AI risks, the AI Incident Tracker, a collaboration with the Responsible AI Collaborative, which connects risks to over 1,400 incidents, and the MIT AI Governance Map, which analyzes risk coverage across more than 1,000 laws, standards, policies, and other governance documents curated by the Center for Security and Emerging Technology (CSET). #AI #AIrisk #AISafety #AIGovernance #ResponsibleAI #RiskManagement

AI and the energy transition are reshaping the economy. Join EG and experts on June 10 to discuss how these factors influence growth and interact with climate change and regional development. Feat @CostaSamaras, @HBoushey, @JigarShahDC @ProfNeilT RSVP➡️ web.cvent.com/event/6a3be4dc…

@ProfNeilT kicks off the #google #MITFuturetech #AIfortheEconomyForum with our findings on AI automation from Thousands of Worker Evaluations of Labor Market Tasks. Read the full paper: arxiv.org/abs/2604.01363

Our new substack post: Can Academic Science Keep Up with the AI Frontier? mitfuturetech.substack.com/p…

MIT researchers @ProfNeilT and @davidautor joined the @csail_alliances podcast to talk about why AI’s impact on jobs hinges less on automation and more on how well the technology is designed to work with humans. bit.ly/4rJhlhb

Very interesting new paper AI and Scale: A Quantitative Task-Based Theory of Automation by @DanialLashkari @li_wensu C. Qiu and @ProfNeilT which takes serious the role of scale in driving AI performance and capabilities and, hence, firm adoption. Applied to the context of computer-vision automation, they find firm-level adoption follows a classic S-curve, rising from under 1% of firms in 2023 to nearly 1/4 by 2035 (>50% if employment-weighted)

Beyond job displacement, this is the real shift. AI doesn’t just automate work, it reshapes where expertise matters. As @davidautor and @ProfNeilT note, when machines handle the predictable, value moves to judgment and creativity. That’s what most “AI-first” strategies miss. #AI

Beyond Job Displacement: How AI Could Reshape the Value of Human Expertise digitalistpapers.com/vol2/au… ✍️ @davidautor @ProfNeilT via "The Digitalist Papers Volume 2" @DigEconLab 👉 "How will transformative AI reshape the world of work? It will not simply eliminate jobs; it will reshape the value of human expertise. This new framework can help us think through very different scenarios, from gradual automation to complete human labor obsolescence—and how we can prepare for them" 💡 “We remain optimistic that humanity is not converging rapidly to the end of labor scarcity, but we recognize that a risky technological and economic transition is already underway—one with vast upside benefits and vast downside risks that will land unevenly on individuals, demographic groups, nations, and generations” @Corix_JC @jeanyvesgonin @sonu_monika @JagersbergKnut @ahier @sim010101 @maponi @EstelaMandela @Shi4Tech @CEO_Aisoma @SpirosMargaris @dinisguarda @RamonaEid @AstridLavalette @ChuckDBrooks @FernandaKellner @mvollmer1 @PVynckier @JoannMoretti @NeiraOsci @tlloydjones @SusanHayes_ @theomitsa @smoothsale @TarakRindani @FrRonconi @Nicochan33 @mikeflache @Khulood_Almani @TysonLester @CurieuxExplorer @Ym78200 @amalmerzouk @smaksked @sulefati7 @pchamard @Analytics_699 @MaryRich78 @Eli_Krumova @TheAIObserverX @NathaliaLeHen @sminaev2015 @jeancayeux @WillyRayNick @DanielleLargier @RLDI_Lamy

@MITSloan's FutureTech is hiring a pre-doc to work w/ Prof. Thompson (@ProfNeilT) on topics related to AI Progress and Timelines; AI and Science; Future of Work; Market Structure and Firm Performance bit.ly/4inn5tp

Our new paper shows how AI foundation models are being adopted in science. Growth is rapid, but uneven. The AI models being used are old and underpowered, so there is still lots of room to make science more productive! @MITFutureTech @MIT_CSAIL @mit_ide arxiv.org/abs/2511.21739

This is tonight! Come hear from @davidautor and @ProfNeilT about how AI will affect jobs - and bring your questions. MIT Museum - 6-7pm!

Our new paper breaks down algorithm progress in AI (which is faster than GPU progress). Surprisingly, much of the gains have only gone to the largest models, which is bad news for AI efficiency improvement. @MITFutureTech arxiv.org/abs/2511.21622

This week, Jensen Huang argued that "everybody's jobs will be different" because of AI. What will that mean for your job? I'll talk with @davidautor and @ProfNeilT on Dec 2 at @MITMuseum. Come join us! cap.csail.mit.edu/members/ev…

#NDTVWorldSummit | "We have seen chaos in AI" : Neil Thompson (@ProfNeilT), Director, FutureTech Research Project, MIT’s Computer Science and Artificial Intelligence Lab notes the "chaos" that can entail in the future of AI #NDTVWorldSummit2025

#NDTVWorldSummit | "AI is a big departure from traditional AI systems" : Neil Thompson (@ProfNeilT), Director, FutureTech Research Project, MIT’s Computer Science and Artificial Intelligence Lab #NDTVWorldSummit2025

#NDTVWorldSummit | What is AI's garden arranging path? Neil Thompson (@ProfNeilT), Director, FutureTech Research Project, MIT’s Computer Science and Artificial Intelligence Lab explains #NDTVWorldSummit2025

#NDTVWorldSummit | Neil Thompson (@ProfNeilT), Director, FutureTech Research Project, MIT’s Computer Science and Artificial Intelligence Lab shares his views with Union Minister Ashwini Vaishnaw (@AshwiniVaishnaw) on India’s technology adoption and AI progress @rahulkanwal @VishnuNDTV #NDTVWorldSummit2025

#NDTVWorldSummit | What should give us comfort about AI? Neil Thompson (@ProfNeilT), Director, FutureTech Research Project, MIT’s Computer Science and Artificial Intelligence Lab explains @ShivAroor #NDTVWorldSummit2025

#NDTVWorldSummit | "The most important part is scaling up, and the second most important part has been algorithm improvement" : Neil Thompson (@ProfNeilT), Director, FutureTech Research Project, MIT’s Computer Science and Artificial Intelligence Lab @ShivAroor #NDTVWorldSummit2025