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arXiv:2401.02843cs.CY

Thousands of AI Authors on the Future of AI

Katja Grace, Harlan Stewart, Julia Fabienne Sandkühler, Stephen Thomas, Ben Weinstein-Raun, Jan Brauner, Richard C. Korzekwa

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Abstract

In the largest survey of its kind, 2,778 researchers who had published in top-tier artificial intelligence (AI) venues gave predictions on the pace of AI progress and the nature and impacts of advanced AI systems The aggregate forecasts give at least a 50% chance of AI systems achieving several milestones by 2028, including autonomously constructing a payment processing site from scratch, creating a song indistinguishable from a new song by a popular musician, and autonomously downloading and fine-tuning a large language model. If science continues undisrupted, the chance of unaided machines outperforming humans in every possible task was estimated at 10% by 2027, and 50% by 2047. The latter estimate is 13 years earlier than that reached in a similar survey we conducted only one year earlier [Grace et al., 2022]. However, the chance of all human occupations becoming fully automatable was forecast to reach 10% by 2037, and 50% as late as 2116 (compared to 2164 in the 2022 survey). Most respondents expressed substantial uncertainty about the long-term value of AI progress: While 68.3% thought good outcomes from superhuman AI are more likely than bad, of these net optimists 48% gave at least a 5% chance of extremely bad outcomes such as human extinction, and 59% of net pessimists gave 5% or more to extremely good outcomes. Between 38% and 51% of respondents gave at least a 10% chance to advanced AI leading to outcomes as bad as human extinction. More than half suggested that "substantial" or "extreme" concern is warranted about six different AI-related scenarios, including misinformation, authoritarian control, and inequality. There was disagreement about whether faster or slower AI progress would be better for the future of humanity. However, there was broad agreement that research aimed at minimizing potential risks from AI systems ought to be prioritized more.

arXiv comments
The asterisk indicates the corresponding author. The dagger indicates equal contribution
Journal reference
Journal of Artificial Intelligence Research 84:9 (2025)
DOI
doi:10.1613/jair.1.19087
Subjects
cs.CYComputers and Society cs.AIArtificial Intelligence cs.LGMachine Learning

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Linked by 1 identifiable commenter in 1 comment across 1 thread, from Aug 2025 to Aug 2025. Found in 2 HN submissions from Jan 2024 to Oct 2026. Open submission discussions.

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    • > The thing is, AI researchers have continually underestimated the pace of AI progress What's your argument? That because experts aren't good at making predictions that non-experts must be BETTER at making predictions? Let me ask you this: who do you think is going to make a…

      godelskiView on HNParent context

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  • Thousands of AI Authors on the Future of AI
  • Ask HN: If you're struggling with p(doom), how are you handling it?

    I'm a VP of product at a small marketplace and a former full-stack dev. I use AI agents every day, connected to all sorts of tools, and I let them run on big projects. Ever since around the time of Jacob Coxon's post, I can't shake the logic that these capabilities will keep growing, proliferate, find their way into the wrong hands, and plausibly lead to mass casualties, or even the optimization of humans out of existence. Whatever you make of Coxon [1], the Hugging Face incident [2], or the…

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