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Pessimism is often viewed as like a mark of sophistication.
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Even if you are consistently wrong, if you are consistently pessimistic, people love to hear that because it sounds like you're being very thoughtful and very serious.
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>> I call myself a rational optimist.
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I think that we are really good at solving things.
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I fully expect that we're going to a lot of stuff up, but those have to coexist together. We need more of that.
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like that we need we need that kind of thing much more like now than ever.
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My guest today is Sam Arbsman who I look at as one of the most fascinating boundary walkers.
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Sam does not have any territory that confines him.
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He is interested in virtually anything and everything.
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Please enjoy my conversation with Sam Arbisman. Welcome back, Sam.
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And I got to disclose you are one of my favorite conversants because we go wild places all the time.
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So, let's start with opening the Cabinet of Wonders. >> Okay. >> What What's new?
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What's new in the Cabinet of Wonders?
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>> Um, well, so I feel like since we last spoke, we were talking about things around like the history of technology and technological archaeology and kind of like spunking.
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I'm definitely thinking a lot more about that.
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I think there's something to be said for like revisiting the past of like the history of computing in order to kind of understand like paths not taken.
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Um so actually one and and I think related to this is also just the extent to which you realize that things like time periods that feel very new are not nearly as new.
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So like for example um I don't think we talked about this last time.
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There's there was an organization uh in the ' 70s called the people's computer company. I don't know. I know. I know about it. >> Okay. Yeah.
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So, so it was it was this and it sounds like it's a company, but it was actually was a newsletter and like a center and kind of this weird thing, >> but the um I think like the opening newsletter um in like 1972 had like their sort of like mission statement and it was all and I think it was something to the effect of um like computers are being used against people instead of for people.
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They're used to control people instead of to free us.
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Like we need to kind of create this people's computer company.
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And that feels like very much of this moment.
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Like it doesn't feel like, oh, it was written decades and decades before.
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decades before. These are things that people are still grappling with and trying to figure out, okay, how do we actually make computers like kind of for humans and kind of like at the human scale and all these kind and and of course the interesting thing is even though it was at the human scale, this
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was even before personal computers like they were still thinking about like how do we actually make them engaging for people and and I'm just struck by that kind of thing like over and over seeing the way in which computing history and technological history just rhymes and like what we can actually learn by plumbing those steps. >> Yeah. And one of the things I I I always >> Yeah.
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And one of the things I I I always search for what I call patterns, you know, very primitive.
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And one of the biggest patterns around innovation and technology is the way humans react to it.
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>> And there's always a subset of humans who absolutely hate that new technology.
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Um, and right now, of course, we're seeing it with AI.
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I saw a tweet that I wanted to ask your opinion about because I I want to think about it. Uh the tweet was this.
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It said I believe that AI is going to actually bifurcate society more not not less.
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Um and that smart people are going to get vastly smarter whereas and this is not my tweet so whereas people who are not that smart are going to get dumber.
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And as I read that, I kind of thought it does have a parallel in terms of the way you think about AI.
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I personally think about AI as a tool that I can use.
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I don't want it to think for me.
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I want it to help me do research.
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I want it to help me with a bunch of that type of things.
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And I love going like for example one of my new habits whenever I see something that I don't really agree with I immediately steelman the argument for it. >> Okay.
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>> And it's really reveals quite a bit >> because yeah I I I don't think I've done it yet with a single time with huh that's a good point. >> Yeah.
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>> What what do you think about that?
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So that I I wonder if it's less true about like smart versus not as smart in terms of like what it's going to accelerate and more about like having an open mind versus not having an open mind.
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And I feel like many people who are smart often mischaracterize those kinds of things cuz I think if you have an open mind and are willing to try new things, it is going to accelerate you.
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If you think, oh no, this is not for me, then right, it will kind of not help at all or stify or whatever it is.
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Um but I do think right if you are open-minded no matter your intelligence level it actually does have the the possibility of kind of accelerating whatever you are learning and things like that.
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Um but I at the same time though I will kind of caveat that with the fact that I have seen pe some of the people who are most excited by AI they are they're excited but they're also like in practice like totally overwhelmed where it's like they are more busy than ever.
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they're spending all their time using it and they're just kind of frantic, which I can understand, but that definitely doesn't seem like the kind of tool use that feels enriching like for for one's humanity.
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So, that I'm a little skeptical of, but I definitely think right, I think it's much more like the state of mind in terms of open-mindedness of like if you are willing to say, okay, this thing might actually be useful, right?
