Toby Ord

This shows both that each expert has a broad distribution and that the expert community on the whole has an even broader one.

Indeed, I think you could do a lot worse than just taking a mixture model of these three experts' views.

Interestingly, since 2023, Coco Taljo's distribution has shifted to the right and Erdil's to the left.

Here's an illustrative distribution for AGI timelines used by Ben Todd of 80,000 hours.

There's an image here.

Dvorkesh Patel reproduced it in his post about AI timelines, saying that it pretty much represented his own uncertainty, giving his median date of 2032 for AI that learns on the job as easily, organically, seamlessly, and quickly as a human, for any white-collar work.

Here is Metaculous's current community estimate for when AGI will be developed.

Synthesizing the community's collective uncertainty, it is very broad and has this same characteristic shape.

There's an image here.

Here is Epoch AI's summary of leading estimates of AI timelines from 2023.

There's an image here.

These look a bit different as they are represented as cumulative probabilities of reaching transformative AI by a given time.

But they are all very broad.

Take a look at the range of years between when they cross 10% to when they cross 90%.

Every single one has an 80% interval at least 50 years wide.

What about researchers working on AI capabilities?

Grace et al.

surveyed thousands of AI researchers who were presenting at their top academic conferences.

They surveyed the researchers in 2022, blue, and 2023, red, about when unaided machines can accomplish every task better and more cheaply than human workers.

There's an image here.