Friend says quantitative forecasting of catastrophic AI risk not yet scientific

Madam Speaker, at Google, we take catastrophic risks and their possibility extremely seriously.

And we address that in a few ways.

One way is that we perform research into producing our own safety frameworks for artificial general intelligence.

So we have an AGI safety and security approach.

We also have a frontier safety framework, which is our protocols for monitoring our models under development for dangerous capabilities.

Those protocols then point to safety mitigations that we must take if we, in fact, cross what we call our critical capability levels.

Part of our testing and evaluation is, of course, using

commonly used benchmarks across the industry.

Those benchmarks do provide some quantification of the capabilities of the models themselves.

But when it comes to forecasting future catastrophic risk, it's not a perfect science at this stage.

And in this particular case, academics have noted that there is no reference class on which to base quantitative probabilities.

So we all have to be very humble about making such quantitative claims because there isn't really a rigorous scientific way to do those yet.