Pigeon Hour

Aaron Bergman
  • 4.8 (4)
  • Social Sciences

Recorded conversations; a minimal viable pod www.aaronbergman.net

  1. Jul 9

    #17: Sarah Hastings-Woodhouse knows everything there is to know about AI

    A podcast with Sarah Hastings-Woodhouse, who is on Substack, Twitter (@littIeramblings) and potentially elsewhere Topics discussed * Current thing: Fable gets export-controlled * Sarah defends government-enforced staged deployment * Non-misalignment misuse as an existential risk, maybe * Internal deployment (other current thing smart people talk about) * Sarah goes woke thinks that rationalists should not say true but useless and unpalatable things; invisible graveyard of those who’d otherwise have gotten involved as AI safety * Why Sarah left UK AISI after 10 months * Agglomeration effects (London) vs being able to buy things (Sheffield) * Current thing: it’s very hot in the UK and Sarah is coping * Trump on AI: do we want high variance or reasons-responsiveness when they conflict? Transcript [00:01] Aaron: Hello. [00:02] Sarah: Hello. Yeah, well, my laptop no longer has a functioning built-in webcam because I marinated my laptop in Coke Zero, so. [00:09] Aaron: Nice. [00:09] Sarah: Yeah. [00:10] Aaron: I feel like maybe... All right. Whatever. I’ll try to convince you to get a $10,000 computer at some point. [00:15] Sarah: I don’t think I need that. [00:17] Aaron: Sorry. I think I’m projecting. [00:21] Sarah: If you want a $10,000 laptop, you should get one. [00:24] Aaron: Thank you. I probably won’t, but you know. I read 1.5, listened to 1.5 of your recent blog posts. [00:34] Sarah: Thank you. [00:35] Aaron: And not the one that you requested me to listen to. Although, to be fair, I did the listening before I heard from... Yeah, before you responded. [00:47] Sarah: That’s fine. I had no idea of anything specific I wanted to talk about. I just felt like yapping. [00:51] Aaron: Okay. [00:52] Sarah: Did you generate any takes from listening to 1.5 of my blogs? [01:01] Aaron: So, the full one I listened to was the Fable. And honestly, I could’ve done a lot more preparation, so we should talk about the other stuff. But the only thing was like, oh, maybe you’re very slightly sympathetic to the, oh, maybe it’s a coincidence — or sorry, not a coincidence — maybe it’s not the Trump administration just being hopelessly corrupt, and a little bit more sympathetic to that point of view than I am. But I didn’t have any burning hot takes. [01:33] Sarah: Don’t we kind of have evidence that it wasn’t a malicious, petty, anti-Anthropic move because they’re now doing a similar thing with OpenAI? This was the update heard the day after I published that, and I was like, “Oh, no, my point has already been somewhat undermined.” Well, not undermined, because I left it open as to what I thought would happen, but... [01:52] Aaron: So it remains TBD whether they will in fact be export controlled. And so one thing you can imagine, and I think kind of expect this to happen, is just a rapid approval process or a staged rollout over a month for OpenAI’s. It remains to be seen. I could be proven wrong, but staged rollout over a month. First of all, also giving warning beforehand instead of arbitrarily. Actually, let’s set that aside because, fair enough, maybe they just woke up or whatever. But yeah, basically similar from a high-level point of view, type of treatment, but in fact OpenAI’s just gets approved way faster, with fewer restrictions. And they probably didn’t go through all the effort of turning Mythos into Fable, which was — that amount of effort or time, money, et cetera, is probably bigger than what OpenAI will have ever spent, I’m expecting. Or I guess we’ll never know. But I’m guessing that it’ll be bigger than what OpenAI will have sort of spent or implicitly spent, including via the staged rollout. Also, I feel like the wording is such that the staged rollout is like — isn’t that the term that they’re using, or am I wrong? Am I misremembering? [03:14] Sarah: Yeah, something like that. [03:16] Aaron: Because that’s very much a “we’re going to let you do the thing,” just not like, “oh, no, we’re going to ban them,” and then retroactively, or then maybe we’ll have further negotiations. But these are in fact very different things — an indefinite export control versus an informal staged rollout. I don’t know. [03:35] Sarah: Yeah, I can see how they’re different. I’m just saying it appears like there is now a general principle that the government wants some lag time between the model being developed and it being publicly deployed, and maybe this is partially to harden our infrastructure to cybersecurity threats or whatever. And it now appears that that is a genuine intention that they have, as opposed to they are just mad at Anthropic. They might separately be a bit mad at Anthropic, but like— [04:02] Aaron: No, I think it’s both. And I just have a very high prior also on the Trump administration being ridiculously cynical and — is cronyism the right word? Just like if Jensen Huang asks for no export controls, it’s like, okay, no export controls. And Dario’s kind of autistic and woke. [04:26] Aaron: And more importantly, not just totally bending the knee to Trump, and trying to actually be part of civil society in a non-sycophantic way. Now I’m saying sycophantic like it’s a word that you use. [04:41] Sarah: Yeah. But, okay. [04:42] Aaron: Yeah. [04:42] Sarah: I don’t want to defend the Trump administration. That’s not my thing. [04:49] Aaron: No, do it. [04:50] Sarah: But I guess the most charitable possible interpretation of events here is that Anthropic did in fact do a much more — their comms strategy around Mythos and Fable was a lot scarier, right? And presumably policymakers don’t have, or at least not all of them have, the time to actually analyze the benchmarks and observe that Mythos Preview and GPT-5.5 were similarly capable. And so maybe they just got kind of jump scared. They scrambled. They did a clumsy, poorly executed thing. In OpenAI’s case, they have not been similarly alarmed because OpenAI doesn’t do that kind of comms, which in my opinion they probably should. And there’s a version of this story where they’re being kind of incompetent, but they are not in fact just maliciously going after Anthropic specifically— [05:39] Aaron: I mean— [05:39] Sarah: ...for personal reasons, right? [05:42] Aaron: I agree this is in principle possible. I think what actually happened is Trump and one or two top people that he talks to just told the Commerce Department. It’s not like there’s an abstract policymaking blob. There is, but separately, I think this specifically ran through Trump and maybe one other person. [06:01] Sarah: But I feel like that makes it more plausible, right? Because it’s a knee-jerky sort of impulse reaction. [06:07] Aaron: But we already know — we literally know that Trump personally dislikes Anthropic. [06:15] Sarah: Yeah. I don’t know. Honestly, I’m not— [06:19] Aaron: I think— [06:20] Sarah: ...really sure whether it really matters. The thing I’m more confused about is that there are people coming out now, like Zvi Mowshowitz, for example, being like this kind of principle of doing staged rollouts is the maximally bad policy because it widens the gap between the capabilities that the labs— [06:36] Aaron: Oh, right. Yeah. [06:36] Sarah: ...make available to the public. And I’m kind of confused by this take. I think it might be somewhat bad in the sense that now the capabilities are not as publicly auditable, and maybe if you really care about external orgs being able to do safety research with the current frontier, then this is a problem, and it’s bad that we don’t know exactly what’s happening. But it’s clearly not the maximally bad thing. The maximally bad thing is the government is just letting them YOLO and has no insight or visibility into this process at all. At least now there’s some plausible information flow. Just as a consequence of the government having to do the interaction with the labs to agree on the staged rollout, they are now getting more information. [07:12] Aaron: Yes. [07:12] Sarah: And the government getting more information seems like the only plausible path I can think of … Get full access to Aaron's Blog at www.aaronbergman.net/subscribe

