Thousands of AI Authors on the Future of AI

Abstract

In October 2023, 2,778 researchers who had published in top-tier artificial intelligence (AI) venues gave predictions on the pace, nature and impacts of AI progress. Significant steps were taken to minimize and evaluate bias. In evaluations of participation bias, we found that most groups responded at similar rates. The participants estimated that several milestones had at least a 50% chance of being feasible for AI by 2028, including constructing a payment processing site and fine-tuning an LLM. 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—13 years earlier than in our 2022 survey (N = 738). The chance of all occupations becoming fully automatable, however, was not expected to reach 10% until 2037, and 50% until 2116 (compared to 2164 in the 2022 survey. Most respondents expressed substantial uncertainty about long-term impacts: While 68% in 2023 thought good outcomes from high-level machine intelligence AI were more likely than bad ones, 48% of these net optimists gave at least a 5% chance of extremely bad outcomes. Conversely, 59% of net pessimists gave 5% or more to extremely good outcomes. Depending on how we asked, 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 AI increasing misinformation, boosting authoritarian control, worsening inequality, and other scenarios. There was broad agreement that research aimed at minimizing risks from AI systems ought to be more prioritized.

Cite

Text

Grace et al. "Thousands of AI Authors on the Future of AI." Journal of Artificial Intelligence Research, 2025. doi:10.1613/JAIR.1.19087

Markdown

[Grace et al. "Thousands of AI Authors on the Future of AI." Journal of Artificial Intelligence Research, 2025.](https://mlanthology.org/jair/2025/grace2025jair-thousands/) doi:10.1613/JAIR.1.19087

BibTeX

@article{grace2025jair-thousands,
  title     = {{Thousands of AI Authors on the Future of AI}},
  author    = {Grace, Katja and Sandkühler, Julia Fabienne and Stewart, Harlan and Weinstein-Raun, Benjamin and Thomas, Stephen and Stein-Perlman, Zach and Salvatier, John and Brauner, Jan and Korzekwa, Richard C.},
  journal   = {Journal of Artificial Intelligence Research},
  year      = {2025},
  doi       = {10.1613/JAIR.1.19087},
  volume    = {84},
  url       = {https://mlanthology.org/jair/2025/grace2025jair-thousands/}
}