I have yet to write detailed scenarios for AI futures, which definitely seems like something I should do considering the title of my blog (Forecasting AI Futures). I have speculated, pondered and wondered much in the recent weeks—I feel it is time. But first, I have some thoughts about scenario forecasting.

The plan:

Write down general thoughts about scenario forecasting with special focus on AI (this post).
Write one or two specific scenarios for events over the coming months and years.
Wait a few months, see what comes true, and update my scenario forecasting methods.

Other work

In 2021, Daniel Kokotaljo published a scenario titled What 2026 looks like. He managed to predict many important aspects of the progression of AI between 2021 and now, such as chatbots, chain-of-thought, and inference compute scaling.

Now he is collaborating with other forecasters—including Eli Lifland, a superforecaster from the Samotsvety forecasting group—to develop a highly detailed and well-researched scenario forecast under the AI Futures Project. Designed to be as predictively accurate as possible, it illustrates how the world might change as AI capabilities evolve. The scenario is scheduled to be published in Q1 of this year.

I also recommend reading Scale Was All We Needed, At First and How AI Takeover Might Happen in 2 Years, two brilliant stories exploring scenarios with very short timelines to superintelligence.

Using and Misusing Scenario Forecasting

People may hear about a specific superintelligence disaster scenario, and then confidently say something like “That seems entirely implausible!” or “AIs will just be tools, not agents!” or “If it tried that, humans could just [insert solution].”

There is some fundamental issue here. Those who see significant risks struggle to convey their concerns to those who think everything is fine.

And I think this problem at least partly has to do with scenario forecasting. One side is envisioning specific bad scenarios, which can easily be refuted. The other side is envisioning specific good scenarios, which can also be easily refuted.

The question we should consider is something more like “Out of all possible scenarios, how many lead to positive outcomes versus negative ones?”. But this question is harder to reason about, and any reasoning about it takes longer to convey.

We can start by considering what avoiding the major risks would mean. The w...

Task Prioritization