    #17: Sarah Hastings-Woodhouse knows everything there is to know about AI

  2. May 24

    #16: Tommy Crow is extraordinarily based and correct about everything

    Episode main page: https://www.aaronbergman.net/p/tommy-crowA podcast with Tommy Crow, who is on Substack, Twitter (@tommyjoancrow), TikTok, and elsewhere, recorded irl after a recent EAGx conference in DC! Topics discussed - Tommy’s awake top surgery: how it happened, why almost every doctor said it was impossible - “Fighting the tube,” post-op torture, and the liability incentives that quietly make pain a tolerated feature of US surgical care - The role of amnestic drugs like midazolam - preventing memory of suffering rather than the suffering itself - and why that’s epistemically and morally suspect - Historical precedent for getting this catastrophically wrong as evidence the current consensus deserves scrutiny - Practical self-advocacy: drafting a healthcare power of attorney with anesthesia/intubation restrictions, and why the state-default POA is worse than anything you’d write - How to find heterodox doctors - Hormones as a tightly-coupled system: Aaron’s cis TRT experience, Tommy’s trans TRT experience, and tradeoffs that get glossed over - Healthcare abundance as a policy and career direction - Shenanigans by Tommy’s insurance provider - Gay male culture as Tommy’s “classically liberal” second home Transcript [00:00] Aaron: Hi, this is Aaron, and in this episode of Pigeon Hour, Tommy Crow and I talk about surgery, medicine, and more. Tommy is a super cool guy who I met in person for the first time at EAGxDC a couple weeks ago. We recorded the next day after the conference in person, and we’re finally getting this out now. One thing to note is that during the recording, I committed to running the transcript through Claude in case anything is misleading or deserving of correction. There are a few things what I consider to be pretty minor, but those are in the Substack post attached to this episode, with a bit of back and forth between Claude and then Tommy or I depending on who said the thing in question. So, without further ado, me and Tommy. [00:48] Aaron: Okay, we are now recording. [00:50] Tommy: Okay. [00:51] Aaron: Actually, so we’re recording on one device just in case. And because now I have a 48-gig Mac, I can do Otter as well. Okay. Tommy, I hope that’s okay — that was the name of the Google Calendar event. [01:13] Tommy: Tommy coming. Love that. Yeah, I had a similar incident that also made me a little paranoid about losing recordings. [01:22] Aaron: Oh wow, what happened? [01:23] Tommy: I mean, it wasn’t like a huge deal, but I similarly tried to rig up a way to record a phone call and failed to record one side of it — I only recorded my side. And it was with this kind of gray-market surgeon I was talking to. He — I almost did my surgery with him. I actually had plane tickets to Italy booked. [01:49] Aaron: Oh, dang. [01:51] Tommy: And he was actually a legitimate researcher at the University of Naples, and then we just found out that he was also doing black-market plastic surgeries out of a hotel on the side. [02:01] Aaron: That’s kind of cool. I’m — [02:03] Tommy: Yes. Like, and I totally — [02:05] Aaron: — not sure if I endorse it, but it’s kind of cool anyway. [02:08] Tommy: Well, we had a whole debate. I was thinking about doing it with him because at the time I couldn’t find anyone else in the world who was willing to try it. So I thought he might be my only hope. [02:18] Aaron: Do you want to give — wait, so for the people, do you want to give context? [02:23] Tommy: So, okay, so as far as we know, I’m the only documented case of someone getting modern female-to-male top surgery fully awake. And before I did this, most doctors would tell you that it was medically impossible. And this was just very obviously not true. Anyone who understands this particular method of local anesthesia that was used would know that it can be done this way. It’s not hard technology to understand, but it’s very underappreciated. So a lot of doctors will just sort of dismiss it out of hand. [02:59] Aaron: And yesterday — so we met at EA Global. Well, we met online, but then we were talking at EA Global in person, Washington, DC. By the way, this is an in-person Pigeon Hour, a special event. Yeah, welcome to the beautiful recording studio, which is a couch. [03:10] Tommy: Happy to be here. [03:11] Aaron: So wait, why did you even want to do the not-asleep version? [03:23] Tommy: That’s the million-dollar question, isn’t it? So I think general anesthesia opens you up to a lot more risk of pain at multiple points throughout the procedure. And I think this happens a lot more than people are typically aware of. And it actually happens oftentimes as part of the procedure. So just one example of something that commonly happens in American hospitals is this phenomenon that they call “fighting the tube” — that’s actually the phrase that doctors and anesthesiologists use. They call it fighting the tube. And that’s basically exactly what it sounds like. It’s where they wake you up after surgery in post-op while you’re still intubated, and they wait for you to basically struggle and thrash and try to scream and gurgle against the tube because you feel like you’re getting waterboarded. And they just kind of tie you down or hold you down and let that happen for a while. And they do this because there’s a complicated mix of liabilities here. Basically they will slightly, slightly, slightly reduce your chance of dying in exchange for an almost certain chance of causing you extreme suffering and anguish, because that reduces liability for them — they face much more liability for your preventable death than they do for your preventable suffering. [04:47] Aaron: Yeah, okay. So to not be coy about it — yes, we’re going to be talking about how you’re secretly being tortured in surgery and why this is bad. I’m always doing this — I’m always saying “um” and “uh” when I start recording. It’s terrible. I do it even off recording, to be fair. But anyway. So this is not just a top surgery thing. This is a general surgery thing. I’m not trying to cancel trans voices or anything, I promise. I’m trying to make it like — there’s a general problem here, right? Or a general phenomenon here. And then we’ll let the people of Pigeon Hour decide if it’s a problem. I think it’s a problem. [05:32] Tommy: Well, and I will say it in my very trans voice — this is not the issue that I encountered, it just happened to be applicable in a trans surgery for me. But this is applicable in many, many, many surgeries across the entire United States, and presumably elsewhere as well, although I’m not informed about that particularly. And there are two things that I’ll say that are very general concerns or topics that I’m interested in. Number one, there is a pain management crisis in the United States that has been going on ever since the opioid epidemic, where basically there’s a whole bunch of incentives that discourage doctors from managing pain effectively and also normalize the use of anterograde amnesia–inducing drugs as a substitute for pain relief. So that’s number one. And number two, there are just better ways to do fat-based surgeries specifically. Any surgery that’s being done with fat can be done better oftentimes than it is, because this technology called tumescent local anesthesia is very underused. [06:44] Aaron: Yeah, so wait — the amnesia thing is kind of obviously also — wait, to back up, a meta point is like, it’s a very kind of horrifying topic that I don’t especially like discussing. Do you think it’s important? [06:55] Tommy: Yeah. [06:55] Aaron: But we’ll try. I mean, we’ll try to strike a balance of being like — not withholding important information, but also not scaring people away from actually listening. I mean, I think it’s a genuinely hard problem. There’s some sort of curve where you maximize the impact, but if no one’s listening, you don’t maximize the impact. So you’ve got to hit the top of the curve. So the amnesia thing basically means that you don’t remember, and so that is effectively what’s going on — that you are being made to not form memories of being tortured, rather than just not being tortured in the first place. And you know way more about this than I do. This is like a big part of your researching this — it’s evidently a big part of your life. And the way it’s sort of been like the horrors of the background universe to me or something. But I do know as some context that there’s precedent in the sense of — we used to not use any anesthesia at all when operating on infants. [07:59] Tommy: Yes. [07:59] Aaron: And this is in Jonathan Birch’s book Edge of Sentience — sorry, we’ll cut out my pausing. And yes, that’s the proper, both philosophical and just accurate, as far as I can tell, description of what happened. And basically, it was totally standard practice to just simply cut open human babies without doing anything about — without any sort of prevention of pain or suffering. And one normie response is like, “that’s obviously bad,” and I think it probably is. But the other thing is that there’s a gigantic asymmetry. It’s like, why are you so sure? You know, if there’s only a — I mean, definitely at a 30% chance I think you can go pretty low while the moral calculus checks out as to whether you should take at least any steps, and certainly probably pretty intensive steps, to prevent suffering. Like, what are the chances that we’re wrong about infants not feeling pain, right? And I will go to bat for: knowing the subjective experience of another being is extraordinarily difficult. So like — yeah, I don’t think there’s any sort of trick going on to say that even if you think in some situations that maybe in fact there’s no suffering, like, ground truth under the surface — it’s worth considering the p

