In case people are interested, while updating updating Epoch’s Literature Review of AI Timelines with this new forecast, I created a small notebook which uses a slightly different approach to aggregating the individual forecasts. Briefly, I fit a Gamma distribution to each forecast, which produces a CDF. Then, I combine the fitted CDFs using the geometric mean of odds. (This general approach is inspired by what AI Impacts has done in their expert surveys, although they use a different method of aggregating the fitted CDFs.) The final results are pretty similar, although a little more aggressive in the short- and longer-term, and a little less aggressive in the medium-term:
P(AGI by ___):
2030: 28%
2050: 59%
2100: 89%
Year when P(AGI) reaches ___:
10%: 2024
50%: 2043
90%: 2104
The notebook also includes some simple plots of the forecasts which you can play with.
In case people are interested, while updating updating Epoch’s Literature Review of AI Timelines with this new forecast, I created a small notebook which uses a slightly different approach to aggregating the individual forecasts. Briefly, I fit a Gamma distribution to each forecast, which produces a CDF. Then, I combine the fitted CDFs using the geometric mean of odds. (This general approach is inspired by what AI Impacts has done in their expert surveys, although they use a different method of aggregating the fitted CDFs.) The final results are pretty similar, although a little more aggressive in the short- and longer-term, and a little less aggressive in the medium-term:
P(AGI by ___):
2030: 28%
2050: 59%
2100: 89%
Year when P(AGI) reaches ___:
10%: 2024
50%: 2043
90%: 2104
The notebook also includes some simple plots of the forecasts which you can play with.