Spencer Becker-Kahn

Wiki Contributions


DeepMind is hiring for the Scalable Alignment and Alignment Teams

Hi there,

Given that you've described various 'primarily conceptual' projects on the Alignment Team, and given the distinction between Scientists and Engineers, one aspect that I'm unsure about is roughly: Would you expect a Research Scientist on the Alignment Team to necessarily have a minimum level of practical ML knowledge? Are you able to say any more about that? e.g.  Would they have to pass a general Deep Mind coding test or something like that? 

SERI ML Alignment Theory Scholars Program 2022

Hi Ryan, do you still plan for results to come out by May 27? And for those who are successful for the next stage to start June 6th etc.? (That's what is says on the FAQ on the website still). 

Intuitions about solving hard problems

Yes I think you understood me correctly. In which case I think we more or less agree in the sense that I also think it may not be productive to use Richard's heuristic as a criterion for which research directions to actually pursue.

Intuitions about solving hard problems

I broadly agree with Richard's main point, but I also do agree with this comment in the sense that I am not confident that the example of Turing compared with e.g. Einstein is completely fair/accurate. 

One thing I would say in response to your comment, Adam, is that I don't usually see the message of your linked post as being incompatible with Richard's main point. I think one usually does have or does need productive mistakes that don't necessarily or obviously look like they are robust partial progress. But still, often when there actually is a breakthrough, I think it can be important to look for this "intuitively compelling" explanation. So one thing I have in mind is that I think it's usually good to be skeptical if a claimed breakthrough seems to just 'fall out' of a bunch of partial work without there being a compelling explanation after the fact.

Call For Distillers

I agree i.e. I also (fairly weakly) disagree with the value of thinking of 'distilling'  as a separate thing. Part of me wants to conjecture that it's comes from thinking of alignment work predominantly as mathematics or a hard science in which the standard 'unit' is a an original theorem or original result which might be poorly written up but can't really be argued against much. But if we think of the area (I'm thinking predominantly about more conceptual/theoretical alignment) as a 'softer', messier, ongoing discourse full of different arguments from different viewpoints and under different assumptions, with counter-arguments, rejoinders, clarifications, retractions etc. that takes place across blogs, papers, talks, theorems, experiments etc that all somehow slowly works to produce progress, then it starts to be less clear what this special activity called 'distilling' really is. 

Another relevant point, but one which I won't bother trying to expand on much here, is that a research community assimilating - and then eventually building on - complex ideas can take a really long time. 

[At risk of extending into a rant, I also just think the term is a bit off-putting. Sure, I can get the sense of what it means from the word and the way it is used - it's not completely opaque or anything - but I'd not heard it used regularly in this way until I started looking at the alignment forum. What's really so special about alignment that we need to use this word? Do we think we have figured out some new secret activity that is useful for intellectual progress that other fields haven't figured out? Can we not get by using words like "writing" and "teaching" and "explaining"?]

Job Offering: Help Communicate Infrabayesianism

It could also work here. But I do feel like pointing out that the bounty format has other drawbacks. Maybe it works better when you want a variety of bitesize contributions, like various different proposals? I probably wouldn't do work like Abram proposes - quite a long and difficult project, I expect - for the chance of winning a prize, particularly if the winner(s) were decided by someone's subjective judgement. 

Job Offering: Help Communicate Infrabayesianism

This post caught my eye as my background is in mathematics and I was, in the not-too-distant past, excited about the idea of rigorous mathematical AI alignment work. My mind is still open to such work but I'll be honest, I've since become a bit less excited than I was. In particular, I definitely "bounced off" the existing write-ups on Infrabayesianism and now without already knowing what it's all about, it's not clear it's worth one's time. So, at the risk of making a basic or even cynical point: The remuneration of the proposed job could be important for getting attention/ incentivising people on-the-fence.