Predictions of Human-Level AI Timelines

2022 Expert Survey on Progress in AI

Collected data and analysis from a large survey of machine learning researchers.

Surveys on fractional progress towards HLAI

How long until human-level performance, if we naively extrapolate progress since researchers joined their subfields?

Walsh 2017 survey

Toby Walsh surveyed hundreds of experts and non-experts in 2016 and found their median estimates for ‘when a computer might be able to carry out most human professions at least as well as a typical

Oren Etzioni surveyed 193 AAAI fellows in 2016 and found that 67% of them expected that ‘we will achieve Superintelligence’ someday, but in more than 25 years. Details Oren Etzioni, CEO of the Allen Institute

AGI-11 survey

The AGI-11 survey was a survey of 60 participants at the AGI-11 conference. In it: Nearly half of respondents believed that AGI would appear before 2030. Nearly 90% of respondents believed that AGI would appear

Chance date bias

There is modest evidence that people consistently forecast events later when asked the probability that the event occurs by a certain year, rather than the year in which a certain probability of the event will

2016 ESPAI Narrow AI task forecast timeline

This is an interactive timeline we made, illustrating the median dates when respondents said they expected a 10%, 50% and 90% chance of different tasks being automatable, in the 2016 Expert Survey on progress in

Automation of music production

Most machine learning researchers expect machines will be able to create top quality music by 2036. Details Evidence from survey data In the 2016 ESPAI, participants were asked two relevant questions: [Top forty] Compose a

2016 ESPAI questions printout

This is a list of questions from the 2016 Expert Survey on Progress in AI. Details This page is a printout of questions from the 2016 Expert Survey on Progress in AI provided by the

Media discussion of 2016 ESPAI

The 2016 Expert Survey on Progress in AI was discussed in at least 20 media outlets, popular blogs, and industry-specific sites that we know of. Most of them were summaries of the survey findings. Commonly

AI Impacts