Essentials: regulation
Should governments act on AI now? The key papers, numbers, people and newsletters, sized to the time you have. The full question page. Picks are chosen for their weight in the debate and span its sides; they are refreshed every two weeks, last on 29 Oct 2026. The reasons are AI-written and evidence-cited; no rankings or scores.
Five papers, the numbers with their exact quotes, five people and three sources.
Papers to read
- How the U.S. Public and AI Experts View Artificial IntelligenceColleen McClain et al. · Pew Research Center · 2025 · Evidence for the claim
Pew survey: about six in ten US adults and 56% of AI experts worry the government will not go far enough on AI rules.
- Americans Prioritize AI Safety and Data SecurityGallup and Special Competitive Studies Project · Gallup News · 2025 · Evidence for the claim
Gallup survey: 80% of US adults would keep AI safety rules even if AI develops more slowly.
- Artificial Intelligence and the future of workEuropean Commission · Special Eurobarometer · 2025 · Evidence for the claim
Eurobarometer: 84% of Europeans say AI at work needs careful management for privacy and transparency.
- How Might Fiscal Policy Respond to the Rise of Artificial Intelligence?Karen Dynan et al. · NBER · 2026 · Evidence for the claim
NBER scenarios for how fiscal policy could respond to AI, favouring policies that hold up whichever scenario arrives.
This NBER paper lays out long-term US scenarios combining faster productivity growth, greater income inequality, job displacement and a higher capital share of income, and works through what each would mean for federal debt. It then weighs policy responses on growth, income distribution, support for laid-off workers and the taxation and ownership of capital, favouring policies that hold up across scenarios given how uncertain AI's effects are.
- Workforce policy for the age of AI Not peer reviewedBrookings · Brookings · 2026 · Mixed evidence
Brookings: the evidence supports neither mass unemployment nor universal gains, so workforce policy should not rest on exposure alone.
This policy piece argues the evidence supports neither mass unemployment nor universal augmentation: AI is likely to displace some work quickly and augment other work gradually, with outcomes varying by occupation, industry and employer. It contends that exposure is the wrong basis for workforce policy, which should instead focus on how AI changes the value of human expertise and access to opportunity.
Of these 3 papers: 3 with evidence for the claim.
Of these 5 papers: 4 with evidence for the claim, 1 mixed.
Of these 5 papers: 4 with evidence for the claim, 1 mixed.
Figures to know
- 58%US adults worried the government will not go far enough regulating AI
Colleen McClain et al., 2025 · Regulation“Both experts (56%) and the public (58%) are more concerned that the U.S. government will not go far enough in regulating AI”
- 56%US AI experts worried the government will not go far enough regulating AI
Colleen McClain et al., 2025 · Regulation“Both experts (56%) and the public (58%) are more concerned that the U.S. government will not go far enough in regulating AI”
- 80%US adults: keep AI safety rules even if AI develops more slowly
Gallup and Special Competitive Studies Project, 2025 · Regulation“80% of U.S. adults believe the government should maintain rules for AI safety and data security, even if it means developing AI capabilities more slowly”
- 84%Europeans: AI at work needs careful management for privacy and transparency
European Commission, 2025 · Regulation“84% of Europeans think that AI requires careful management to protect privacy and ensure transparency in the workplace”
- 70%AI researchers saying AI safety research should be prioritized more
Katja Grace et al., 2025 · Regulation“70% of respondents thought AI safety research should be prioritized more than it currently is”
Every number is quoted from its source and linked to the paper; estimates differ in method and horizon, so they are not directly comparable.
People to follow
- Yoshua Bengio agreesComputer scientist, Université de Montréal
Computer scientist and Turing Award co-recipient with a documented position in favour of acting on AI now.
Key work: Deep learning; Generative adversarial networks
- Gillian Hadfield agreesProfessor of AI Alignment and Governance, Johns Hopkins University
Professor of AI alignment and governance at Johns Hopkins who works on how to design rules for AI.
Key work: Rules for a Flat World: Why Humans Invented Law and How to Reinvent It for a Complex Global Economy; Managing extreme AI risks amid rapid progress
- Daron Acemoglu agreesEconomist, Massachusetts Institute of Technology
Economist with a documented position that governments should steer AI's direction now.
Key work: Robots and Jobs: Evidence from US Labor Markets; The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment
- Joshua Gans it's complicatedEconomist, Rotman School of Management, University of Toronto
Co-author of 'Prediction Machines'; his documented position on acting now is mixed.
Key work: Prediction Machines: The Simple Economics of Artificial Intelligence; Power and Prediction: The Disruptive Economics of Artificial Intelligence
- Ajay Agrawal it's complicatedEconomist, Rotman School of Management, University of Toronto
Founder of the Creative Destruction Lab and co-author of 'Power and Prediction'; his documented position is mixed.
Key work: Prediction Machines: The Simple Economics of Artificial Intelligence; Power and Prediction: The Disruptive Economics of Artificial Intelligence
Of these 3 people: 3 agrees. Documented, cited positions only.
Of these 5 people: 3 agrees, 2 it's complicated. Documented, cited positions only.
Of these 5 people: 3 agrees, 2 it's complicated. Documented, cited positions only.
Newsletters and sources
- AI Governance Lab (Rob Reich)Newsletter · 1 posts in this guide
A newsletter on AI governance and policy from a Stanford political philosopher.
- Justified Posteriors (Andrey Fradkin)Newsletter · 7 posts in this guide
Discusses research that bears on AI policy alongside the economics.
- OECD AI Policy ObservatoryOECD · dataset · outside this guide
Tracks AI policies and laws across countries in one place.
- Stanford AI Index ReportStanford Institute for Human-Centered AI · report · outside this guide
Its yearly report counts AI laws and public opinion on AI across countries.