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Then it can accelerate and it's and it's much more right rather than kind of using it in place of your own thought.
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It's like, okay, how can I make myself kind of the best version of myself or a better version of myself?
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But then there's the opposite, which is the people who say, "No, this this thing has nothing for me."
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And then therefore there there's right then there's like nowhere to go with it.
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It just kind of ends and kind of cuts off cautioning.
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>> Yeah, I I love that distinction cuz I obviously that was kind of the first place I went to.
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It isn't uh raw IQ or anything like that.
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It's really disposition, open-mindedness being the the top one.
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I personally think that and I think you agree, but that generalists who are polymathic, who have lots of interests, like it's catnip, right?
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But the on your point about the uh using it as a tool.
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So, I'm writing a uh I've written four books as you know uh but I'm writing a fiction book and so I used AI extensively to train me on developing my fiction voice and like I watched a lot of videos on YouTube and everything and I made notes and you know there was some really interesting things like you know everything's the hero's journey or whatever.
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Uh, but it wasn't until I created a bunch of prompts for it to be really mean to me. >> Okay. >> Yes.
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>> And I would like the exact opposite of like like sophincia.
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It's like no like just trash everything I'm creating. >> Exactly.
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I really want you to be mean.
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The And like one of my avatars was the meanest but smartest critic in literature. And ooh, he's wicked.
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Anyway, but the interaction developing the the voice. Wow.
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Like I I've never used a tool that effective. >> That's amazing. And so, right.
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And so when you're using it, are you right?
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Because I feel like a lot of like writers certainly preai a lot of the time in which you kind of like start to develop your voice, it's often times you're kind of interpolating based on other voices and like other author authors that you that you look up to.
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Has this been able to kind of like fasttrack that process of like helping you find your voice that much more like rapidly so you don't kind of have to meander for a long time until you get there? >> Absolutely.
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Um I love reading, right? I love fiction.
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>> My problem with fiction is I'm an addict.
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Like if I start reading fiction, I'm up until two because I just keep reading.
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>> But my tastes in fiction are generally literary fiction.
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you know, like David Mitchell is one of my favorite uh Cloud Atlas and all of his I've read everything he's written.
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Uh but I also love sci-fi.
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Uh but my challenge was having written four non-fiction uh books, I had a very distinct voice in non-fiction. Yeah.
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>> Which I learned very quickly was a really bad voice for fiction.
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But >> so one of the parts of my learning curve was here are the authors I adore >> and helped me develop my voice which is very by the way it turns out very different than those authors. >> Okay. Yeah.
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Uh, but the the speed with which I was able to come up to writing in this new voice, I I honestly don't think I could have done it without the interactive because I I think that that, as you know, I'm a huge fan of the senitar model, right?
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Human plus machine, right?
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I think a lot of the criticism that you always hear about AI slop, etc.
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Well, that is pushing a button saying, "Write me a science fiction novel." >> Yeah.
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>> It's going to write it's going to compress it to whatever the middle kind of tier is.
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And it's it not being used as a tool at all.
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And so like I'll read that stuff and I'm like, "Ah, this is awful."
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However, when you use it as a tool and especially as an editor, it's pretty cool because like literally it'll say, "Yeah, you that character would never say that."
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And and I'll like read the line that I wrote and I'm like, "God damn it, it's right."
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>> That's so interesting.
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>> So, I I just think uh that the ability to it's it's a bit like having a tutor, right?
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And we're seeing this in education right now with the various schools that are forming.
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What What are your thoughts about that?
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What do you think about really changing our educational system? I I have a bias here. >> Yeah.
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>> I think our educational system is horrible. >> Okay.
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>> Uh especially because I think it's incredibly antiquated.
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It was it was selected for training industrial workers.
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I kind of think to sit in a room for eight hours and take instructions and that is not the world in which we live.
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>> So I'm definitely sympathetic to what you're saying.
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I I'm also sensitive to the fact that like often times whenever you're kind of engaging or interrogating or trying to change any sort of large complex system, you don't necessarily want to just throw it all out and start from scratch because you're going to end up with a system that's like equally if not more complex and probably not as well understood and then you have to like deal with like trust's fence and all these other kinds of things.
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And so for me, I'm much more of the opinion of this kind of um and actually Carl Pauper, I think in one of his books about he has this idea of kind of like utopian engineering versus peacemeal engineering.
