This post was written by Mark Xu based on interviews with Carl Shulman. It was paid for by Open Philanthropy but is not representative of their views. A draft was sent to Robin Hanson for review but received no response.

Summary

Robin Hanson estimates the time until human-level AI by surveying experts about the percentage progress to human-level that has happened in their particular subfield in the last 20 years, and dividing the number of years by the percentage progress.
Such surveys look back on a period of extremely rapid growth of compute from both hardware improvements and more recently skyrocketing spending.
Hanson favors using estimates from subsets of researchers with lower progress estimates to infer AI timelines requiring centuries worth of recent growth, implying truly extraordinary sustained compute growth is necessary to surpass human performance.
Extrapolated compute levels are very large to astronomically large compared to the neural computation that took place in evolution on Earth, and thus likely far overestimate AI requirements and timelines.

Introduction

Suppose that you start with $ $1$ that grows at 10% per year. At this rate, it will take ~241 years to get $ $10$ billion ($ $10^{10}$ ). When will you think that you’re ten percent of the way there?

You might say that you’re ten percent of the way to $ $10$ billion when you have $ $1$ billion. However, since your money is growing exponentially, it takes 217 years to go from $ $1$ to $ $1$ billion and only 24 more to go from $ $1$ billion to $ $10$ billion, even though the latter gap is larger in absolute terms. If you tried to guess when you would have $ $10$ billion by taking 10x the amount of time to $ $1$ billion, you would guess 2174 years, off by a factor of nine.

Instead, you might say you’re ten percent of the way to $ $10^{10}$ when you have $ $10^{1}$ , equally spacing the percentile markers along the exponent and measuring progress in terms of log(wealth). Since your money is growing perfectly exponentially, multiplying the number of years it takes to go from $ $1$ to $ $10$ by ten will produce the correct amount of time it will take to go from $ $1$ to $ $10^{10}$ .

When employing linear extrapolations, choosing a suitable metric that better tracks progress, like log wealth over wealth for investment, can make an enormous difference to forecast accuracy.

Hanson’s AI timelines estimation methodology

Hanson’s preferred method for estimating AI...

Surveys