I think this is undignified.
I agree that it would be safer if humanity were a collective hivemind that could coordinate to not build AI until we know how to build the best AI, and that people should differentially work on things that make the situation better rather than worse, and that this potentially includes keeping quiet about information that would make things worse.
The problem is—as you say—”[i]t’s very rare that any research purely helps alignment”; you can’t think about aligning AI without thinking about AI. In order to navigate the machine intelligence transition in the most dignified way, you want your civilization’s best people to be doing their best thinking about the problem, and your best people can’t do their best thinking under the conditions of paranoid secrecy.
Concretely, I’ve been studying some deep learning basics lately and have written a couple posts about things I’ve learned. I think this was good, not bad. I think I and my readers have a slightly better understanding of the technology in question than if I hadn’t studied and hadn’t written, and that better understanding will help us make better decisions in expectation.
This applies doubly so to work that aims to make AI understandable or helpful, rather than aligned—a helpful AI will help anyone
Sorry, what? I thought the fear was that we don’t know how to make helpful AI at all. (And that people who think they’re being helped by seductively helpful-sounding LLM assistants are being misled by surface appearances; the shoggoth underneath has its own desires that we won’t like when it’s powerful enough to persue them autonomously.) In contrast, this almost makes it sound like you think it is plausible to align AI to its user’s intent, but that this would be bad if the users aren’t one of “us”—you know, the good alignment researchers who want to use AI to take over the universe, totally unlike those evil capabilities researchers who want to use AI to produce economically valuable goods and services.
I think these judgements would benefit from more concreteness: that rather than proposing a dichotomy of “capabilities research” (them, Bad) and “alignment research” (us, Good), you could be more specific about what kinds of work you want to see more and less of.
I agree that (say) Carmack and Sutton are doing a bad thing by declaring a goal to “build AGI” while dismissing the reasons that this is incredibly dangerous. But the thing that makes infohazard concerns so fraught is that there’s a lot of work that potentially affects our civilization’s trajectory into the machine intelligence transition in complicated ways, which makes it hard to draw a boundary around “trusted alignment researchers” in a principled and not self-serving way that doesn’t collapse into “science and technology is bad”.
We can agree that OpenAI as originally conceived was a bad idea. What about the people working on music generation? That’s unambiguously “capabilities”, but it’s also not particularly optimized at ending the world that way “AGI for AGI’s sake” projects are. If that’s still bad even though music generation isn’t going to end the world (because it’s still directing attention and money into AI, increasing the incentive to build GPUs, &c.), where do you draw the line? Some of the researchers I cited in my most recent post are working on “build[ing] better models of primate visual cognition”. Is that wrong? Should Judea Pearl not have published? Turing? Charles Babbage?
In asking these obnoxious questions, I’m not trying to make a reductio ad absurdum of caring about risk, or proposing an infinitely slippery slope where our only choices are between max accelerationism and a destroy-all-computers Butlerian Jihad. I just think it’s important to notice that “Stop thinking about AI” kind of does amount to a Butlerian Jihad (and that publishing and thinking are not unrelated)?