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And the utopian engineering is okay, we're going to just like create this thing with this very clear end.
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And oftentimes it kind of like destroys society in in the in the the path of getting to that versus peacemail engineering is saying okay let's try to experiment a little bit like here and there change kind of things see which works um which doesn't re-evaluate and slowly but surely hopefully get to something better.
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So I definitely think education has a great deal of room for improvement.
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Um I'm hesitant to say we have to just like throw it all out and kind of start from scratch but I definitely think at the margins there's so many things we can be thinking about.
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Um, and it also depends at like the the grade level or the scale that you're kind of thinking.
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Um, so like for example, I think that one of the areas that we really haven't thought about as a society for a long time is just sort of like continuing adult education.
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And obviously we do think about that.
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But for me like just continuously learning and being curious about the world like that's a thing I always want to be doing and there should be mechanisms for everyone to be involved in that.
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And so if we can create institutions and mechanisms for allowing that and like democratizing that kind of thing and obviously AI can probably help with that kind of thing quite a bit then I'm all for that.
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So like there's that then there's okay rethinking the college level education and I think there's lots of space for that and then right then you can also just go all the way down to like K through 12 or even like infants and like toddlers like there's I think at every stage you can probably modify it but for me it's not okay I have a new idea let's throw away the old thing.
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throw away the old thing. It's more let's actually build some new system or some new institution, new organization, new mechanism that's maybe more bespoke kind of like much more adapted things like that and then allow that to compete
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with the other systems that are already there and then hopefully kind of according to that like peace peace meal engineering kind of approach it will there'll be some competition the new one maybe will do really well the old ones will actually kind of have to up their game. So, uh, yeah, I'm actually super
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So, uh, yeah, I'm actually super excited, but I, yeah, but I think a lot about, um, yeah, that kind of like continuing educa, like continuing adult education kind of model and you mentioned before like generalist models and polymath that kind of things.
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I think that and maybe this is also just like me justifying my me being too interested in too many different things, but we need more of that.
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And and actually so one related to the polymath stuff my mother told me that when she was young when she was in I guess the the Girl Scouts she said so you had like all these badges you can specialize in like I don't know not tying or I don't know do arts and crafts or whatever it is.
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And she said there was one badge that was the dabbler badge which was you could get a badge just for dabbling in a whole bunch of different things.
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And I love that idea like that that I mean that's kind of like that is my dream and we need more educational models that kind of valorize and incentivize like the dabler badge of knowledge at all different ages and levels.
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So yeah, I I think there's a lot of space here. >> Yeah.
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And just to be clear, I agree 100% with your approach.
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>> I am not in favor of top- down systems being designed >> because you're right.
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I'm I'm a huge fan of Ken Stanley's Greatness Cannot Be Planned.
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Everything is iterative >> and like you can't decide, oh, I'm going to get here and that is the only path because you've got to see all of the branching everything else.
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So 100% agreement around the way it should happen.
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Um, I I I think though that the idea of the the it would be great and maybe it happens slowly, but it would be great if the new way of education.
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I think maybe you're right.
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I think maybe start with adult continuing education.
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Um, >> because you don't have to worry about regulation or anything.
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It's like you can just build a thing >> and you can try everything. >> Yeah.
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You can do whatever you want. That's amazing.
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We we are investors in synthesis school and they've done really well with getting kids to like math. >> Yeah, that's amazing.
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>> Uh which is really interesting.
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Um and we also have some other initiatives where we are helping out with tablets that are solar powered for uh less advanced uh countries.
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By that I mean they don't have Wi-Fi everywhere.
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Um, and but you're right.
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Let a thousand experiments bloom.
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What are your thoughts about, you know, I know that you grew up on the science fiction comic books that your grandfather, right, gave you?
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>> They give me all these like old magazines like short stories. >> Yeah. Yeah.
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>> And and are is that not happening anymore? I don't know. I don't know.
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I have grand >> science fiction or >> No, no, no, no, no, no.
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kids like with the comic book with that type of thing. >> Okay.
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I mean, so to be clear, like these these mag So this was um so >> these were not comic books. >> Yeah.
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So it was like these like kind of like pulp magazines and so it was like so the one that my grandfather I think >> most subscribed to was analog science fiction in fact and as far as I'm aware it's still around.
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Um, uh, I haven't like I don't I don't subscribe to it, but yeah, he would just give me these like shopping bags full of all the old copies like after he he uh had finished reading them and then like I would take them like like when I would go to summer camp, I would bring them all and just read them.
