Tech Acceleration vs Deceleration: ea vs. e/acc debate | Erik Torenberg & Haseeb Qureshi

If you look at the companies that are actually accelerating,

they're mostly EAs, right? Which like kind of fucks up the narrative, which is like, oh, the EAs are ruining everything, they're slowing everyone down, and like it's the accelerationists who want to go fast. The accelerationists are mostly VCs. They were mostly not building anything. They're just like on the sidelines, cheerleading for this imaginary team that they think is in the driver's seat when it's reality. It's fucking EA people who are even thinking that this was possible in the first place, right? It was the it was the it was all the VCs who were not investing in any of this stuff because they thought it was so impractical and it was worth it. It's the EAs who believed that AI risk was a real thing because AI was going to become really powerful really quickly, who created all this shit.

Yeah.

Welcome to Bankless, where today we're exploring the frontier of the tech acceleration versus deceleration debate. This is Ryan Shawn Adams. I'm here with David Hoffman, and we're here to help you become more bankless. The question on today's episode, and I think a question that is everywhere right now, should we accelerate or decelerate our tech progress? And how about when it comes to something as powerful as AI? This isn't just a debate in tech circles, at least not any longer. This is now a political debate. I think it's poised to define the next decade. We've had leaders from both sides of the debate on the podcast. You might remember our episode with Eliezer Yudkowski, who argues very much from an AI safety perspective, and Beth Jesus, which is almost the complete opposite of that. So you've already heard what they think. Today's episode is more of a synthesis type episode. This is a debate on these two opposing opinions to help you think through where you might stand on the issue. We have Haseeb Kureshi, who tends towards the EA side of the conversation, which favors more caution, more regulatory intervention around AI, and we have Eric Tornberg. He tends more towards the EAC side of the issue, which is a bit more uh tech forward, faster progress, and a lighter touch from our regulators. We talk about the history of the debate, the cultures in Silicon Valley. We talk about Sam Altman, we talk about the regulators, the big bad US government, SBF, and what they think is the most sensible position on the acceleration versus deceleration debate.

One of the reasons, Ryan, why I was really motivated to get this episode uh out here is because I think right now this conversation is relevant to both crypto and AI, is about like accelerationism and are we pushing the gas? Do we want to push the gas further? Uh it's now just relevant to these two industries. I think there's more industries that is going to be relevant for beyond just what the scope of what this conversation is. I think this is like a sign of things to come. There are other industries that are also going to.

Present some very hard conversations to humanity, like, and therefore government. Uh and our tech sector is going to be coming out of the tech sector sector. When we talk about accelerationism, the world is going to look so much more different in 20 years than any other 20-year increment that we've ever had before. And that's only going to increase. So we have biotech and gene editing on the horizon. We have longevity, people uh like Brian Johnson literally trying to become immortal. Uh, and I think AI and crypto are like banded together as kind of these accelerationist movements. But the thing is, I think these are the first of many industries to show up on the accelerationist side. Uh, and this conversation about this like caution versus gas do we press on the gas pedal or do we hit the brakes? That is going to be a more it's going to define society more and more and more, I think, as we move forward into the future. So that's the kind of the frame of thought that I hope listeners go into in this conversation.

I completely agree. This is the political debate of the decade, but it's also probably the political debate of the entire next century. So a lot of lotta podcast episode fodder for us in in the future. All right guys, we're gonna get right to the conversation, but before we do we wanna thank the sponsors that made this episode possible.

Bankless Nation, I'm excited to introduce you to Eric Tornberg, an investor, technologist, and fellow podcaster. He's got a podcast network called Turpentine Media. Lots of excellent podcasts in that network at the intersection of technology, culture, philosophy, social commentary. Eric, welcome to the podcast, my man.

Thanks for having me. Longtime bankless fan. The stoke to be on.

You know, actually, before we introduce your fellow guests here, I actually remember a very early podcast episode that you had Ryan on as a guest, actually. I Ryan and Cyrus Yunesi, I believe. Uh, which is when some of the formative years around like Ether's money as a topic.

Amazing.

Yeah.

Joining Eric here on the podcast today, bankless systems probably know Haseeb Khrushy, another investor technologist podcaster, uh, who we we've had on the bankless many, many times before. Uh GP over at Dragonfly and is also uh in the effective altruist camp, well before anyone in crypto even knew what that meant. Haseeb, welcome back to Bankless.

Thanks for having me guys. Always fun to be here.

