When do experts think humanlevel AI will be created?
Short answer: within your lifetime.
It’s hard to precisely predict the amount of time until humanlevel AI (HLAI)^{[1]}. Approaches include aggregate predictions, individual predictions, and detailed modeling.
Aggregate predictions:

AI Impacts’ 2022 survey of 738 machine learning researchers produced an aggregate forecast of 50% by 2059.

As of June 2024, Metaculus^{[2]} has a median forecast of 2031 for “the first general AI system” and a median forecast of 2027 for “weakly general AI”. Both these timeline forecasts have been shortening over time.

This website combines predictions from different forecasting platforms into a single (possibly inconsistent) timeline of events.

In January 2023, Samotsvety’s forecasters estimated 50% probability of AGI by 2041 with a standard deviation of 9 years.
Individual predictions:

Daniel Kokotajlo’s 2023 analysis predicted 2028.

Connor Leahy, CEO of Conjecture, gave a ballpark prediction in 2022 of a 50% chance of AGI by 2030, 99% by 2100. A 2023 survey of employees at Conjecture found that all of the respondents expected AGI before 2035.

Holden Karnofsky estimated in 2021 that there was “more than a 10% chance we'll see transformative AI within 15 years (by 2036); a ~50% chance we'll see it within 40 years (by 2060); and a ~⅔ chance we'll see it this century (by 2100).”

Paul Christiano estimated in 2023 that there was a 30% chance of transformative AI by 2033.

Yoshua Bengio estimated “a 95% confidence interval for the time horizon of superhuman intelligence at 5 to 20 years” in 2023.

Geoffrey Hinton also predicted 520 years in 2023, but his confidence is lower.

Shane Legg estimated a probability of 80% within 13 years (before 2037) in 2023.
Models:

A report by Ajeya Cotra for Open Philanthropy estimated the arrival of transformative AI (TAI) based on “biological anchors”^{[3]}. In the 2020 version of the report, she predicted a 50% chance by 2050, but developments in AI in the two years that followed pushed her estimate to 2040 in 2022.

Matthew Barnett created a model based on the “direct approach” of extrapolating training lossthat as of Q2 2024 outputs a median estimate of transformative AI around 2053^{[4]}.

Epoch has done a literature review of timelines.
These forecasts are speculative,^{[5]} depend on various assumptions, predict different things (e.g., transformative versus humanlevel AI), and are subject to selection bias.^{[6]} However, they broadly agree that HLAI is plausible within the lifetimes of most people alive today. What’s more, these forecasts generally seem to have been getting shorter over time.
We concentrate here on HLAI and similar levels of capacities such as Transformative AI (TAI), which may be different from AGI. For more info on these terms, see this explainer. ↩︎
Metaculus is a platform that aggregates the predictions of many individuals, and tends to have a decent track record at making predictions related to AI. ↩︎
The author estimates the amount of compute done by biological evolution in the development of human intelligence and argues this should be considered an upper bound on the amount of synthetic compute necessary to develop HLAI. ↩︎
Based on the final graph titled “Cumulative probability distribution over TAI”. ↩︎
Scott Alexander points out that researchers that appear prescient one year sometimes predict barely better than chance the next year. ↩︎
One can expect people with short timelines to be overrepresented in those who study AI safety, as shorter timelines increase the perceived urgency of working on the problem. ↩︎