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Um, I don't know to what extent that's out there anymore.
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Um, certainly because you can put things online like there's just an abundance of stories out there.
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Um, but in some ways maybe that just makes it a little bit more difficult to or at least there's another hurdle of like just give me a whole bunch of stuff that I can kind of just like plow through like yeah when I'm at camp or whatever. Um, but I don't know.
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I I I certainly hope I I I think there's short like science fiction short story magazines still out there.
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And um I don't know if it's a burgeoning industry, but I really want it to be. >> Yeah.
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>> And and you were deeply influenced by the Foundation series as was I.
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The thing we're trying to do with Infinite Books is bring back positive science fiction because like the stuff I grew up on was like really pretty positive about the future.
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>> Um, obviously there were the problems, you know, Harry Seldon forecasts that you're going to be a thousand years of darkness.
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>> Uh, but >> then we kind of fell into this very dystopia black mirror.
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In fact, we published a book called White Mirror. >> Right. Yeah.
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Um and do you do you see those kinds of trends happening?
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those kinds of trends happening? I mean, so a number of years ago, right, people had noticed that ex exactly like very explicitly what you were saying and um so there was a there's a center at Arizona State University called the Center for Science in the Imagination and they actually partnered with a
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number of science fiction writers um and I think the kind of like galvanizing essay was written by Neil Stevenson was and the idea was like can we create more positive optimist optimistic visions of the future and they actually they they I think they partnered writers with engineers and scientists and okay. So
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So then they would write the story and then the um the scientists and engineers would kind of flesh out the actual like meat of whatever idea was was in that and kind of show like its its possibility and its plausibility.
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Um, I wonder if though some of this is as the world not only is changing kind of faster and faster, but like as our ability to like look further into the future, like that horizon gets closer and closer, that means that we just kind of not that we're dystopian, but we kind of just cut off a little bit of that ability to kind of see further forward.
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And that makes it less easy to imagine these positive visions of the future.
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I mean, >> I'm kind of thinking this through as we're talking, but I would say I mean >> I think I mean certainly there are positive visions of the future that sometimes have in our future but their past a negative moment.
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So like there would be um there's like some amazing future but before that we have to kind of get through I don't know World War II or something like that.
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Um, I would love to think we could get to the really positive vision without necessarily getting getting something really really bad.
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Um, but I just wonder if that if it's simply the fact that as technological change happens faster and faster, we maybe lessen our capacity to think far off in the future.
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And that maybe somehow in our minds gets caught up with not quite dystopia but sort of a impoverished vision of the future because everything's changing so rapidly.
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And so at a certain point you're like, "Oh, I can't really I can't imagine what that's going to be like."
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And and people have talked about this idea that like like thinking about like like the year 2000 was this kind of like mythical far-off thing.
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And of course, we would as we got closer and closer to the year 2000, people still put like set stories in the year 2000, even though it was getting closer and closer and not nearly as far.
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And of course, now it's like it is in the rearview mirror.
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Um there's actually the uh um the the the music duo uh Flight of the Concords.
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They actually So they have like like the the humans are dead and like it begins, right?
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The distant future, the year 2000. And I just I love that.
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Um, but I think many of us kind of are sort of anchored to that kind of past vision of the of the future.
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And I don't know, maybe we just need to start talking about I mean, what is it like um like 2001 Space Odyssey like the sequels were like there was 2010 and 2061. >> Maybe we start Yeah.
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start aiming for 2061 or I guess I Futurama has the year 3000s like some of those kinds of things.
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So, and I I feel like for every example I'm giving, you can probably think of a counter example, but I almost wonder, right, if people are just so concerned with all of the changes happening in the here and now that they just don't have the bandwidth to imagine these futures.
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And so, it's not as if we're dystopian or utopian.
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We're just like very like this moment focused.
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And that simply cashes out in the inability to imagine these positive visions.
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Well, I I have a thesis that basically um our our our human OS, our human operating system has a couple of kinks that lead to a more bleak uh outlook.
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And the first is a bias towards negativity, right?
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Which if you look at evolution and probably not the worst thing to have if you're >> if you plan for the worst, yeah, you'll probably survive a little bit.
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>> You're going to have you're going to have a bias for negativity.
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But also this desire for the illusion of certainty, right? Yeah.
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Because it is an illusion unless we're talking about the sun coming up tomorrow.