So just to lay some foundation for this episode, and I think what this episode is going to be is kind of evolve on its own. But really, we are watching two camps out uh evolve in the tech space, and it's also migrated into government as well. Uh, but there's also some nuances. This is the accelerationism versus decelerationism camp. Uh, there are some other tribes inside of these tribes, there are some adjacent tribes, but overall, there's identities forming in the world of tech and governance and where we are going as a society in the future, and it's causing arguments, it's causing debates. Uh, the accelerationists want to just hit on the gas pedal and innovate, innovate, innovate as fast as possible. And the decelerationists are like, ooh, scary. Uh, let's regulate. Let's regulate these things. Now, I don't think we've totally seen um perfect identification or identities form around these tribes. I think these this is all new for Silicon Valley as a whole, uh, which is why we want to bring you guys here on the podcast today to kind of like suss out and like figure out this landscape of these growing alignments across tech, across Silicon Valley, across politics. Think we can do that here on the show today?

Let's do it.

Perfect.

I saw I kind of just like laid down uh a whole bunch of stuff, uh different identities, different values. Um maybe Haseeb you can kind of get us started here because uh you were you were R an effective altruist well before anyone in crypto knew or cared what that meant. And that was one of the like earliest call it tribes, both in Silicon Valley in the venture space, and and also just broadly. Um maybe you can kind of identify about like the formations of that whole camp and how it's uh innovated or just been a part of the whole like Silicon Valley tech sector.

Sure. So I think effective altruism for most people, it came into the popular imagination with SBF, which now it's kind of an irrevocable taint on the movement and on the kind of the ideas behind EA. But EA came originally in around like 2011, 2012, mostly around Oxford and Cambridge, from a small number of philosophers who were very interested in this idea of trying to apply a more rigorous form of ethics and morality to philanthropy. It originally started with philanthropy and then broadened into a number of other ideas. So it starts with folks like Peter Singer, um, and uh, you know, a small, a small number of um uh what's what's who's the guy um

Who was affiliated with SBF. There's Will McCaskill and I think that's the Will McCaskill. Will McCaskill. That's right. Will McCaskill, Toby Ord, uh, a few guys who all basically came up around that time who started writing about a lot of these ideas in public. And the origination of the EA movement is very close to the rationalist movement, which was also founded by Eliezer Yukowski, who also has a lot of ties to AI Dumerism. And so the EA, though, is a little bit different from rationalism. Rationalism is the is the cohort that really came out of Silicon Valley. Whereas actually EAA mostly came outside of uh the tech sector, mostly came from universities. So

Now, EA, the core ideas behind effect of altruism very simply are that most people, when they think about doing charity or doing good for the world, they kind of turn their brains off. They're basically guided by their emotions. They kind of donate based on mood affiliations or what makes people look good or what sounds good. And they don't think as rigorously as they do when they are, for example, doing science or technology or politics or I don't know, maybe not politics, but when they're building businesses, for example, right? So when you're building a business, you A B test, you look for statistical significance. You're like very careful in making sure does this thing actually improve my product? Does this thing actually get the thing that I want? And if not, you are very, very careful to measure the difference and allocate resources accordingly. But when most people do charity, they're just kind of like, well, you know.

Here for the

Teaching violin in the inner cities, that sounds good. Sure. Let's like go, you know, start a museum. Uh that'll that'll be good for kids learning how to read or whatever. These kinds of things that like they sound really good, but are they actually good and how good are they? And so uh EA kind of came up as this very scientific, engineering heavy approach to thinking about how to do ethical, um, ethical actions in the most rigorous way. And there's a whole framework around it. I don't think we need to go into the details, but one of the things that came out of EA, which is now very, very relevant in the world of Silicon Valley, is for a long time, EAs have argued about what is the most important cause area that actually can move the most impact in the world over a short amount of time with a small amount of resources. And, you know, many people talk about global poverty, uh, animal welfare, but one of the most popular cause areas for a very long time, like almost 10 years now, has been uh AI risk.

