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Harry Potter and The Methods of Rationality

What if Harry was a scientist? What would you do if the universe had magic in it? 
A story that conveys many rationality concepts, helping to make them more visceral, intuitive and emotionally compelling.

Vladimir_Nesov19hΩ15249
Comparing Payor & Löb
I would term □x→x "hope for x" rather than "reliability", because it's about willingness to enact x in response to belief in x, but if x is no good, you shouldn't do that. Indeed, for bad x, having the property of □x→x is harmful fatalism, following along with destiny rather than choosing it. In those cases, you might want to □x→¬x or something, though that only prevents x from being believed, that you won't need to face □x in actuality, it doesn't prevent the actual x. So □x→x reflects a value judgement about x reflected in agent's policy, something downstream of endorsement of x, a law of how the content of the world behaves according to an embedded agent's will. Payor's Lemma then talks about belief in hope □(□x→x), that is hope itself is exogenous and needs to be judged (endorsed or not). Which is reasonable for games, since what the coalition might hope for is not anyone's individual choice, the details of this hope couldn't have been hardcoded in any agent a priori and need to be negotiated during a decision that forms the coalition. A functional coalition should be willing to act on its own hope (which is again something we need to check for a new coalition, that might've already been the case for a singular agent), that is we need to check that □(□x→x) is sufficient to motivate the coalition to actually x. This is again a value judgement about whether this coalition's tentative aspirations, being a vehicle for hope that x, are actually endorsed by it. Thus I'd term □(□x→x) "coordination" rather than "trust", the fact that this particular coalition would tentatively intend to coordinate on a hope for x. Hope □x→x is a value judgement about x, and in this case it's the coalition's hope, rather any one agent's hope, and the coalition is a temporary nascent agency thing that doesn't necessarily know what it wants yet. The coalition asks: "If we find ourselves hoping for x together, will we act on it?" So we start with coordination about hope, seeing if this particular hope wants to settle as the coalition's actual values, and judging if it should by enacting x if at least coordination on this particular hope is reached, which should happen only if x is a good thing. (One intuition pump with some limitations outside the provability formalism is treating □x as "probably x", perhaps according to what some prediction market tells you. If "probably x" is enough to prompt you to enact x, that's some kind of endorsement, and it's a push towards increasing the equilibrium-on-reflection value of probability of x, pushing "probably x" closer to reality. But if x is terrible, then enacting it in response to its high probability is following along with self-fulfilling doom, rather doing what you can to push the equilibrium away from it.) Löb's Theorem then says that if we merely endorse a belief by enacting the believed outcome, this is sufficient for the outcome to actually happen, a priori and without that belief yet being in evidence. And Payor's Lemma says that if we merely endorse a coalition's coordinated hope by enacting the hoped-for outcome, this is sufficient for the outcome to actually happen, a priori and without the coordination around that hope yet being in evidence. The use of Löb's Theorem or Payor's Lemma is that the condition (belief in x, or coordination around hope for x) should help in making the endorsement, that is it should be easier to decide to x if you already believe that x, or if you already believe that your coalition is hoping for x. For coordination, this is important because every agent can only unilaterally enact its own part in the joint policy, so it does need some kind of premise about the coalition's nature (in this case, about the coalition's tentative hope for what it aims to achieve) in order to endorse playing its part in the coalition's joint policy. It's easier to decide to sign an assurance contract than to unconditionally donate to a project, and the role of Payor's Lemma is to say that if everyone does sign the assurance contract, then the project will in fact get funded sufficiently.
Nina Panickssery10h164
Mourning a life without AI
Your Substack subtitle is "I won't get to raise a family because of AGI". It should instead be "I don't want to raise a family because of AGI" I think it's >90% likely that if you want and try to, you can raise a family in a relatively normal way (i.e. your wife gives birth to your biological children and you both look after them until they are adults) in your lifetime.  Not wanting to do this because those children will live in a world dissimilar to today's is another matter, but note that your parents also raised you to live in a world very dissimilar from the world they grew up in, but were motivated to do it anyway! So far, over many generations, people have been motivated to build families not by the confidence that their children will live in the same way as they did, but rather by other drives (whether it's a drive towards reproduction, love, curiosity, norm-following, etc.). I also think you're very overconfident about superintelligence appearing in our lifetimes, and X-risk being high, but I don't see why either of those things stop you from having a family. 