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And have you ever noticed like there's nobody running around like pounding on tables saying, "I will bet a million dollars the sun's coming up tomorrow." Right?
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coming up tomorrow." Right? But those two together kind of lean toward well what's the worst that I mean David Deutsch with his you know uh the the principle that we are the greatest connectors and explainers we're kind of at the beginning of infinity like I I read that and I'm just like I love this I love looking at it this way but then he also does a great job showing why so
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many uh societies basically all >> because of the precautionary principle and my view has always been kind of around technology in particular everything is dual use and I don't mean just AI or computers fire is a technology the ability to consistently relight a fire >> is a technology and we didn't ban fire even though fire is really dangerous same with electricity can be very very dangerous ous. So
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So instead of banning things like the precautionary principle would have many of those closed-minded societies do, we came up with fire engines, fire departments, fire warnings, fire extinguishers, fire exits.
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>> And I will caveat that with the fact that like those and fire has been around for quite a long time and some of those technological advances and like the like societal advances, those are relatively recent.
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recent. I know which is which when you kind of think about it like it's kind of wild that like Benjamin Franklin was doing some of the work around like like fire departments and things like that and I don't know all the detail but I vaguely remember this and right that's only several hundred years old and we've
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had fire for for a long time and so I think um so I will kind of so I think there is some caveats there but going back to what you're saying of like kind of pessimism and things like that I feel like though that pessimism is often viewed as like a mark of sophicic ication and and I I
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personally think like oh like thinking about how things can go well that's super exciting and being optimistic like these are amazing things that being said I feel like time and time again even if you are consistently wrong if you are consistently pessimistic people love to
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hear that because it sounds like you're being very thoughtful and very serious and I feel like I mean I guess Paul Erlick recently recently passed away and right and he was I >> and Julian Simon won the bet >> yeah Paul made his wife make the check out to him because he didn't want his signature on it. Oh,
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Oh, >> I didn't even realize that.
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>> And if you do a deep dive on him, like the fact that I I mean, not to speak ill of the dead, but he was consistently wrong across his entire career.
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And yet they kept inviting him back.
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He kept having the lecture series. He kept being on TV.
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Meanwhile, Julian Simon, you know, the the the greatest resource, right, us humans. >> Yeah. >> Like, he won the bet.
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If if we walked out into Union Square right now and just randomly asked people, have you ever heard of Julian Simon? How about Paul Erlick?
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>> It's going to be 10 to1.
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Paul, >> that being said though, I've seen I've seen research that showed that depending on when you had kind of started and stopped the bet, it could have been a tossup, which is so it's a little bit more complicated.
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That being said, it shows that like right what like the way to think about the future right is kind of this weird complex like nonlinear system and to be so certain about it and like whether it's certainly pessimistic or just like certain like oh no this kind like that I feel like also is not the right way to operate.
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Um, and maybe it's not even just pessimism is a sign of sophistication.
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And maybe it's just ultimately certainty and like that like having that sort of like righteous simple certainty is something that people find very appealing and going back to like the human OS kind of stuff like that is the kind of thing that we are drawn towards.
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But having that epistemic humility of like, oh, maybe I'm like, maybe there are weird nonlinearities and unexpected consequences and second order effects and we should kind of think through all these kinds of things that does not I a sophisticated pundit make or at least an appealing pundit.
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But we need more of that.
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Like we need we need that kind of thing much more like now than ever. I couldn't agree more.
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And like I call myself a rational optimist because I fully expect that we're going to a lot of stuff up.
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And if you don't expect that, you have not looked at history.
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And so the idea that I I move forward with is I'm incredibly optimistic about humanity.
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I think that we are really good at solving things.
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We're also really good at screwing things up, but those have to coexist together.
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And and so to to be uh panglosian or polyianish is going to be defeated, right?
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Because there inevitably will come problems.
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And the way I look at it is there will, you know, there will always be problems no matter how good whatever gets.
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We it doesn't have to be just technology.
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any part of society, right?
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No matter how good we get it, there's always going to be problems.
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And sometimes we make them more apparent because as you say, like in the last, let's call it what, three or 4 hundred years, many of these technologies like got invented.
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We're missing the thousands of years where people are like, "Yeah, that's just the way it is, right?"
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And so I I definitely believe that to be prepared for the problems you that's got to be part of the way you think. >> Yeah.
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And and this is like going back to like Popper and like the peace meal engineering just constantly saying okay like things can be things are good.