The idea being that as people develop more and more powerful AIs, AIs might be so powerful that they could end up disrupting society or even causing mass human extinction. And this was before ChatGPT, this is before any of the modern kind of acceleration in AI advancement that we've seen over the last 10 years. And so people have been working on this, you know, a lot of small groups like Miri and Chai and these very weird kind of people in the back room doing stuff that was very disconnected from Silicon Valley. Only now, with the rise of large language models and the sense that everybody has of like, oh shit, this is actually happening and this is real, has the discourse around AI risk started to really intersect with society, with tech, with economics, with politics. All these things suddenly matter now. That's kind of been happening in a backroom for about 10 years. That part of EA, so I was aligned with these ideas basically like 10 years ago, before any of this stuff was really on a global stage, of thinking, hey, you know, you read these arguments, you know, there's a very famous book by Nick Bostrom called Superintelligence, where he sketches out a lot of the in-principle arguments of how rapid AI advancement might cause some degree of existential risk. Um and you read the arguments, you're like, yeah, you know, this kind of makes sense. Uh it's not a slam done, it's like obviously correct. It's not that clearly this will happen, but there's at least a risk that it will happen, and nobody seems to be thinking about that risk besides these, you know, small cohort of weirdos in the East Bay or in in Oxford. Uh and so people thought at that time, oh, yeah, you should donate some money to these people because this seems like a very underexplored risk that right now society is ignoring. Now, today it's quite different. Society is not ignoring that risk. Now it's like a it's something that the White House is thinking about, which is kind of crazy, right? Very recently, Paul Cristiano, uh, who was the head of you is a very, very early EA, he was the head of safety at OpenAI. He left OpenAI. Now he is uh at NIST. NIST recently hired him as like the head of AI safety at NIST. So now at this point, you know, it's uh very firmly entrenched in at least the US government is this this concern that, hey, AI safety is a real thing, and that's not just um.

It's not just sort of AI bias or AI replacing jobs. It's also catastrophic risks that might arise from the rapid advancement in AI.

Yeah. I think probably listeners are generally familiar with uh GiveWell, which is this charitable organization that does a lot of research for understanding if you give this one charity one dollar, how effective will that one dollar actually go into like improving people's lives? Uh and then like this is where famously like they came down to like malaria nets. If you actually want to like put your one dollar and save the most number of human lives, you would just buy malaria nets for like kids in Africa to prevent them from getting malaria. But this would also like this is a very effective and rigorous process of understanding how to capital allocate in the world of charitable giving. But I think as we are working on defining the landscape of all these different like tribes and identities about like the future come uh arises here. I think, Haseeb, what you're also alluding to is that, well, there's like this like risk-off, low-risk research and pragmatic capital allocation strategy in the world of charity. But then there's also like, okay, well, what about some like venture bet future high impact things as well? So not just about like, hey, current kids uh could be impacted by this, but like we could also have future generations and like not just like next future generation, but literally every single future generation. So that's this is how like the world of effect effective altruism got interested in like AI risk because like that's literally the whole thing. It's like all of human human society. And so effective altruism is kind of taking the like not just like a pragmatic approach to charitable giving today, but like also taking like venture bets in charity or venture bets in like effective altruism. Uh, how how do you how do you how would you feel about just that that out on right there? Reflect on that for a second.

No, I think that's exactly right. Most people, when they think about EA or they hear these recommendations among EA, they're immediately turned off.

Um, there's a few reasons why people immediately get turned off. One is that, like, well, you know, who are you to say? What's the most effective and what's not? You know, seems like you guys are kind of these big central planny type people, and you know, naturally people have an aversion to that. Uh and the, you know, so one thing to understand about EA is that EA is making recommendations at the margin.

Right. EA is sort of not assuming that most people will follow EA because they don't. And that would be stupid to assume that everyone will do what you tell them to do. So you always want to be thinking, what should more people be doing at the margin?

And you'll probably influence 1%, maybe 2% of people at the most. If you're influencing everybody, like let's say you are the government, then okay, the way you allocate capital and the way you make recommendations should be very different. But if you are saying, okay, I can basically influence about one to two percent of people, what should one to two percent of more people do given where dollars are already being allocated?

And the answer usually is, well, okay, you know, there's some obvious things like we should have schools, we should have sanitation, we should have, and so somebody might say, well, are you arguing that we should not have schools or not have sanitation? Instead, we should all donate to malaria bednets. The answer is no, obviously not. Um, given where the majority of dollars are being deployed today, where should the next dollar go? That's the real question that EA is tasked with trying to answer. So given that backdrop, um, now you might ask the question of like, well, you know, if you donate to an anti malaria bednet, okay, I guess that makes sense. You save somebody's life from dying of malaria. That's a very cheap way to save somebody's life. Um, but you know, donating to AI risk, maybe AI is not a risk, right? Maybe there's only a 10% chance that AI is a risk. In which case, you'd be wasting that money.