Raemon5d*9747
Heroic Responsibility
I think this part of Heroic Responsibility isn't too surprising/novel to people. Obviously the business owner has responsibility for the business. The part that's novel is more like: If I'm some guy working in legal, and I notice this hot potato going around, and it's explicitly not my job to deal with it, I might nonetheless say "ugh, the CEO is too busy to deal with this today and it's not anyone else's job. I will deal with it." Then you go to each department head, even if you're not even a department head you're a lowly intern (say), and say "guys, I think we need to decide who's going to deal with this." And if their ego won't let them take advice from an intern, you might also take it as your responsibility to figure out how to navigate their ego – maybe by making them feel like it was their own idea, or by threatening to escalate to the CEO if they don't get to it themselves, or by appealing to their sense of duty. A great example of this, staying with them realm of "random Bureaucracy", I got from @Elizabeth: E. D. Morel was a random bureaucrat at a shipping company in 1891. He noticed that his company was shipping guns and manacles into the Congo, and shipping rubber and other resources back out to Britain. It was not Morel's job to notice that this was a bit weird. It was not Morel's job to notice that that weirdness was a clue, and look into those clues. And then find out that what was happening was, weapons were being sent to the Congo to forcibly steal resources at gunpoint. It was not his job to make it his mission to raise awareness of the Congo abuses and stop them. But he did. ... P.S. A failure mode of rationalists is to try to take Heroic responsibility for everything, esp. in a sort of angsty way that is counterproductive and exhausting. It's also a failure mode to act as if only you can possibly take Heroic responsibility, rather than trying to model the ecosystem around you and the other actors (some of whom might be Live Players who are also taking Heroic Responsibility, some of whom might be sort of local actors following normal incentives but are still, like, part of the solution) There is nuance to when and how to do Heroic Responsibility well.
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Mo Putera7h350
EJT
1
This MO thread initiated by Bill Thurston on the varied ways mathematicians think about math has always made me wonder how theoretical researchers in other fields think about their domains. I think of this as complementary to Mumford's tribes of mathematicians, and (much more tangentially) to Eliezer's remark on how sparse thinkers are at the intellectual frontiers.  ---------------------------------------- Here are some of my favorite quotes. Terry Tao talks about an "adversarial perspective" which I'm guessing is the closest match to how alignment researchers think: There's the "economic" mindset; Tao again: Physical analogies; Tao again: Visualisation techniques; Tao again: Another take on visual thinking, by François G. Dorais: Benson Farb on Thurston's visual-geometric way of thinking about higher dimensions – Thurston was widely considered the best geometric thinker in the history of math: At a more elementary level, here's Phil Issett on geometric thinking: Qiaochu Yuan's way of thinking about determinants isn't one I've seen written up before:   Subconscious thought processing "masticating" tons of examples; Vivek Shende: Shende's mastication remark reminds me of Michael Nielsen's "exhaust, bad [Anki] cards that seem to be necessary to get to good cards": Nielsen himself has interesting remarks on how he thinks about doing math in the essay above, which is mainly about using Anki to deepen mathematical understanding: ---------------------------------------- Sometimes the ways of thinking seem too personal to be useful. Richard Feynman, in The Pleasure of Finding Things Out, explained how counting is a verbal process for him, and then ended with: Sam Derbyshire concurs: as does Mariano Suárez-Álvarez: I think this is too pessimistic, and not necessarily reflective of collaborative problem-solving. Tao again: But Terry Tao is an extremely social collaborative mathematician; his option seems somewhat foreclosed to truly ground-up independent
dynomight20h662
JonathanN, Linch, and 1 more
3
Just had this totally non-dystopian conversation: "...So for other users, I spent a few hours helping [LLM] understand why it was wrong about tariffs." "Noooo! That does not work." "Relax, it thanked me and stated it was changing its answer." "It's lying!" "No, it just confirmed that it's not lying."