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We can still make them better.
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Let's constantly try to iteratively improve and just try to shy away from sort of that like that utopian vision, >> right?
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because utopian visions often elide a lot of the complexity but are also right like they're they're utopian.
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They're not the real world and the real world is messy.
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And so let's just actually use the kinds of approaches that work with the messiness of the real world which I think we're pretty good at.
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And obviously as the world gets more and more complex and interconnected you have to have a certain amount of humility and but that's kind of the whole peace meal engineering approach which is do things run experiments try to improve things bit by bit see what works see when things bite back and make a better world slowly but surely.
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Yeah, I I'm 100% in the camp of peace meal, right?
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Because you can't know, right?
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It's like I love that quote about no matter how smart somebody is, no matter how innovative, no matter how creative, you cannot ask them to make a list of things that would never occur to them, >> right?
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>> And and like one of the things that I believe in very deeply is cognitive diversity, right?
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And and I think that the whole movement, you know, diversity, etc.
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, they they got it wrong, right?
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Because they made it about skin color, about sex, about, you know, where you come from.
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The the diversity that really works is people who think very differently.
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And I love the we we see it with our fellows, uh, you know, about our fellowship program.
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And when we get them all together, it's just the most delightful couple of days ever. >> Yeah.
29:57
because you have like deeply scientific people who are working on really >> like edge case projects >> with with authors who wonderful don't think like that at all but the synthesis >> that comes out of those is really truly extraordinary. >> Yeah.
30:17
And and so that kind of leads me into the conversation where you think it's much more important to look at biology as say physics when we're dealing with these very human systems because again I'm 100% on board. The real world is messy. >> Yeah.
30:36
>> And utopian visions led to Mao to Stalin to Hitler. Right.
30:41
They maybe weren't utopian, but they were this is the way they were totalizing. They were totalizing.
30:47
And I'm terrified of that. >> What do you think?
30:50
Like if I was going to put you on the spot and say, "All right, Sam.
30:54
I'm going to fund an institute that you are going to be the head of.
30:58
You're going to be the executive director.
30:59
Walk me through what that institute looks like."
31:03
>> And I I definitely think a lot about these kind like weird research organizations and like the need for more of these kinds of things.
31:08
And I will caveat all this with beforehand like I'm fairly agnostic as to what are the like right kind of models.
31:16
I think we just need to try more things.
31:17
That being said, uh I definitely think I we were talking before like Ken and Joel layman of like the why greatness cannot be planned.
31:24
the why greatness cannot be planned. I think that as much as I think a number of people recognize the importance of that kind of thing, it's very hard to incentivize like omnivorous curiosity and kind of like undirected sort of approaches of
31:44
like just pursuing novelty or interestingness because oftentimes in the research world um or when you're even when you're funding people, not projects, there's still a certain short-term nature to it and like accountability and and so it could be like there's like blue sky research in academia. It's
32:03
It's still subject to grant cycles and so and you can only operate over the course of like several years.
32:11
And so I think I feel like there's there's a need for just being able to say like let's make really long bets on either domains or people and say like we can't call that money back and we also really don't want to actually know what's going on inside until far far later than most people would be comfortable with.
32:32
and and so you can see like hints of this kind of thing when um so like Xerox Park which of course was in a corporate industry lab setting but my sense is part of the special like secret sauce was that the administrators were very good at kind of protecting the researchers from what was happening outside and they kind of were given a lot like a lot of freedom and a lot of time to kind of play with things.
32:58
I think that there's just a lot of really long-term undirected weird research or just weird researchers that like have like we've never run the experiment of like what is it like to just give people like almost too much freedom.
33:13
Now, conversely, you could say too much freedom like you need to have like a little bit of constraints or something like that to actually kind of get something good out of that.
33:20
But I wonder if we've never really tried to run that experiment.
33:26
And so that's something that I think is really interesting.
33:28
Um, Toronto, just like being able to try really weird long-term things.
33:32
But I would also say I also, now this is maybe this is this is like an overly kind of like straw man consider like concern which is like university settings are overly concerned with like disciplinary boundaries.
33:50
And we were talking like the weird kind of more polymathic stuff like that's where the interesting things are happening.
33:57
But even though people want to do the kind of free form kinds of things, they often have to like still get tender with in their department or whatever it is.
34:04
And so trying to actually run some of these experiments where people can be weird misfits in between disciplinary boundaries, that would be great.
