A new paper titled When Will AI Exceed Human Performance? Evidence from AI Experts reports some bizarre results. From the abstract:

Researchers believe there is a 50% chance of AI outperforming humans in all tasks in 45 years and of automating all human jobs in 120 years, with Asian respondents expecting these dates much sooner than North Americans.

So we should expect a 75 year period in which machines can perform all tasks better and more cheaply than humans, but can’t automate all occupations. Huh?

I suppose there are occupations that consist mostly of having status rather than doing tasks (queen of England, or waiter at a classy restaurant that won’t automate service due to the high status of serving food the expensive way). Or occupations protected by law, such as gas station attendants who pump gas in New Jersey, decades after most drivers switched to pumping for themselves.

But I’d be rather surprised if machine learning researchers would think of those points when answering a survey in connection with a machine learning conference.

Maybe the actual wording of the survey questions caused a difference that got lost in the abstract? Hmmm …

“High-level machine intelligence” (HLMI) is achieved when unaided machines can accomplish every task better and more cheaply than human workers

versus

when all occupations are fully automatable. That is, when for any occupation, machines could be built to carry out the task better and more cheaply than human workers.

I tried to convince myself that the second version got interpreted as referring to actually replacing humans, while the first version referred to merely being qualified to replace humans. But the more I compared the two, the more that felt like wishful thinking. If anything, the “unaided” in the first version should make that version look farther in the future.

Can I find any other discrepancies between the abstract and the details? The 120 years in the abstract turns into 122 years in the body of the paper. So the authors seem to be downplaying the weirdness of the results.

There’s even a prediction of a 50% chance that the occupation “AI researcher” will be automated in about 88 years (I’m reading that from figure 2; I don’t see an explicit number for it). I suspect some respondents said this would take longer than for machines to “accomplish every task better and more cheaply”, but I don’t see data in the paper to confirm that [1].

A more likely hypothesis is that researchers alter their answers based on what they think people want to hear. Researchers might want to convince their funders that AI deals with problems that can be solved within the career of the researcher [2], while also wanting to reassure voters that AI won’t create massive unemployment until the current generation of workers has retired.

That would explain the general pattern of results, although the magnitude of the effect still seems strange. And it would imply that most machine learning researchers are liars, or have so little understanding of when HLMI will arrive that they don’t notice a 50% shift in their time estimates.

The ambiguity in terms such as “tasks” and “better” could conceivably explain confusion over the meaning of HLMI. I keep intending to write a blog post that would clarify concepts such as human-level AI and superintelligence, but then procrastinating because my thoughts on those topics are unclear.

It’s hard to avoid the conclusion that I should reduce my confidence in any prediction of when AI will reach human-level competence. My prior 90% confidence interval was something like 10 to 300 years. I guess I’ll broaden it to maybe 8 to 400 years [3].

P.S. – See also Katja’s comments on prior surveys.

[1] – the paper says most participants were asked the question that produced the estimate of 45 years to HLMI, the rest got the question that produced the 122 year estimate. So the median for all participants ought to be less than about 84 years, unless there are some unusual quirks in the data.

[2] – but then why do experienced researchers say human-level AI is farther in the future than new researchers, who presumably will be around longer? Maybe the new researchers are chasing fads or get-rich-quick schemes, and will mostly quit before becoming senior researchers?

[3] – years of subjective time as experienced by the fastest ems. So probably nowhere near 400 calendar years.