Calendar year when the 2023 ESPAI aggregate forecast assigns a 50% probability to high-level machine intelligence
- Measures
- The calendar year at which the aggregate forecast distribution (mean of fitted gamma CDFs across respondents) of the 2023 Expert Survey on Progress in AI (Grace et al., AI Impacts) reaches 50% probability that high-level machine intelligence exists, HLMI meaning unaided machines can accomplish every task better and more cheaply than human workers.
- Population
- 2,778 respondents to the 2023 ESPAI, authors at six top AI venues
- Conditions
- As reported by the survey authors (Grace et al. 2024, 'Thousands of AI Authors on the Future of AI'), assuming scientific activity continues without major negative disruption.
- Unit
- a calendar year
About 2047.
Stated as a single figure, the precision the evidence supports.
Assessment
The graph's estimate, all things considered: the figures and arguments it rests on, and how they were combined.
The 2023 Expert Survey on Progress in AI, reported by Katja Grace and colleagues in "Thousands of AI Authors on the Future of AI" (2024), puts the aggregate forecast's 50% chance of high-level machine intelligence in 2047. That is 13 years earlier than the 2060 figure from the 2022 survey. The figure is a fact about the survey's published aggregate, not a forecast of when such systems will actually arrive. The aggregate is built by fitting a distribution to each respondent's answers and averaging them. Respondents' views varied widely, and the answers were sensitive to how questions were framed: the related question about full automation of labor gave a much later 50% year, 2116. A different way of aggregating the answers would give a different year, but 2047 is the figure the authors report.
The work: which figures, how they were combined, and the arithmetic
The published value is 2047, from the survey report (arXiv 2401.02843, January 2024; revised 2024). The report says the aggregate gives a 50% chance of HLMI by 2047, 13 years earlier than the 2022 survey's 2060. The value is reported as a single year with no stated uncertainty. Since the quantity is defined as the reported aggregate, the estimate is a point at 2047. The only remaining doubt is whether a later revision of the report changed the figure, and I know of none. I did not reopen the source in this pass because the budget was limited. The figure is widely and consistently cited.
Estimates
Each figure a source states for this quantity, in its own words, under the argument it belongs to and read against the graph's estimate.
Grey band: the graph's estimate, with its central value as a line. Dark marks: each source's own figure. A thin line is an interval, a thick bar its middle half, a dot a single figure, a dashed arrow a bound. An open box is where an argument places the value.
Decomposition
This claim is atomic: it bottoms out in a bedrock fact, an open empirical question, or a value premise, and does not decompose further.
Provenance
Where this quantity's evidence comes from. The figures sources state are under Estimates above.
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 aggregate 2023 forecast predicted a 50% chance of HLMI by 2047, down thirteen years from 2060 in the 2022 survey.
HLMI: unaided machines can accomplish every task better and more cheaply than human workers; assumes science continues without major negative disruption. n=1,714.
Cite this claim: a formal citation with its evidence attached
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Created by extractor · Nov 1, 2026. Every judgment on this page is accompanied by a reasoning trace.