34:10
Um that being said, I I think whatever I'm proposing right now is like almost like too broad.
34:15
I can see also the need for and now I'm just like throwing out idea after idea.
34:21
One of like that's what I'm looking for related to actually going back to like we were like we were talking about like the history of computing earlier.
34:27
I feel like whether it's history of science or history of computing or history of technology more broadly, there is like I feel like I have this sense that if we just stopped publishing new research right now, we would still be able to make a huge number of advances by just recombining some of the stuff that's already come before us and like kind of like like poking around inside the archives and like like the old things.
34:53
Um, and so right there's and there there was uh I can't remember if we if we discussed this last time, but there was there was this information scientist by the name of um Don Swanson in the mid1 1980s and he wrote this paper about undiscovered public knowledge.
35:06
And the idea behind it was like in the vast scientific literature there there might be a paper that says A implies B and there might also be another paper somewhere else uh that says B implies C.
35:17
But because no human can actually read all the literature, even though it might be true that if you combine those two papers together, A might very well imply C, no one knows this.
35:26
And and so he actually, it was very interesting, like he he wasn't content leaving it as a thought experiment.
35:31
He said, "Okay, I'm actually going to try to use computers."
35:32
In that case, it was like the cutting edge computational techniques of the mid1 1980s, which was, I think, like keyword searches in like a medical database.
35:40
But he actually was able to make some advances that got published in medical journals, even though he was just an information scientist.
35:46
information scientist. he didn't have medical background and and of course since then we now have much much more sophisticated techniques and obviously with AI it's kind of overclocked that ability but whether or not it's in searching the scientific literature
35:59
whether or not it's looking in the like old and forgotten kind of paths not taken of scient scientific advances or technological advances there's still so much to be done in just like revisiting the past and I think that's like another thing that is really just incredibly under underappreciated, underfunded as well. So, I feel like
36:20
So, I feel like that's that that's another area as well that could really benefit from something like that. >> Yeah.
36:26
I we're making a documentary through our films division about Bell Labs uh and we're working with the author of the idea factory and uh so he's kind of doing the script and everything.
36:38
And the way I think about it is academia has these kind of constraints that uh developed into a system that creates that hyperbolic discounting right like no we need results here we need to get this grant and one thing feeds the other which is I think one of the reasons why we've seen so much less kind of profound breakthroughs and the reason I'm fascate fascinated by the Bell Labs Xerox Park idea is like Bell Labs gave us Claude Shannon. >> Yeah.
37:16
>> Who gave us information theory and nothing that we are doing right now we would be doing if Claude was not there.
37:24
But he also spent a great deal of his time just >> screwing around like the the the trumpet that shoots fire and the chess game and like so that my sense though is >> that >> Clutchen was still very much an outlier even in Bell Labs like he was and >> he had a very early success and was kind of given almost this like role of like okay you can go off and do those kinds of things.
37:49
of things. Most of the people in Bell Labs were given a great deal of freedom, but it was it was a certain type of freedom and and so and um like I know uh Eric Gileiam has written about some of these kinds of things around like like the ide there was the role of the
38:02
systems engineer within Bell Labs which was >> the people whose kind of job was to like identify the really interesting problems that could then be handed out to the people who were really smart and kind of needed interesting things to think about. Um, and I'm not exactly sure
38:16
Um, and I'm not exactly sure exactly how they operated, but there was this very sophisticated set of mechanisms to kind of channel in an open-ended way the the creativity and the innovation there.
38:28
Um, but in a way that's still kind of cashed out in terms of like things that could be useful for for Bell Labs.
38:34
That being said, I mean, mentioned like Claude Chen as an outlier. one of the other ones.
38:38
So, uh, Richard Hamming, who was also kind of a computer science and I guess also maybe like mathematics.
38:45
Um, he if you look at this might have been like in the 1970s.
38:51
Um, if you looked at the directory of Bell Labs, I believe so he was a he was the chair of the I don't know computer science research department and it turns out there were only two members in that.
39:02
it was him, the chair and I think his secretary and he actually and he talked about how he's like he had worked very hard to kind of construct this mechanism where he had a great deal of flexibility and freedom and you didn't have to worry about bureaucracy.
39:13
Now he also was kind of an outlier but I love that idea of like departments of one that then create this institutional space for you to do just really weird things.
39:24
And um and of course he was probably the outlier in Bell Labs, but I would love that at scale of like departments of one where you can then kind of like build your little bespoke organization within a larger organization.
