Forecasting AI Progress: Evidence from a Survey of Machine Learning Researchers
Baobao Zhang, Noemi Dreksler, Markus Anderljung, Lauren Kahn, Charlie, Giattino, Allan Dafoe, Michael C. Horowitz

TL;DR
This study surveys AI/ML researchers to gather forecasts on AI progress, revealing a median estimate of 2060 for human-level AI and increased optimism about near-term milestones and societal impacts.
Contribution
It provides updated forecasts from AI researchers on AI development timelines and compares them with previous studies, highlighting trends and shifts in expert expectations.
Findings
50% chance of human-level AI by 2060
Near-term milestones forecasted to occur sooner
Researchers are optimistic about societal impacts
Abstract
Advances in artificial intelligence (AI) are shaping modern life, from transportation, health care, science, finance, to national defense. Forecasts of AI development could help improve policy- and decision-making. We report the results from a large survey of AI and machine learning (ML) researchers on their beliefs about progress in AI. The survey, fielded in late 2019, elicited forecasts for near-term AI development milestones and high- or human-level machine intelligence, defined as when machines are able to accomplish every or almost every task humans are able to do currently. As part of this study, we re-contacted respondents from a highly-cited study by Grace et al. (2018), in which AI/ML researchers gave forecasts about high-level machine intelligence and near-term milestones in AI development. Results from our 2019 survey show that, in aggregate, AI/ML researchers surveyed…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsBig Data and Business Intelligence
