Joseph Noel Walker (in SF 7-12 Nov; DC 12-17 Nov)

AI as Normal Tech is one of the most thoughtful, coherent pieces of policy writing in the last few years. If you haven’t read it, you should. Its policy recommendations get far less attention than its predictions though, and that’s warped the messages people take away from the essay. The authors do not argue that AI as Normal Tech = all will be well, do nothing. Instead they make the case that policy should focus on “reducing uncertainty” about the trajectory of the technology and its consequences + building resilience. I think that’s surprise a lot of people who like this general meme. It sure sounds a lot like most frontier AI policy proposals I encounter, and it would be vastly more ambitious than what we have right now. I’m not saying there’s no gap. But the fact that this essay has been cited to oppose many sensible, uncertainty-reducing policy proposals directly contradicts the conclusions of the authors. Incident reporting, whistleblower protections, transparency laws — all are cited as prime examples of good policy. And yet, more often than not, I hear this meme invoked to push back against the need for those exact policies. Did people just miss Section IV of the essay? No, I think what’s happening is that people want to read a careful, even-handed essay that is painstakingly precise to instead stand in for a general meme that supports their confidently held predictions for the future or to dunk on predictions they find implausible. But every bit of this essay shows that these authors actually mean what they say — they are carefully reasoners, who want to rigorously evaluate claims, and the same humility that leads them to push back on many claims of impending risk also make them admit their deep uncertainty about the future. They’re far less concerned about dunking on other people to prove they’re right, and much more focused on how to handle that uncertainty. So instead of rejecting policy efforts, they argue we should aim for policies that are “robust” to multiple assumptions and help us better understand the future. This seems empirically, normatively, and strategically compelling. The goal isn’t to bet all your chips on whatever belief you put 55% credence on. It’s to advance policies that handle the portfolio of possible outcomes well and help you adjust that portfolio more intelligently as you learn more. What this all means is that their predictive claims are less load-bearing than you might think. Sure, they predict AI will be a normal tech, but the practical upshot is that we aren’t sure and there are plenty of policy interventions that are robust to different empirical and normative beliefs. So we should pursue those! The reality is that most of those policies, which should represent some reasonable, moderate flank, remain unadopted, weak, or highly contested. And as valuable as arguing on Twitter is, the way to actually resolve these disputes is to build a policy system that allows us to learn and adapt, to “adjudicate it on the facts” so to speak. If people took that away from the essay, I think we’d be on a much better trajectory than we are now