  3. Jan 25

    #15: Robi Rahman and Aaron tackle donation diversification, decision procedures under moral uncertainty, and other spicy topics

    Summary In this episode, Aaron and Robi reunite to dissect the nuances of effective charitable giving. The central debate revolves around a common intuition: should a donor diversify their contributions across multiple organizations, or go “all in” on the single best option? Robi breaks down standard economic arguments against splitting donations for individual donors, while Aaron sorta kinda defends the “normie intuition” of diversification. The conversation spirals into deep philosophical territory, exploring the “Moral Parliament” simulator by Rethink Priorities and various decision procedures for handling moral uncertainty—including the controversial “Moral Marketplace” and “Maximize Minimum” rules. They also debate the validity of Evidential Decision Theory as applied to voting and donating, discuss moral realism, and grapple with “Unique Entity Ethics” via a thought experiment involving pigeons, apples, and 3D-printed silicon brains. Topics Discussed * The Diversification Debate: Why economists and Effective Altruists generally advise against splitting donations for small donors versus the intuitive appeal of a diversified portfolio. * The Moral Parliament: Using a parliamentary metaphor to resolve internal conflicts between different moral frameworks (e.g., Utilitarianism vs. Deontology). * Decision Rules: An analysis of different voting methods for one’s internal moral parliament, including the “Moral Marketplace,” “Random Dictator,” and the “Maximize Minimum” rule. * Pascal’s Mugging & “Shrimpology”: Robi’s counter-argument to the “Maximize Minimum” rule using an absurd hypothetical deity. * Moral vs. Empirical Uncertainty: Distinguishing between not knowing which charity is effective (empirical) and not knowing which moral theory is true (moral), and how that changes donation strategies. * Voting Theory & EDT: Comparing donation logic to voting logic, specifically regarding Causal Decision Theory vs. Evidential Decision Theory (EDT). * Donation Timing: Why the ability to coordinate and see neglectedness over time makes donation markets different from simultaneous elections. * Moral Realism: A debate on whether subjective suffering translates to objective moral facts. * The Repugnant Conclusion: Briefly touching on population ethics and “Pigeon Hours.” * Unique Entity Ethics: A thought experiment regarding computational functionalism: Does a silicon chip simulation of a brain double its moral value if you make the chip twice as thick? Transcript AI generated, likely imperfect AARON Cool. So we are reporting live from Washington DC and New York. You’re New York, right? ROBI Mm-hmm. AARON Yes. Uh, I have strep throat, so I’m not actually feeling 100%, but we’re still gonna make a banger podcast episode. ROBI Um, I might also, yeah. AARON Oh, that’s very exciting. So this is— hope you’re doing okay. It was— I hope you’re— if you, if you, like, it was surprisingly easy to get, to get, uh, tested and prescribed antibiotics. So that might be a thing to consider if you have, uh, you think you might have something. Um, mm-hmm. So we, like, a while ago— should we just jump in? I mean, you know, we can cut. ROBI Stuff or whatever, but— Yeah, um, you can explain, uh, so I talked to Max, uh, like 13 months ago. AARON It’s been a little while. Yeah, yeah. Oh yeah, yeah. And so this is, um, I just had takes. So actually, this is for, for the, uh, you guys talked for the as an incentive for the 2024, uh, holiday season EA Twitter/online giving fundraiser. Um, and I listened to the— it was a good— it was a surprisingly good conversation, uh, like totally podcast-worthy. Um, I actually don’t re— wait, did I ever put that on? I’m actually not sure if I ever put that on, um, the Pigeon Hour podcast feed, but I think I will with— I think I got you guys’ permission, but obviously I’ll check again. And then if so, then I, I will. Um, and I just had takes because some of your takes are good, some of your takes are bad. And so that’s what we have to—. ROBI Oh, um, I think your takes about my takes being bad are themselves bad takes. Uh, at least the first 4 in a weird doc that I went through. Um, yeah, I saw you published it somewhere on YouTube, I think. I don’t know if it also went on Pigeon Hour, but it’s up somewhere. AARON Yes, yes. So that we will— I will link that. Uh, people can watch it. There’s a chance I’ll even just like edit these together or something. I’m not really sure. Figure that out later. Um, yeah. Yes. So it’s, yeah, definitely on you. Um, so let me pull up the— no, I, I think at least two of— so I only glanced at what you said. Um, so two of the four points I just agree with. I just like concede because at least one of them. So I just like dumped a ramble into, into some LLM. ROBI Yeah. AARON Like, These aren’t necessarily like the faithful, um, uh, things of what I believe, but like the first one was just, um, so like I have this normie intuition, and I don’t have that many normie intuitions, so like it’s, it’s like a little suspicious that like maybe there’s a, a reason that we should actually diversify donations instead of just maximizing by giving to the one. Mm-hmm. Like just like, yeah, every dollar you just like give to the best place. And that like quite popular smaller donors say people giving less than like $100,000 or quite possibly much more than that, up to like, say, a million or more than that. Um, that just works out as, as donating to like a single organization or project. ROBI Yeah. Okay. Um, I, I think we should explain, uh, what was previously said on this. So there’s some argument over— okay. So like, um, normal people donate some amount of money to charity and they just give like, I don’t know, $50 here and there to every charity that like pitches them and sounds cute or sympathetic or whatever. Um, And then EAs want to, um, first of all, they, I don’t know, strive to give at least 10% or, I don’t know, at least some amount that’s significant to them and, uh, give it to charities that are highly effective, uh, and they try to optimize the impact of those dollars that they donate. Whatever amount you donate, they want to, like, do the most good with it. Um, so the, like, standard economist take on this is, um, So every charity has, uh, or every intervention has diminishing marginal returns, right, to the— or every cause area or every charity, um, possibly every intervention, um, or like at the level of an individual intervention, maybe it’s like flat and then goes to zero if you can’t do any more. Anyway, um, so cause areas or charities have diminishing marginal returns. If you like donate so much money to them, they’re no longer, um, they’ve like done the most high priority thing they can do with that money. And then they move on to other lower priority things. Um, so generally the more money a charity gets, the less, um, the less effective it is per dollar. This is all else equal, so this is not like— like, actually, if you know you’re going to get billions of dollars, you can like do some planning and then like use economies of scale. Uh, so it’s like not strictly decreasing in that way with like higher-order effects, but for like Time held constant, if you’re just like donating dollars now, there’s diminishing marginal returns. Okay, so, uh, it is— the economist’s take is like, it is almost always the case that the level of an individual donor who donates something like, let’s say, 10% of $100K, like, the, the world’s best charity is not going to become like no longer the world’s best charity after you donate $10,000. And most people donate like much less than that. So the, uh, like standard advice here is, um, if you are an individual donor, not a like, um, institutional donor or grantmaker or someone directing a ton of funds, um, you should just like take your best guess at the best charity and then donate to that. And then there are ways to optimize this for like bigger amounts. So you’ve probably heard of donor lotteries, which is like 100 or 1,000 people who want to save time all pool their money and then, then someone is picked at random and then they do research and maybe they split those donations 3 ways. Or like it all goes to something, or like— [Speaker:HOWIE] Yeah. AARON [Speaker:Kevin] Hmm. ROBI $10,000 times, uh, 100 or 1,000 is like a million or $10 million. At that level, it’s plausible that you should donate to multiple things. Um, so in that case, maybe it makes sense. AARON Um, so I don’t, I don’t— oh, sorry, go ahead. ROBI Uh, so that’s the standard argument. Um, and, um, I, I’m happy to, um, explain why this still holds, uh, to anyone who is like engaged at least this far. Um, most people haven’t even heard of it and they’re like, um, well, but what if I’m not sure about which of these two things, then I should like donate 50/50 to them. AARON Um, uh. ROBI I’ll let you go on, but I just want to say this is a really lucky time to record this podcast because Yesterday someone replied to me on the EA forum linking to some, um, uh, have you heard of, uh, Rethink Priorities, um, Moral of Parliament simulator? AARON [Speaker:Howie] Yes. ROBI [Speaker:Keiran] Okay, so it has some, um, pretty wacky and out-there decision rules, and, um, so I was— I was arguing with someone on the EA forum about this, like, um, saying Uh, it doesn’t make sense to, um, to, to split your donations, uh, at the level of an individual donor, um, even moral uncertain— and they said, but what about moral uncertainty? What if I’m not sure, like, if animals even matter? Um, uh, and I said, well, even then you should take your, like, probability estimate that animals matter and then get your, like, EV of a dollar to each and then give all of your dollars to whichever is better. Um, and they

