Host of the Technical AI Safety Podcast https://technical-ai-safety.libsyn.com
Coorganizer of EA Philly
Streams Linear Algebra Done Right in Coq on twitch https://twitch.tv/quinndougherty92
If I must make a really bad first approximation, I would say a rubber band is attached to the moral circle, and on the other end of the rubber band is the political circle, so when the moral circle expands it drags the political circle along with it on a delay, modulo some metaphorical tension and inertia. This rubber band model seems informative in the slave case, but uselessly wrong in the chickens case, and points to some I think very real possibilities in the AI case.
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In Think Tank Junior Fellow, OP writes
Recently obtained a bachelor’s or master’s degree (including Spring 2022 graduates)
How are you thinking about this requirement? Is there something flex about it (like when a startup says they want a college graduate) or are there bureaucratic forces at partner organizations locking it in stone (like when a hospital IT department says they want a college graduate)? Perhaps describe properties of a hypothetical candidate that would inspire you to flex this requirement?
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Ah, just saw email@example.com at the bottom of the page. Sorry, will direct my question to there!
Hi Luke, could you describe a candidate that would inspire you to flex the bachelor's requirement for Think Tank Jr. Fellow? I took time off credentialed institutions to do lambda school and work (didn't realize I want to be a researcher until I was already in industry), but I think my overall CS/ML experience is higher than a ton of the applicants you're going to get (I worked on cooperative AI at AI Safety Camp 5 and I'm currently working on multi-multi delegation, hence my interest in AI governance). If possible, I'd like to hear from you how you're thinking about the college requirement before I invest the time into writing a cumulative 1400 words.
Awesome! I probably won't apply as I lack political background and couldn't tell you the first thing about running a poll, but my eyes will be keenly open in case you post a broader data/analytics job as you grow. Good luck with the search!
I'm thrilled about this post - during my first two-three years of studying math/cs and thinking about AGI my primary concern was the rights and liberties of baby agents (but I wasn't giving suffering nearly adequate thought). Over the years I became more of an orthodox x-risk reducer, and while the process has been full of nutritious exercises, I fully admit that becoming orthodox is a good way to win colleagues, not get shrugged off as a crank at parties, etc. and this may have played a small role, if not motivated reasoning then at least humbly deferring to people who seem like they're thinking clearer than me.
I think this area is sufficiently undertheorized and neglected that the following is only hypothetical, but could become important: how is one to tradeoff between existential safety (for humans) and suffering risks (for all minds)?
I find myself shocked at point #2, at the inadequacy of the state of theory of these tradeoffs. Is it premature to worry about that before the AS movement has even published a detailed agenda/proposal of how to allocate research effort grounded in today's AI field? Much theorization is needed to even get to that point, but it might be wise to think ahead.
I look forward to reading the preprint this week, thanks
I've been increasingly hearing advice to the effect that "stories" are an effective way for an AI x-safety researcher to figure out what to work on, that drawing scenarios about how you think it could go well or go poorly and doing backward induction to derive a research question is better than traditional methods of finding a research question. Do you agree with this? It seems like the uncertainty when you draw such scenarios is so massive that one couldn't make a dent in it, but do you think it's valuable for AI x-safety researchers to make significant (i.e. more than 30% of their time) investments in both 1. doing this directly by telling stories and attempting backward induction, and 2. training so that their stories will be better/more reflective of reality (by studying forecasting, for instance)?
So I read Gwern and I also read this Dylan Matthews piece, I'm fairly convinced the revolution did not lead to the best outcomes for slaves and for indigenous people. I think there are two cruxes for believing that it would be possible to make this determination in real-time:
One of my core assumptions, which is up for debate, is that EAs ought to focus on outcomes for slaves and indigenous people more than the general case of outcomes.
I'm puzzled by the lack of push to convert Patrick Collision. Paul Graham once tweeted that Stripe would be the next google, so if Patrick Collision doesn't qualify as a billionaire yet, it might be a good bet that he will someday (I'm not strictly basing that on PG's authority, I'm also basing that on my personal opinion that Stripe seems like world domination material). He cowrote this piece "We need a science of progress" and from what I heard in this interview, signs point to a very EA-sympathetic person.