Tamsin Leake

I'm Tamsin Leake, co-founder and head of research at Orthogonal, doing agent foundations.

Wiki Contributions


Reposting myself from discord, on the topic of donating 5000$ to EA causes.

if you're doing alignment research, even just a bit, then the 5000$ are probly better spent on yourself

if you have any gears level model of AI stuff then it's better value to pick which alignment org to give to yourself; charity orgs are vastly understaffed and you're essentially contributing to the "picking what to donate to" effort by thinking about it yourself

if you have no gears level model of AI then it's hard to judge which alignment orgs it's helpful to donate to (or, if giving to regranters, which regranters are good at knowing which alignment orgs to donate to)

as an example of regranters doing massive harm: openphil gave 30M$ to openai at a time where it was critically useful to them, (supposedly in order to have a chair on their board, and look how that turned out when the board tried to yeet altman)

i know of at least one person who was working in regranting and was like "you know what i'd be better off doing alignment research directly" — imo this kind of decision is probly why regranting is so understaffed

it takes technical knowledge to know what should get money, and once you have technical knowledge you realize how much your technical knowledge could help more directly so you do that, or something

So this option looks unattractive if you think transformative AI systems are likely to developed within the next 5 years. However, with a 10-years timeframe things look much stronger: you would still have around 5 years to contribute as a research.

This phrasing is tricky! If you think TAI is coming in approximately 10 years then sure, you can study for 5 years and then do research for 5 years.

But if you think TAI is coming within 10 years (for example, if you think that the current half-life on worlds surviving is 10 years; if you think 10 years is the amount of time in which half of worlds are doomed) then depending on your distribution-over-time you should absolutely not wait 5 years before doing research, because TAI could happen in 9 years but it could also happen in 1 year. If you think TAI is coming within 10 years, then (depending on your distribution) you should still in fact do research asap.

(People often get this wrong! They think that "TAI probably within X years" necessarily means "TAI in approximately X years".)

I'm confused about why 1P-logic is needed. It seems to me like you could just have a variable X which tracks "which agent am I" and then you can express things like sensor_observes(X, red) or is_located_at(X, northwest). Here and Absent are merely a special case of True and False when the statement depends on X.

Hence, the policy should have an escape clause: You should feel free to talk about the potential exfohazard if your knowledge of it isn't exclusively caused by other alignment researchers telling you of it. That is, if you already knew of the potential exfohazard, or if your own research later led you to discover it.

In an ideal world, it's good to relax this clause in some way, from a binary to a spectrum. For example: if someone tells me of a hazard that I'm confident I would've discovered one my own one week later, then they only get to dictate me not-sharing-it for a week. "Knowing" isn't a strict binary; anyone can rederive anything with enough time (maybe) — it's just a question of how long it would've taken me to find it if they didn't tell me. This can even include someone bringing my attention to something I already knew, but to which I wouldn't as quickly have thought to pay attention if they didn't bring attention to it.

In the non-ideal world we inhabit, however, it's unclear how fraught it is to use such considerations.

My current belief is that you do make some update upon observing existing, you just don't update as much as if we were somehow able to survive and observe unaligned AI taking over. I do agree that the no update at all because you can't see the counterfactual is wrong, but anthropics is still somewhat filtering your evidence; you should update less.

(I don't have my full reasoning for {why I came to this conclusion} fully loaded rn, but I could probably do so if needed. Also, I only skimmed your post, sorry. I have a post on updating under anthropics with actual math I'm working on, but unsure when I'll get around to finishing it.)

Due to my timelines being this short, I'm hopeful that convincing just "the current crop of major-AI-Lab CEOs" might actually be enough to buy us the bulk of time that something like this could buy.

commenting on this post because it's the latest in the sequence; i disagree with the premises of the whole sequence. (EDIT: whoops, the sequence posts in fact discuss those premises so i probably should've commented on those. ohwell.)

the actual, endorsed, axiomatic (aka terminal aka intrinsic) values we have are ones we don't want to change, ones we don't want to be lost or modified over time. what you call "value change" is change in instrumental values.

i agree that, for example, our preferences about how to organize the society we live in should change over time. but that simply means that our preference about society aren't terminal values, and our terminal values on this topic are meta-values about how other (non-terminal) values should change.

these meta-values, and other terminal values, are values that we should not want changed or lost over time.

in actuality, people aren't coherent agents enough to have immutable terminal values; they have value drift and confusion about values and they don't distinguish (or don't distinguish well) between terminal and instrumental values in their mind.

but we should want to figure out what our axiomatic values are, and for those to not be changed at all. and everything else being instrumental to that, we do not have to figure out alignment with regards to instrumental values, only axiomatic values.

one solution to this problem is to simply never use that capability (running expensive computations) at all, or to not use it before the iterated counterfactual researchers have developed proofs that any expensive computation they run is safe, or before they have very slowly and carefully built dath-ilan-style corrigible aligned AGI.

nothing fundamentally, the user has to be careful what computation they invoke.

an approximate illustration of QACI:

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