    #15: Robi Rahman and Aaron tackle donation diversification, decision procedures under moral uncertainty, and other spicy topics

  4. Jan 25

    Vegan Hot Ones | EA Twitter Fundraiser 2024

    A great discussion between my two friends Max Alexander of Scouting Ahead and Robi Rahman (in response to a fundraiser that we wrapped up more than 13 months ago)Tweet with context: https://x.com/AaronBergman18/status/1999918243205779864?s=20 Transcript (AI-generated, likely imperfect) MAX Hello to the internet, maybe. ROBI Hey internet. MAX Um, I’m Max. ROBI I’m Robi. MAX Um, thank you all for donating, especially you. Um, so we’re gonna do a vegan version of Hot Ones. I actually don’t know if the camera can properly see. I mean, we took a photo as well, so someone will see it eventually. Um, but I have some very not spicy questions for you, and I hope. ROBI They get spicy, right? MAX Do you think it’s a little spicy? ROBI Um, I don’t know. Anyway. MAX Yeah, they’re not, you know, I’m sure someone will judge me greatly for this online. ROBI Um, yeah, the, uh, the food is spicy at least, or it gets a bit spicy. So, um, we’ve got, um, uh, we’ve got field roast, uh, buffalo wings without the buffalo sauce. We’ve got some spices on them. We’ve got, uh, Jack and Annie jackfruit nuggets and Impossible fake chicken nuggets, uh, with— my god, Sriracha, um, spicy chili. MAX Crisp. ROBI Calabrian hot chili powder, habanero hot salsa, Scotch bonnet puree, Elijah’s Extreme Regret Screamin’ Hot, um, Scorpion Reaper hot sauce. MAX Cool. ROBI And, um, some, uh, Dave’s Hot Chicken. MAX Reaper seasoning and Carolina I’m going to have a much worse time than you are. ROBI I’m looking forward to this. MAX Yeah, uh, I guess I think in tradition of hot ones, um, the guest, um, introduces themselves and like says a background. So I don’t know if you want. ROBI To— okay, yeah, um, let’s see, um, I’ve been involved in EA for— well, I think the first meetup I went to was 2017. Um, they, uh, EA was much smaller then and, uh, we didn’t have our own meetups. They were, um, the DCEA meetup group was, uh, combined with a vegan feminist environmentalist— [Speaker:MAX] That’s cool. [Speaker:ROBI] —something meetup. [Speaker:MAX] Yeah, nice. [Speaker:ROBI] Eventually we, we had enough EAs that we, you know, spun off our own, uh, effective altruism only thing. [Speaker:MAX] Cool. [Speaker:ROBI] Yeah, um, yeah, but, uh, that was fun. Um, that was also the first year I played giving games. Um, And then, uh, I was, I was kind of a global health person back then, but, um, um, Matt Ginsel was way ahead of his time, and he, um, like in the Giving Games, you get to— you like play all the games like poker or like whatever, whatever, and you win the chips, and then at the end you put the chips in, into the box for whatever charity you think should get the money. And, um, He surprised me by donating to pandemic prevention, which wasn’t even on my radar then. And then, like, 3 years later, he was totally right. MAX Yeah, unfortunately. ROBI Yeah. Uh, yeah. MAX And now you work at Epoch. ROBI I work at Epoch. Yeah. Um, I do AI forecasting, basically. My job is kind of to figure out when everyone else’s job will be automated. Delightful. MAX You know? Yeah. Cool. Um, yeah, I guess maybe our very lukewarm, uh, question is, uh, which do you think is better, fuel or soil land? ROBI Um, I think I prefer Soylent for the drinks. MAX [Speaker:Robi] Interesting. ROBI [Speaker:Max] But, um, Hewlett Hot Savory was great. They’ve recently rebranded, right? [Speaker:ROBI] I don’t know. [Speaker:MAX] Hot Savory to, um, Instant Meals or like, something like that? I haven’t bought it in a while. MAX [Speaker:Robi] I, yeah, I bought some for the fundraiser. ROBI [Speaker:Max] Should we eat some lukewarm nuggets to go with the lukewarm questions? MAX [Speaker:Robi] Yeah, yeah, exactly. ROBI [Speaker:Max] So let’s start off with the Chili Crisp, um, uh, buffalo wing. [Speaker:ROBI] Okay. [Speaker:MAX] Cheers. MAX Yeah, that’s not that spicy. ROBI [Speaker:Robi] Eat the whole thing. MAX [Speaker:Max] Oh no. ROBI I’m sorry. It’s so far. Chicken nugget. [Speaker:ROBI] Yeah, um, yeah, I don’t think I would— I don’t know if I would notice that’s not chicken. MAX [Speaker:Max] Oh yeah. For sure. ROBI I mean, I’m not a huge fan of chicken nuggets anyway, but yeah. Um. MAX Cool. Okay, um, let’s see. ROBI Uh. MAX Okay, well, this one’s a little spicy at least. Uh, what’s one thing you think everyone in EA is getting wrong? ROBI Um, I’m kind of like very EA orthodox, and I think EA is like basically right about everything. Um, the The thing I think EAs get wrong— I think the, um, I don’t believe in the, like, perils of maximizing stuff, or like— like, maximizing does have the problems that they point out, but like, I don’t think anyone has a good argument that, like, you should not maximize. MAX Sure. ROBI I think all of the, like— I don’t know, I just bite the bullet. I’m taking everything to the— like, if the principles are right and you have the facts, yeah, the conclusion is what it is. MAX Okay, well, that’s good. I think I have a question later that’s like Is the repugnant conclusion actually repugnant? ROBI I’ll have some