And again, you know, the way that EA frames this is that you know you're thinking more about a portfolio of good, as opposed to thinking, well, definitely this good will do this much and this good will do that much. Uh, most people, when they're thinking about, okay, I want to do one thing, um, you know, I want to eat lunch. And if you're gonna eat lunch, are you gonna take a risk on like, you know, maybe this random restaurant is like an amazing restaurant and I should try it out? Or you're just like, look, I I know that if I go to, you know, I don't know, Denny's, at least have a decent meal, right? I don't know, depending on how you feel about Denny's. Um, and most people are naturally very risk averse when it comes to their own lives or the things that they do with their time. But the idea is that when you have a large portfolio of giving, of all the giving in the world, you actually want there to be some people who are doing high risk giving because, you know, sort of high risk, high reward, if nobody's doing high risk giving and nobody's doing stuff that looks kind of weird or that may not pay off or that may not even matter, but in the in the times when it does matter, it really, really matters a lot. Um, so the analogy that a lot of EA people give is that, you know, imagine that um, you know, this is something like uh like like like nuclear research. If you were in the 1930s or the 1920s and you were thinking about nuclear research, um, you know, at the time it was kind of this relatively boring kind of scientific thing that nobody really nobody really understood why this mattered until they saw the atom bomb and they saw the destructive power of nuclear energy. And at the and there was a time that this was considered to be very speculative, that that this was even possible at this kind of scale to have this much destructive damage from this technology. And, you know, on the off chance that it turned out to be right.

That the order of magnitude estimates of this stuff was correct, then you would really want there to be a lot of research into the safety of, you know, how to prevent nuclear proliferation, how to prevent mass nuclear scale wars. Um, but you know, people maybe underinvested in that. And as a result, you know, people in the you know 50s, 60s, 70s kind of lived under this specter that maybe there would be maybe one or two more decades of human existence and then the world would just wipe itself out. And, you know, for all we know, maybe we weren't that far from that happening. Um maybe it was, we were, we were kind of various times on the brink of massive amounts of human uh damage and catastrophic risk from this proliferation of nukes. And so the question is is AI like this?

Is AI a similar technology? And the answer might be well, probably not. Maybe AI only has like a 20% chance of that.

10% chance of that. But even if it's 20 or 10% chance, what an EA would likely say is that, well, that is high enough that you probably want some people, maybe one to two percent of people, spending their time on this. Because, you know, one to two percent of people spending their time on something that might be 10% as bad as nukes, that that's a pretty good trade. That's a pretty good investment if you're thinking about the overall portfolio of how people are spending their time and spending their resources. So if you think about EA as here is what I decree as an EA, as this East Bay rationalist guy, that everybody in the world should be doing, then I think you'll you'll come away with the sense that EA are EAs are a bunch of you know selfish pricks and they think they should run the world. Um, but if you come away with the sense that, oh, okay, EAs are advocating about at the margin how to alter the the portfolio of all the different things that human beings are working on to ameliorate risk and increase the likelihood of human flourishing, then you might say, okay, that sounds like a reasonable investment strategy. You know, maybe I don't agree with it completely, but it's it's a lot more reasonable if you think about it that way.

So Hasiba, I want to bring Eric into the the this conversation, just kind of reflect on what you said and add. But I have just one question that kind of plagues me. So we started this conversation talking about accelerationism versus delarationism. The way we started this conversation was talking about EA and the rationale behind how EA came to support and fund a lot of the AI safety initiatives. And it's really, when I think of AI, it's really like utilitarianism or consequentialism as a philosophy, kind of applied to giving. That part to me sort of makes sense. But it doesn't necessarily follow that AI must lead to investments in funding of AI safety. Because if you are in the EA community and you believe in this sort of giving, you could just as well make the case that uh in order to benefit the most amount of um, like the greatest number of future humans, say trillions of humans, we want to actually invest in AI technology because we believe AI technology will build a utopia.

And cure diseases, cure illnesses, solve uh the problem of of death and like old age and all of these things. And so you could easily make the case in the EA community under that philosophy that no, we shouldn't be funding necessarily anything that would slow down AI. We should actually be funding startups, we should be funding open AI, we should be funding like all the tech that goes into AI. But it seems like the community just forked mainly in one direction such that EA has become somewhat associated with uh AI safety. I think, by the way, recently maybe some of the founders of EA, um, Will McCaskill and others have kind of walked back from that and be like, hey, you know, that's not.

A EA is not necessarily AI safety. They're not one and the same. There's kinda some differences. Anyway, I I just throw that idea out there and uh Eric, w what are your reflections on this conversation so far?

Well,

first I just want to add that not all long termism is is the in the venture bet category, right? It's also things like pandemic prevention or reducing nuclear proliferation, things that already already exist, already happened. And they were talking about pandemic prevention before COVID, right? So they're really onto some things. The the the leap that

the long termism can be um

broadly explained by this idea that EA is about a kind of arbitrage, right? Uh Dave, you described how if one dollar can make a better difference, uh bigger difference to people in Africa than it can to people in San Francisco, well maybe we put should put our dollar to to to people in Africa. And and EA says, okay.