Daniel Paleka1d8319
0
Slow takeoff for AI R&D, fast takeoff for everything else Why is AI progress so much more apparent in coding than everywhere else? Among people who have "AGI timelines", most do not set their timelines based on data, but rather update them based on their own day-to-day experiences and social signals. As of 2025, my guess is that individual perception of AI progress correlates with how closely someone's daily activities resemble how an AI researcher spends their time. The reason why users of coding agents feel a higher rate of automation in their bones, whereas people in most other occupations don't, is because automating engineering has been the focus of the industry for a while now. Despite the expectations for 2025 to be the year of the AI agent, it turns out the industry is small and cannot have too many priorities, hence basically the only competent agents we got in 2025 so far are coding agents. Everyone serious about winning the AI race is trying to automate one job: AI R&D. To a first approximation, there is no point yet in automating anything else, except to raise capital (human or investment), or to earn money. Until you are hitting diminishing returns on your rate of acceleration, unrelated capabilities are not a priority. This means that a lot of pressure is being applied to AI research tasks at all times; and that all delays in automation of AI R&D are, in a sense, real in a way that's not necessarily the case for tasks unrelated to AI R&D. It would be odd if there were easy gains to be made in accelerating the work of AI researchers on frontier models in addition to what is already being done across the industry. I don't know whether automating AI research is going to be smooth all the way there or not; my understanding is that slow vs fast takeoff hinges significantly on how bottlenecked we become by non-R&D factors over time. Nonetheless, the above suggests a baseline expectation: AI research automation will advance more steadily compared to auto
Tomás B.3h71
Algon
1
Suppose you're a billionaire and you want to get married. However, gold-digging people of the gender you prefer target you. They are good enough at faking attraction that you cannot tell. How should you act? One idea I had was this: pick 10000 random people and then select from there. You will at the very least likely remove most of the world-class dissemblers. Armstrong proposes a similar scheme in Siren worlds and the perils of over-optimised search.
Daniel Tan1h30
0
Thoughts on high-level theory of impact (somewhat overfit to myself)  * It's useful to model labs as rushing towards AGI, with a limited safety budget. Within that, they'll allocate resources based on a combination of (i) importance and (ii) tractability. * Therefore valuable research will either (i) demonstrate something is important / not important, or (ii) show that something is more tractable than previously thought. Both of these will affect the resource allocations of labs. * For people outside labs, one path to impact is to do 'general science' / establish 'playbooks' that makes it easy for labs to implement effective interventions that improve outcomes. 
Mo Putera22h241
0
Something about the imagery in Tim Krabbe's quote below from April 2000 on ultra-long computer database-generated forced mates has stuck with me, long years after I first came across it; something about poetically expressing what superhuman intelligence in a constrained setting might look like: And from that linked essay above, Stiller's Monsters - or perfection in chess: In 2014 Krabbe's diary entry announced an update to the forced mate length record at 549 moves: Krabbe of course includes all the move sequences in his diary entries at the links above, I haven't reproduced them here.
GradientDissenter3d*8613
Ryan Meservey, RobertM, and 6 more
13
Notes on living semi-frugally in the Bay Area. I live in the Bay Area, but my cost of living is pretty low: roughly $30k/year. I think I live an extremely comfortable life. I try to be fairly frugal, both so I don't end up dependent on jobs with high salaries and so that I can donate a lot of my income, but it doesn't feel like much of a sacrifice. Often when I tell people how little I spend, they're shocked. I think people conceive of the Bay as exorbitantly expensive, and it can be, but it doesn't have to be. Rent: I pay ~$850 a month for my room. It's a small room in a fairly large group house I live in with nine friends. It's a nice space with plenty of common areas and a big backyard. I know of a few other places like this (including in even pricier areas like Palo Alto). You just need to know where to look and to be willing to live with friends. On top of rent I pay ~$200/month (edit: I was missing one expense, it's more like $300) for things like utilities, repairs on the house, and keeping the house tidy. I pool the grocery bill with my housemates so we can optimize where we shop a little. We also often cook for each other (notably most of us, including myself, also get free meals on weekdays in the offices we work from, though I don't think my cost of living was much higher when I was cooking for myself each day not that long ago). It works out to ~$200/month. I don't buy that much stuff. I thrift most of my clothes, but I buy myself nice items when it matters (for example comfy, somewhat-expensive socks really do make my day better when I wear them). I have a bunch of miscellaneous small expenses like my Claude subscription, toothpaste, etc, but they don't add up to much. I don't have a car, a child, or a pet (but my housemate has a cat, which is almost the same thing). I try to avoid meal delivery and Ubers, though I use them in a pinch. Public transportation costs aren't nothing, but they're quite manageable. I actually have a PA who helps me with
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