thoughts on that. Yeah, I think I basically disagree with Holden Karnofsky and Scott Alexander on, like, you should get off the crazy train if it seems too weird. Like, no, if the reasoning checks out, you should do what you should do. MAX Cool. ROBI Yeah, I kind of think— this might be a bit spicy— Okay. I kind of think, um, they are— I slightly suspect they’re just saying that as cover, like after the FTX scandal and whatnot. Like, no, no, no, no, we don’t really believe in that stuff where you like take it to the extreme and like, yeah, yeah, yeah. MAX That is plausible. I don’t know Holden, so I cannot say for sure. ROBI Neither do I, but I’d like to think he’s smarter than to— sure. MAX Yeah, yeah. Um, cool. Yeah, though Yeah, I mean EA is a whole big thing, so, you know, um, cool, that’s a good one. That’s a— if you brought that to a party, you know, you would start a 3-hour discussion, sort of. ROBI No, I think that would be like, um, a 30th percentile EA spicy opinion. MAX Well, yeah, but then the other people, you like start the whole thing and they, uh, yeah, cool. ROBI Um, cool. MAX Oh wait, should we eat another thing first? ROBI Yeah, how many questions are there? MAX 16? I have 16, but some of them are like not— Yeah, 2, 3 questions. Okay, cool. ROBI Um, yeah, uh, so you spoke at UHG once, right? I— not— I wasn’t quite a speaker. I was a, um, I ran a session. Yeah, it was, but it was, um, it was like a forecasting interactive exercise. So it was a, like, short presentation, and then we did a workshop. MAX Cool. ROBI Yeah, I think the EAG team has been trying to move away from static content and lectures, because EA has this meme of, like, you don’t go for the content, you go for the one-on-ones. Or a lot of people say, like, well, why should I watch a talk when my time is scarce and I could just watch it on YouTube anyway at 2x speed, thereby saving all this time? I don’t think people would— I don’t think the counterfactual is actually watching. I think it’s just never seeing the talk. Exactly. MAX Yeah. ROBI But, but, um, And there have been some really good talks at the AGs. Kevin Esvelt at EAJxBoston was incredible. Yeah, very, very good biosecurity presentation. But yeah, so I offered to— or like was, you know, talking to the content team about like they might have wanted a presentation, but they didn’t want it to just be a lecture. I could just give an Epoch spiel, but I think it was more fun with, you know, people who are in current views. MAX [Speaker:Max] Cool. Yeah, I guess if you were to do it now, has anything changed or. ROBI Is it mostly the— [Speaker:ROBI] Well, I would fix— one of my forecasting questions had a loophole. I think we were— so Matthew Barnett is another AI forecasting guy. He has just left Epoch to form a startup. Spicier than anything I’m doing. I can talk about that later. MAX [Speaker:Max] Yes, that’s a good question actually. ROBI Well, I’ll finish. Um, Matthew and I, you know, uh, had some questions. We adapted them for the UAG format. Um, I think I made some last-minute changes and then overlooked a loophole, which was— so the, um, I don’t remember what it was exactly, but it, it was something like one of the questions ended up being like— so there were 3 big questions of like different domains. Um, one was like superhuman in math, one was like, um, do all like households tasks by inventing robotics, and one was, um, um, synthetic biology capabilities. And one, uh, the last question was something like, um, when will it be possible to, with the aid of AI, invent a virus at least— like, synthesize a virus at least as dangerous as COVID or something. But I think I edited it last minute and then left some loophole where someone raised their hand and was like, “Well, you can already acquire a sample of a virus at least as dangerous as COVID by getting a sample of COVID.” Simply just have someone sneeze and then deliver it. So AI can already do that. But that’s not the point of the question. No, it was something like, “When will a rogue terror— when will it be possible for a rogue terrorist group with the aid of AI to get a sample of a virus at least as dangerous as COVID?” And they can already get COVID. Yeah, yeah, yeah, yeah. MAX Uh, yeah, cool. ROBI Uh, that wasn’t the exact question, but something like that. Yeah, nice. MAX Um, cool, that’s very fun. Yeah. ROBI Um. MAX Let’S see, uh, I guess, yeah, so if you kind of weren’t in EA now, is there like a career you would— do you have like a dream career that you’re like, ah, it’s just not impactful enough? ROBI So, um, that is a great question. I really like data science. Um, this is a little suspicious. Um, like Maybe I would do the same thing anyway. But yea

  5. 10/06/2025

    Post readout: Utilitarians Should Accept that Some Suffering Cannot be “Offset”

    This is an audio readout of my recent post Utilitarians Should Accept that Some Suffering Cannot be “Offset”, also on the EA Forum Enjoy! Get full access to Aaron's Blog at www.aaronbergman.net/subscribe

    Post readout: Utilitarians Should Accept that Some Suffering Cannot be “Offset”

  6. 05/14/2025

    #14: Jesse Smith on HVAC, indoor air quality, and generally being an extremely based person

