rachelAF

17Joined Aug 2019

Bio

Rachel Freedman, AIS researcher at CHAI. London/Berkeley. Cats are not model-based reinforcement learners.

Comments
4

Book a chat with an EA professional

This is a great idea! I don't currently have capacity for one-to-one calls, but I do hold monthly small group calls in an "office hours" format.

I'm a technical AI safety researcher at CHAI and PhD student at UC Berkeley, and I'm happy to talk about my research, others' research, graduate school, careers in AI safety, and other related topics. If you're interested, you can find out more about my research here, and sign up to join an upcoming call here.

How I failed to form views on AI safety

Thank you for explaining more. In that case, I can understand why you'd want to spend more time thinking about AI safety.

I suspect that much of the reason that "understanding the argument is so hard" is because there isn't a definitive argument -- just a collection of fuzzy arguments and intuitions. The intuitions seem very, well, intuitive to many people, and so they become convinced. But if you don't share these intuitions, then hearing about them doesn't convince you. I also have an (academic) ML background, and I personally find some topics (like mesa-optimization) to be incredibly difficult to reason about.

I think that generating more concrete arguments and objections would be very useful for the field, and I encourage you to write up any thoughts that you have in that direction!

(Also, a minor disclaimer that I suppose I should have included earlier: I provided technical feedback on a draft of TAP, and much of the "AGI safety" section focuses on my team's work. I still think that it's a good concrete introduction to the field, because of how specific and well-cited it is, but I also am probably somewhat biased.)

How I failed to form views on AI safety

Thank you for writing this! I particularly appreciated hearing your responses to Superintelligence and Human Compatible, and would be very interested to hear how you would respond to The Alignment Problem. TAP is more grounded in modern ML and current research than either of the other books, and I suspect that this might help you form more concrete objections (and/or convince you of some points). If you do read it, please consider sharing your responses.

That said, I don’t think that you have any obligation to read TAP, or to consider thinking about AI safety at all. It sounds like you aren’t drawn to a career in the field, and that’s fine. There are plenty of other ways to do good with an ML skill set. But if you don’t need to weigh working in AI safety against other career options, and you don’t find it interesting or enjoyable to consider, then why focus on forming personal views about AI safety at all?

Edited to add a disclaimer: I provided technical feedback on a draft of TAP, and much of the "AGI safety" section focuses on my team's work. I still think that it's a good concrete introduction to the field, because of how specific and well-cited it is, but I also am probably somewhat biased.

Help CEA plan future events and conferences

This closely matches my personal experience of EAG. I typically have back-to-back meetings throughout the entire conference, including throughout all talks. At the most recent EAG London, I and a more senior person in my field mutually wanted to meet, and exchanged many messages like the one in the screenshot above -- "I just had a spot open up in 15 minutes if you're free?", "Are you taking a lunch break tomorrow?", etc. (We ultimately were not able to find mutual availability, and met on zoom a couple of weeks later.)

Like Charles, I don't necessarily think that this is a bad thing. However, if this is the primary intent of the conference, it could be improved somewhat to make small meetings easier (and possibly to include more events like the speaker reception, where people who spend the rest of the conference in prearranged 1:1s can casually chat).

I personally would be very excited about a conference app that allowed people to book small group (1:2) or (1:3) meetings. I find that many people I speak to ask the same questions, and that I am frustratingly unable to accommodate everyone who wants to have a 1:1. I sometimes hold group zoom calls (1:3 or 1:5) afterward for people who I wasn't able to meet during the conference, and this format seems to work well.