Um

Because a person in Africa's life is worth as much as a person in San Francisco's life. What about a person that doesn't exist yet? What about a future person? That person's life is also worth as much as a current person's life. And guess what? There's gonna be trillions of future people, way more than than exist today. And thus we should really care about the future. And there's a lot of people who got on board with that. There's a lot of people who didn't get on board with that. And this was a schism in the in the EA community. Some people are like, hey, I'm all about effective charity, but this long termism stuff that's a bit too bit too out there with me uh for me. And there's some people who go all the way.

And that now when we go even among the people who go all the way, there's another schism that Ryan just outlined. Some people say, hey, it it really depends on what you think about the future of AI. S some people say that the idea that you just said, Ryan, which is if you're concerned about helping most future people, you want to accelerate uh AI. And th these are people who are

Effective accelerationists. This is why there is an additional schism. It's people who are not on board with the AI safety agenda. And one thing that's worth noting, you know, EA and um EAC are having the strongest conflict. But what did um Henry Kissinger say something like the tyranny of small differences? Like uh AI safety people and EAC people agree on 99% of things in many cases. They they both believe that the people who are worried about misinformation or uh DEI or AI saying racist things, they're

They're not focused, they're not at the adult table of the important conversation. Those people are misguided. They're not disagreeing with that. And in many ways, AI safety people and EA people are tech accelerationists. They they agree that nuclear regulation has been really bad. They they are one accelerate things like self-driving cars or um longevity or or other things that EAC people get on board with. The one place in which they disagree is this field of AI. They say AI is this time it's different. We're not just introducing a new technology. We're almost introducing like a new form of evolution or a new species that it one day is going to be cognitively way smarter than us, and thus is a threat, not just to fake news.

It's not like social media, not just to jobs,

but to

actual humanity, to actually uh the chance of of us being extinct. And thus we should treat it differently. And that is the core of the argument between uh effective accelerationists and uh effective altruists as it relates to AI safety.

Okay, okay. So we're we're dealing with like this is like an argument between like Catholics and Protestants basically. It's like uh we're all all in the same religion, but like you guys are are arguing over these these specifics here.

I'm I'm gonna dispute that. I'm gonna dispute that a little bit. I think I think um I I'd say a lot of EAC's um so first of all, I think it's probably worth descri worth actually defining what EAC is, what it means as a movement, because I think it's also been in a sense co-opted by what people want it to mean, which is like accelerationism, right? This idea that oh, all technology is good and all technology should be faster, we should be super libertarian, we should, you know, kind of let all the guardrails off and just let it room, room, room, right? That's not actually what I says, right? If you read the EAC manifesto from from Beth Jesus, who's the guy who invented it, is like this Google engineer, works quantum physics. It's actually pretty fucking crazy, like what he actually literally says. Um, like I don't know, Eric, I I uh I'm I'm not uh it's been a while since I've actually looked at that manifesto, but there's stuff in there about how, like, yes, if um if AI ends up, you know, totally conquering humanity, like that's good. Uh we actually want to feed entropy, we actually worship entropy. Entropy is the thing, you know, the the core value from which all good flows. Um it's like actually very weirdly cult-like and kind of anti-humanist. I think most people don't act haven't actually read it, or they they just kind of take it as a vibe and they're like, well, the vibe that I want it to be is like, you know, basically Mark Andreessen. I think that that is what I imagine EAC is. But if you actually read the EAC Manifesto, it's like some, it's a bunch of other weird shit that's adjacent to like the Mark Andreessen philosophy, but it's not quite the same thing. So I think it's sort of been typecast into this is like Silicon Valley, uh, you know, pro tech libertarian energy, but that's not that's not literally what EAC says.

I don't know Eric if you ha if you would agree or disagree with that.

I I I I do agree with it, and I I should say that that is my um

My tribe in some sense is people like Mike Solana, people like Balogy, people like Mark Mark Andreessen. And so that is where that is where I come from. And so I've been very sympathetic to this EAC movement, right? Which

to some degree says hey, um

over the last decade, there have been a lot of anti tech

movements and sentiments and people trying to use arguments to thus regulate tech in ways that have been very bad, from whether it's energy or social media or a wide variety of things. How about crypto?

Yes. Yes, exactly. And we're not going to let that happen here. And we're finally going to stand up for ourselves. Because you saw Zuckerberg and others apologize. And that didn't really get them anywhere. It only conceded their sort of lack of moral sort of credibility and that they were wrong and blah, blah, blah. And that's all these bad things. And so this EAC is coinciding with a desire for tech to stand up for itself, to say, hey, we are actually good. We are actually going to push back and we are going to defend ourselves.

Um now