    Summary Join host Aaron with Jesse Smith, a self-described "unconventional EA" (Effective Altruist) who bridges blue-collar expertise with intellectual insight. Jesse recounts his wild early adventures in Canadian "bush camps," from planting a thousand trees daily as a teen to remote carpentry with helicopter commutes. Now a carpenter, HVAC technician, and business owner (Tay River Builders), he discusses his Asterisk magazine article, "Lies, Damned Lies, and Manometer Readings." Discover the HVAC industry's surprising shortcomings, the difficulty of achieving good indoor air quality (even for the affluent!), and the systemic issues impacting public health and climate goals, with practical insights on CO2 and radon monitors like the Airthings View Plus. Jesse’s links * Lies, Damned Lies, and Manometer Readings, the Asterisk magazine article discussed at length * Tay River Builders, his contracting company * Willard Brothers Woodcutters, his wood store (and its viral Instagram page) * Jesse on Twitter * The Airthings View Plus air quality monitor discussed (currently $239 on Amazon) (no they’re not paying either of us for this but they should Transcript Aaron: Okay. First recorded pigeon hour in a while. I'm here with Jesse Smith resident dad of EA Twitter. I don't know if. I don't know if you'll accept that. Accept that honor. Okay, cool. and I actually, we haven't chatted, face to face in, like, a while, but I know you have, like, a really interesting. You're very, like, unconventional EA in some respects. Do you want to, like, give me your whole like, life story? In brief? Jesse: okay. So I guess one thing is that I'm super old for EA, right? like. And so being a dad and owning, like, a kind of normal business, I guess another is kind of more blue collar background, right? So, I was originally a carpenter also, then took on being an HVAC technician. So I, the businesses that I own Kind of like focus on a little bit of both those. yeah. So like my my background. I was raised in Canada. I left school, I didn't go to college. yeah. I went into, like, after a few years of, like a few years after high school, went into the trades basically. Aaron: Okay. Yeah. Nice. Okay. Like. Yes, I think that. Yeah, that definitely, like, makes you at least, at least stereotypically. But I think also like, in real life, like, there just aren't that many, like, carpentry businessmen who are, like happen to, like, hang out on Twitter also. So no, this is like legitimately really interesting. And at one point, I swear, I thought you went to Princeton. You must have mentioned the city, and I must have interpreted it as the town. Jesse: Yeah, my my brother, my brothers and I lived in Princeton for quite a while. Two of my brothers actually. Aaron: Still. Jesse: Okay around Princeton. I'm not far from Princeton. That's kind of the area where we work. it is where my dad went to grad school, so could have been that as well. so. Yeah. Yeah, but I did not attend Princeton. Aaron: I mean. Jesse: I worked on some of their buildings, but I have not attended. Aaron: Maybe, maybe that was where I got the that like. Yeah, like like myth from. So I know I have, I got like a couple at least. Matt. Matt from Twitter sent in a question, but I as usual, I've done a minimal level of preparation. So also we can we can talk about talk about truly whatever, but like, maybe. Yeah. So how did you, how did you, like, find out about Yale's? Like one thing. Jesse: Well, yeah. Okay. So there's some, I guess, some weird stuff. So I was fairly enamored with Peter Singer. Kind of just like starting with the book Animal Liberation. It would have been. I forget when he wrote that. Like it would have been years after he wrote it, right? Because I think he wrote it in even when, like when I was super young. But I probably read that in my late teens. Okay. And so, yeah. Aaron: That's that's the 1975 book. Jesse: So yeah, that sounds right. Yeah. I was going to guess the 70s. Right. So I was like. Aaron: Nice. Jesse: Nice or something. Right. So what. Aaron: Year old? Jesse: Yes, exactly. But so so when I was 16, I briefly dropped out of high school and I was working. This is really weird. I was working in these, like, bush camps in Canada. It's somewhat popular to do this. And so, like, I was 16, I celebrated my 17th birthday in a bush camp. That was like a tree planting bush camp. But this. Okay, so this is really weird. It sounds like this is like core blue collar, but it's not quite. The guy who owned the company I was working for was a friend of my dad's, and he was Baha'i and vegetarian. And so he had these vegetarian bush camps that we planted trees and did like some brushing out of. Right. So we ran like brush saws and stuff. And so I sort of I think that's kind of what, like I became a vegetarian out of those camps and was reading kind of Peter Singer's stuff at the time. And I think partly being there made me realize like, oh, this is going to not be that difficult. A lot of guys were really irritated by vegetarian bush camps, right? Like some of it was kind of core blue collar, mediating type guys. But like, I was totally fine. I was actually like super happy because it was kind of my first experience in a full time job. And I was nervous because everybody was like, oh, you know, it's going to be hell. And I actually thought it was great. It was much better than being in high school. I thought at the time, like, they just like everything was squared away, like they just fed you. You just had to go and like, try to put as it was piecework. So it was like $0.22 a tree or something. And after a few days, I think on my third day I put something like a thousand trees into the ground or something. Right. So I was. Aaron: Like, Jesus Christ. Jesse: I was like, oh, this is amazing, right? Like, all I have to do is like. Run as fast as I possibly can with these big bags of trees in the woods in, like, this beautiful setting. Eat the food they give me and then like, go to sleep and, like, read or whatever. Right. So like it was a it was a great experience. I know that's the total effect, right. What's that. Aaron: No no no it's not it's not a digression. One thing is can you just define bush camp like for for us dumb American like, oh yeah, dumb like Americans or whatever. Jesse: Yeah. So I, I don't know, I, I guess maybe I haven't heard the terms. They're in the US, but they must exist for some purpose. Right. So usually it's like somewhere remote that you are basically camped out of. In my case, it was literally like camping. It was tents, which I didn't mind at the time. So you'd be like, you know, in our case, it was big camps. Like, I think sometimes they can be as little as maybe ten people, let's say. Right. And this was like a pretty decent company. So they were running 40. The max I saw was maybe 100 people working out of this camp in the remote wilderness. The first year I did it was around an area called mica, which I understand now is a popular heli skiing destination. Like I have a friend who now skis and mica, which is hilarious to me, but it would maybe take you to the nearest town to mica was probably Revelstoke, which was in this case we could drive there, you know, maybe like a year or two later. There were ones that we were flown into, and in some cases there were even ones where I'm trying to think like I was in one in my like early 20s where they would helicopter. You would take a helicopter ride every day to the site, like so like you. So they would like, you'd see this helicopter coming in and like, they'd land in the camp and then they take you. But it was just it wasn't like it didn't feel like special operations. It was like the helicopter was rented from the, like, small towns Weather channel. Right. Aaron: Well, that's so badass as like, I feel like the correct term for all this is, is very based. Jesse: Yeah, I don't know. I mean, I like it seems weird now to describe this to people and it's not in people's experience. But it wasn't it didn't feel the helicopter thing. Maybe did initially felt weird. Right. Because like, I don't know anything about helicopters, right. Like but it didn't feel that weird at the time. And I knew a lot of people growing up who worked out of bush camps and then years later. So like probably around when I was in my early 20s is when I started my carpentry apprenticeship formally, like I had worked in construction a bit and then done the bush camp thing on and off. And so then I ended up doing some some remote wilderness bush camp carpentry work as well, maybe midway through my apprenticeship. So I worked on a it. An Indian reserve building, a water treatment facility that would have been like probably late 90s. Like I'm thinking like probably right before I moved to the US. And that was like that was months and months. That was actually not a good camp. One of the things I hate is that the first camp I went to was incredible, like incredible, like incredible food, like they would haul in saunas like you had you had a trailer with a sauna. And so, like when you're 16, you know, you're just like, oh yeah, this is like normal, right? And I've often thought like. And the food was amazing. Like the, the lead cook would make like she made it for my 17th birthday. She made me a cake. Right. But I was like, and I'm I'm sure I said like, thank you. But it should have been like effusive with praise, right? Because it was just like, yeah, incredible. And then if you, you know. And then I was probably in like over the years maybe 2 or 3 other camps and they suck. Like I remember showing up and being like hey, when is. And like, so this woman would, she would have like Indian night and Mexican night, like themed food nights and like you like they had generators and you could watch movies and like, it was just crazy. And I remember rolling into, like, this next, logging camps and logging camps are legendarily crappy

  7. 03/25/2025

    Preparing for the Intelligence Explosion (paper readout and commentary)

