Last year, METR used linear extrapolation on country-level data to infer that AI world takeover would ~never happen. However, reviewers suggested that a sigmoid is more appropriate because most technologies follow S-curves. I just ran this analysis and it's much more concerning, predicting an AI world takeover in early 2027, and alarmingly, a second AI takeover around 2029.
Here are the main differences in the improved analysis:
* The original analysis assumed that the equation for AI takeover vs year would be axis-aligned, but this is an arbitrary basis. We now let the angle of the sigmoid fit the data as appropriate, meaning the following data model:
Interestingly, this results in a Z-curve (A < 0) rather than an S-curve. This is consistent with advanced AI being a substitute rather than a complement to labor.
* We now incorporate our priors. Even though we only have hard data since 2023, it's likely that the number of AI takeovers was lower pre-ChatGPT. So we added the inferred point (Nov 30 2022, -0.03). The rotated sigmoid still gets R^2 = 1.000 and now looks much better on BIC than exponential and step-function models, both of which have log-likelihood of minus infinity on negative points.
* This new graph uses only aggregate AI world takeover data, which we're much more confident in than our data from individual countries.
The most important next step is confirming that the # of AI takeovers was large negative in the past. If so, we should start preparing for AI takeover as a recurring rather than one-time event, which could have significant implications for movement strategy. For example, we may need to pivot into something more like seasonal preparedness, similar to how society handles flu outbreaks or daylight savings time.