LessWrong 2.0 Reader

I agree that 0.7% is the number to beat for people who mostly focus on helping present humans and who don't take acausal or simulation argument stuff or cryonics seriously. I think that even if I was much more optimistic about AI alignment, I'd still think that number would be fairly plausibly beaten by a 1-year pause that begins right around the time of AGI. 

What are the mechanisms people have given and why are you skeptical of them?

Related content: https://www.shamusyoung.com/twentysidedtale/?p=168

Somewhat of a nitpick, but the relevant number would be p(doom | strong AGI being built) (maybe contrasted with p(utopia | strong AGI)) , not overall p(doom).

We use learning rate 0.0003 for all Gated SAE experiments, and also the GELU-1L baseline experiment. We swept for optimal baseline learning rates on GELU-1L for the baseline SAE to generate this value. 

For the Pythia-2.8B and Gemma-7B baseline SAE experiments, we divided the L2 loss by $E||x|{|}_2$, motivated by wanting better hyperparameter transfer, and so changed learning rate to 0.001 or 0.00075 for all the runs (currently in Figure 1, only attention output pre-linear uses 0.00075. In the rerelease we'll state all the values used). We didn't see noticable difference in the Pareto frontier changing between 0.001 and 0.0075 so did not sweep the baseline hyperparameter further than this.

This seems correct and important to me.

Maybe "counterfactually robust" is an OK phrase?

The vestibular system can detect whether you look up or down. It could be that the reflex triggers when you a) look down (vestibular system) and b) have a visual parallax that indicates depth (visual system).

Should be easy to test by closing one eye. Alternatively, it is the degree of accommodation of the lens. That should be testable by looking down with a lens that forces accommodation on short distances.

The negative should also be testable by asking congenitally blind people about their experience with this feeling of dizziness close to a rim.

And quantitatively I think it would improve overall chances of AGI going well by double-digit percentage points at least.

Makes sense. By comparison, my own unconditional estimate of p(doom) is not much higher than 10%, and so it's hard on my view for any intervention to have a double-digit percentage point effect.

The crude mortality rate before the pandemic was about 0.7%. If we use that number to estimate the direct cost of a 1-year pause, then this is the bar that we'd need to clear for a pause to be justified. I find it plausible that this bar could be met, but at the same time, I am also pretty skeptical of the mechanisms various people have given for how a pause will help with AI safety.

Thanks! Added.

Thanks! Added.