    Preparing for the Intelligence Explosion is a recent paper by Fin Moorhouse and Will MacAskill. * 00:00 - 1:58:04 is me reading the paper. * 1:58:05 - 2:26:06 is a string of random thoughts I have related to it I am well-aware that I am not the world's most eloquent speaker lol. This is also a bit of an experiment in getting myself to read something by reading it out loud. Maybe I’ll do another episode like this (feel free to request papers/other things to read out, ideally a bit shorter than this one lol) Below are my unfiltered, unedited, quarter-baked thoughts. My unfiltered, unedited, quarter-baked thoughts Okay, this is Aaron. I'm in post-prod, as we say in the industry, and I will just spitball some random thoughts, and then I'm not even with my computer right now, so I don't even have the text in front of me. I feel like my main takeaway is that the vibes debate is between normal to AI is as important as the internet, maybe. That's on the low end, to AI is a big deal. But if you actually do the not math, all approximately all of the variation is actually just between insane and insane to the power of insane. And I don't fully know what to do with that. I guess, to put a bit more of a point on it, I'm not just talking about point estimates. It seems that even if you make quite conservative assumptions, it's quite overdetermined that there will be something explosive technological progress unless something really changes. And that is just, yeah, that is just a big deal. It's not one that I think of fully incorporated into my emotional worldview. I mean, I have it, I think, in part, but not, not to the degree that I think my, my intellect has. So another thing is that one of the headline results, something that Will MacAskill, I think, wants to emphasize and did emphasize in the paper, is the century in a decade meme. But if you actually read the paper, that is kind of a lower bound, unless something crazy happens. And I'll, this is me editorializing right now. So, I think something crazy could happen first, for example, nuclear war with China, that would destroy data centers and mean that, you know, AI progress is significantly set back, or it's an unknown unknown. But the century in a decade is really a truly a lower bound. You need to be super pessimistic with all the in-model uncertainty. Obviously there's out of model uncertainty, but the actual point estimates, whether you take geometric, however you do it, arithmetic means over distributions, or geometric means, however you combine the variables, you actually get much much faster than that. So that is a 10x speed up, and that is, yeah, as I said 10 times, as pessimistic as you can get, I don't actually have a good enough memory to remember exactly what the point estimate numbers are. I should go back and look. So chatting with Claude, it seems that there's actually a lot of different specific numbers and things. So one question you might have is, okay, over the fastest growing decade in terms of technological progress or economic growth in the next 10 decades, what will the peak average growth rate be? But there's a lot of different ways you can play with that to change it. It's, oh, what's the average going to be over the next decade? What about this coming decade? What about before 2030? Do we're talking about economic progress, progress or some less well-defined sense of technological and social progress. But basically it seems the conservative scenario is, is that the intelligence explosion happens and at some, in some importantly long series of years, you get a 5x year over year. So not a doubling every year, but after two years, you get a 25x expansion of, of AI labor. And then 125 after three years. And I need to look back. I think one thing they don't talk about specifically is, oh yeah, sorry. They do talk about one important thing to emphasize. And as you can tell, I'm not the most eloquent person in the world. Is that they talk about pace significantly and about limiting factors. But the third, the thing you might solve for, if you know those two variables is the length of time that such an explosion might take place across and just talking, thinking out loud, that is something that they, whether intentionally or otherwise, or me being dumb and missing it. I don't think that they give a ton of attention to, and that's yeah. I mean, my intuition is approximately fine. Does it matter if the intelligence explosion conditional on conditional on knowing how to distribution of rates of say blocks of years, say, so we're not talking about seconds, we're not talking about, I guess we could be talking about months, but we're not talking about weeks, and we're not talking about multiple decades. So we're talking about something in the realm of single digit to double digit numbers of years, maybe a fraction of a year. So two ish, three orders of magnitude of range. And so the question is, conditional on having a distribution of peak average growth rate for some block of time. Does it matter whether we're talking about two years, or 10 years or what? And sorry, backtracking, also conditional on having a distribution for the limiting factors. So at what point do you stop scaling? Because we know that there's the talking point, infinite growth in a finite world is true. They're just off by 1000 orders of magnitude, or maybe 100. So there actually are genuine limiting factors. And they discussed this, at what point you might get true limits on power consumption or whatever. But yeah, just to recap this little mini ramble. We don't, one thing the paper doesn't go over much is the length of time specifically, except insofar as that is implied by distributions you have for peak growth rates and limiting factors. So another thing that wasn't in the paper, but that was, I'm just spitballing that was in Will MacAskill recent interview on the 80,000 hours podcast with Robert Roeblin about the world's most pressing problems and how you can use your career to solve them. Is that, yeah, I think Rob said this, he wishes that the AIX community hadn't been so tame or timid, in terms of hedging, saying, emphasizing uncertainty, saying, you know, there's a million ways it can be wrong, which is of course true. But I think his, the takeaway he was trying to get at was, even ex-ante, they should have been a little bit more straightforward. And I actually kind of think there's a reasonable critique of this paper, which is that the century in a decade meme is not a good approximation of the actual expectations, you know, the expectations is something like 100 to 1000x, not a 10x speed up. As lucky as a reasonable conservative baseline, you have to be really within model pessimistic to get to the 10x point. Another big thing to comment on is just the grand challenges. And so I've been saying for a while that my P doom, as they say, is something in the 50% range. Maybe now it's 60% or something after reading this paper up from 35% right after the bottom executive order. And what I mean by that, I actually think is some sort of loose sense of, no, we actually don't solve all these challenges. Well, so it's not one thing MacAskill and Morehouse emphasize, but in both the podcast that I listened to and the paper is it's not just about AI control. It's not just about the alignment problem. You really have to get a lot of things right. I think this relates to other work that MacAskill is on that I'm not super well acquainted with. But there's the question of how much do you have to get right in order for the future to go well. And actually think there's a lot of strands there. Like I remember on the podcast with Rob, that we're talking in terms of percentage, percentage value of the best outcome. I'm not, yeah, I'm just thinking out loud here, but I'm not actually sure that's the right metric to go with. It's a little bit like, so you can imagine just we have the current set of possibilities and then exogenously we get one future strand in the multiverse, the Everettian multiverse. And a single Everettian multiverse thread points to the future going a billion times better than it could otherwise. I feel like this approximately should not change approximately anything because you know it's not going to happen. But it does revise down those numbers, your estimate of the expected value, the expected percentage of the best future, it revises that down a billion fold. And so this sort of, no I'm not actually sure if this ends up cashing, I'm just not smart enough to intuit well whether this ends up cashing out in terms of what you should do. But I suspect that it might, that's really just an intuition, so yeah I'm not sure. You know something that will never be said about me is that I am an extremely well organized and straightforward thinker. So it might be worth noting these audio messages are just random things that come to mind as I'm walking around basically a park. Also that's why the audio quality might be worse. Oh yeah getting back to what I was originally thinking about with the grand challenges and my P. Doom. They just enumerate a bunch of things that in my opinion really do have to go right in order for some notion of the future to be good. And so there's just a concatenation, I forget what the term is, but a concatenation issue of even if you're relatively optimistic and I kind of don't know if you should be on any one issue. Like okay, so some of these, let me just list them off. AI takeover, highly destructive technologies, power concentrating mechanisms, value lock-in mechanisms, AI agents and digital minds, space governance, new competitive pressures, epistemic disruption, abundance, so capturing the upside and unknown unknowns. No, they're not, it's not as clean a model as each of these are fully independent. It's much more complex than that, but it's not as simple as you just, oh, if you have a 70% chance on each, you can just take that to the power of eight

