Note: This page is out of date. See an up-to-date version of this page on our wiki. Updated 5 June 2015 We know of around 1,300 public predictions of when human-level AI will arrive, of
Updated 4 June 2015 It is unclear how informative we should expect expert predictions about AI timelines to be. Individual predictions are undoubtedly often off by many decades, since they disagree with each other. However their aggregate may still be quite informative. The
We expect predictions that human-level AI will come sooner to be recorded publicly more often, for a few reasons. Public statements are probably more optimistic than surveys because of such effects. The difference appears to be less than
Experts on AI probably systematically underestimate time to human-level AI, due to a selection bias. The same is more strongly true of AGI experts. The scale of such biases appears to be decades. Most public AI predictions
Updated 9 November 2020 In 2015 AGI researchers appeared to expect human-level AI substantially sooner than other AI researchers. The difference ranges from about five years to at least about sixty years as we move
The Maes-Garreau law posits that people tend to predict exciting future technologies toward the end of their lifetimes. It probably does not hold for predictions of human-level AI. Clarification From Wikipedia: The Maes–Garreau law is the statement that “most favorable
Surveys seem to produce median estimates of time to human-level AI which are roughly a decade later than those produced from voluntary public statements. Details We compared several surveys to predictions made by similar groups of
The MIRI AI predictions dataset is a collection of public predictions about human-level AI timelines. We edited the original dataset, as described below. Our dataset is available here, and the original here. Interesting features of the dataset
Traversed Edges Per Second (TEPS) is a benchmark for measuring a computer’s ability to communicate information internally. Given several assumptions, we can also estimate the human brain’s communication performance in terms of TEPS, and use this
The presence of glial cells may increase the capacity for signaling in the brain by a small factor, but is unlikely to qualitatively change the nature or extent of signaling in the brain. Support Number