  8. 04/11/2024

    #12: Arthur Wright and I discuss whether the Givewell suite of charities are really the best way of helping humans alive today, the value of reading old books, rock climbing, and more

    Please follow Arthur on Twitter and check out his blog! Thank you for just summarizing my point in like 1% of the words -Aaron, to Arthur, circa 34:45 Summary (Written by Claude Opus aka Clong) * Aaron and Arthur introduce themselves and discuss their motivations for starting the podcast. Arthur jokingly suggests they should "solve gender discourse". * They discuss the benefits and drawbacks of having a public online persona and sharing opinions on Twitter. Arthur explains how his views on engaging online have evolved over time. * Aaron reflects on whether it's good judgment to sometimes tweet things that end up being controversial. They discuss navigating professional considerations when expressing views online. * Arthur questions Aaron's views on cause prioritization in effective altruism (EA). Aaron believes AI is one of the most important causes, while Arthur is more uncertain and pluralistic in his moral philosophy. * They debate whether standard EA global poverty interventions are likely to be the most effective ways to help people from a near-termist perspective. Aaron is skeptical, while Arthur defends GiveWell's recommendations. * Aaron makes the case that even from a near-termist view focused only on currently living humans, preparing for the impacts of AI could be highly impactful, for instance by advocating for a global UBI. Arthur pushes back, arguing that AI is more likely to increase worker productivity than displace labor. * Arthur expresses skepticism of long-termism in EA, though not due to philosophical disagreement with the basic premises. Aaron suggests this is a well-trodden debate not worth rehashing. * They discuss whether old philosophical texts have value or if progress means newer works are strictly better. Arthur mounts a spirited defense of engaging with the history of ideas and reading primary sources to truly grasp nuanced concepts. Aaron contends that intellectual history is valuable but reading primary texts is an inefficient way to learn for all but specialists. * Arthur and Aaron discover a shared passion for rock climbing, swapping stories of how they got into the sport as teenagers. While Aaron focused on indoor gym climbing and competitions, Arthur was drawn to adventurous outdoor trad climbing. They reflect on the mental challenge of rationally managing fear while climbing. * Discussing the role of innate talent vs training, Aaron shares how climbing made him viscerally realize the limits of hard work in overcoming genetic constraints. He and Arthur commiserate about the toxic incentives for competitive climbers to be extremely lean, while acknowledging the objective physics behind it. * They bond over falling out of climbing as priorities shifted in college and lament the difficulty of getting back into it after long breaks. Arthur encourages Aaron to let go of comparisons to his past performance and enjoy the rapid progress of starting over. Transcript Very imperfect - apologies for the errors. AARON Hello, pigeon hour listeners. This is Aaron, as it always is with Arthur Wright of Washington, the broader Washington, DC metro area. Oh, also, we're recording in person, which is very exciting for the second time. I really hope I didn't screw up anything with the audio. Also, we're both being really awkward at the start for some reason, because I haven't gotten into conversation mode yet. So, Arthur, what do you want? Is there anything you want? ARTHUR Yeah. So Aaron and I have been circling around the idea of recording a podcast for a long time. So there have been periods of time in the past where I've sat down and been like, oh, what would I talk to Aaron about on a podcast? Those now elude me because that was so long ago, and we spontaneously decided to record today. But, yeah, for the. Maybe a small number of people listening to this who I do not personally already know. I am Arthur and currently am doing a master's degree in economics, though I still know nothing about economics, despite being two months from completion, at least how I feel. And I also do, like, housing policy research, but I think have, I don't know, random, eclectic interests in various EA related topics. And, yeah, I don't. I feel like my soft goal for this podcast was to, like, somehow get Aaron cancelled. AARON I'm in the process. ARTHUR We should solve gender discourse. AARON Oh, yeah. Is it worth, like, discussing? No, honestly, it's just very online. It's, like, not like there's, like, better, more interesting things. ARTHUR I agree. There are more. I was sort of joking. There are more interesting things. Although I do think, like, the general topic that you talked to max a little bit about a while ago, if I remember correctly, of, like, kind of. I don't know to what degree. Like, one's online Persona or, like, being sort of active in public, sharing your opinions is, like, you know, positive or negative for your general. AARON Yeah. What do you think? ARTHUR Yeah, I don't really. AARON Well, your. Your name is on Twitter, and you're like. ARTHUR Yeah. You're. AARON You're not, like, an alt. ARTHUR Yeah, yeah, yeah. Well, I. So, like, I first got on Twitter as an alt account in, like, 2020. I feel like it was during my, like, second to last semester of college. Like, the vaccine didn't exist yet. Things were still very, like, hunkered down in terms of COVID And I feel like I was just, like, out of that isolation. I was like, oh, I'll see what people are talking about on the Internet. And I think a lot of the, like, sort of more kind of topical political culture war, whatever kind of stuff, like, always came back to Twitter, so I was like, okay, I should see what's going on on this Twitter platform. That seems to be where all of the chattering classes are hanging out. And then it just, like, made my life so much worse. AARON Wait, why? ARTHUR Well, I think part of it was that I just, like, I made this anonymous account because I was like, oh, I don't want to, like, I don't want to, like, have any reservations about, like, you know, who I follow or what I say. I just want to, like, see what's going on and not worry about any kind of, like, personal, like, ramifications. And I think that ended up being a terrible decision because then I just, like, let myself get dragged into, like, the most ultimately, like, banal and unimportant, like, sort of, like, culture war shit as just, like, an observer, like, a frustrated observer. And it was just a huge waste of time. I didn't follow anyone interesting or, like, have any interesting conversations. And then I, like, deleted my Twitter. And then it was in my second semester of my current grad program. We had Caleb Watney from the Institute for Progress come to speak to our fellowship because he was an alumni of the same fellowship. And I was a huge fan of the whole progress studies orientation. And I liked what their think tank was doing as, I don't know, a very different approach to being a policy think tank, I think, than a lot of places. And one of the things that he said for, like, people who are thinking about careers in, like, policy and I think sort of applies to, like, more ea sort of stuff as well, was like, that. Developing a platform on Twitter was, like, opened a lot of doors for him in terms of, like, getting to know people in the policy world. Like, they had already seen his stuff on Twitter, and I got a little bit, like, more open to the idea that there could be something constructive that could come from, like, engaging with one's opinions online. So I was like, okay, f**k it. I'll start a Twitter, and this time, like, I won't be a coward. I won't get dragged into all the worst topics. I'll just, like, put my real name on there and, like, say things that I think. And I don't actually do a lot of that, to be honest. AARON I've, like, thought about gotta ramp it. ARTHUR Off doing more of that. But, like, you know, I think when it's not eating too much time into my life in terms of, like, actual deadlines and obligations… Get full access to Aaron's Blog at www.aaronbergman.net/subscribe

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Ratings & Reviews

4.8
out of 5
4 Ratings

About

Recorded conversations; a minimal viable pod www.aaronbergman.net

Information

  • Creator
    Aaron Bergman
  • Years Active
    2023 - 2026
  • Episodes
    21
  • Rating
    Explicit
  • Copyright
    © Aaron Bergman
  • Show Website
    Pigeon Hour