39:35
>> So So it seems like we're getting back to the organization I asked you to design.
39:40
>> So I I agree by the way and we're we're trying it in a very small way and who we give fellowships to and grants to.
39:47
>> Uh we are very drawn to weird.
39:50
uh we are very drawn to people who don't fit the mold uh because we think that there is a tremendous amount of information there.
40:00
Um but you have to almost treat it like a venture capitalist, right?
40:05
Like for every nine you might get one.
40:08
But we're by the way, we're we're okay with that.
40:10
But wh how I mean like I I was thinking about it on the way in here today and it's like the number one question that's burning in my mind.
40:20
Do you have like a metric or is it an intuitive sense for how do you establish like the good kind of weird we're looking for? Yeah.
40:32
>> From the weird cosplay, you know, the like the the people who like, oh, weird's in now. Okay.
40:38
going to be really weird. >> Yeah.
40:42
I think I mean certain because this there's a lot of like failure modes in building these kinds of organizations and actually so related to this one of the things I I wrote this I wrote an essay several months ago um about the forces of like institutional reversion to the mean which some people have discussed it.
40:58
discussed it. I kind of discussed it in the context of like canalization of like the fact that like all these organizations maybe start weird or they have grand ideas but then often times they end up becoming kind of like shunted into and channeled into much more normal looking things which I normal is great you can do a lot of
41:17
interesting things in traditional academia and corporate industry labs but like a lot of these organizations these nontraditional research organizations start with grand visions but then kind of they might end up becoming sort independent versions of a university department, which is not bad, but maybe not quite the original goal. Or they
41:32
Or they might start as a really strange for-profit research lab, but in a certain amount of time, they are basically just a startup.
41:40
Um, and some of the forces are because and they have they're accountable to their investors or whatever it is.
41:46
And so everything I mean every choice is all kind of defensible, but you kind of have to guard against those kinds of things.
41:54
Actually going back to what you're saying of like the weirdness like there's also there's right some people are like oh I'm going to kind of yeah cosplay kind of like the weirdness but one of the reasons why these organizations sometimes become like much more traditionally academic in
42:09
appearance is because even the people who think that they might want to do weird things they often have kind of in the back of their mind the concern that oh maybe this organization is going to fail or I'm not going to be a fit for it and where where would I go after that? probably back into academia. And so I
42:24
probably back into academia.
42:24
And so I have to make myself look understandable to the world of academia and university departments.
42:30
And so as a result, even if at the institutional level they're trying to do something different, the individuals might try to end up doing more traditional kinds of research.
42:40
And so the I mean one way to potentially do this is like find people who have already like written off academia entirely and like oh I'm just going to like I've kind of I have no interest in this.
42:50
I'm just going to go off and do something weird um or strange or non-traditional and whatever whatever term we want to use.
42:55
Um but it's really hard and I think partly and going back to what I was saying before of like kind of locking in the resources and the structure helps prevent some of that kind of canalization forces.
43:06
But it's very tough because even if you kind of lock in the resources, if the people that you're actually populating these organizations and institutions with are not actually the right fit.
43:21
They're kind of they're they're looking they they they they give off the appearance of weird, but they're not actually doing something that interesting, then right, that'll also kind of force it as well.
43:30
And so it's um I I feel like there's a lot of a lot of failure modes in terms of these kinds of things.
43:38
things. Um I mean one potential thing is to say rather and in addition like alongside thinking long term you say okay this kind of thing can exist for a long term but we'll still actually have like a lifetime where you say okay we're going to it's going to exist for
43:56
10 years 20 years 30 years and then it's done and so that kind of can help inoculate against some sort of I don't know institutional drift or mission like mission shifting So maybe there's kind of something in between where it's like, okay, you have to say we have to think long term. We
44:11
We have to incentivize certain kinds of behavior, but we also recognize that there's an inherent natural lifespan to it.
44:18
And so that kind of can protect against some of those other kinds of forces as well.
44:23
>> Again, I'm I'm trying to get down to your selection criteria >> for the people.
44:29
>> Yeah, for the people because it could be very useful for me with our fellowships and our grants.
44:34
So I would so I I think so there's probably I mean certainly you can definitely like there's there's a fine line sometimes between like weird interesting and weird crazy.
44:44
Um I would say potentially one and and I think people have tried to think about how to incentivize this kind of thing within like even like more traditional like grant funding mechanisms at like the National Science Foundation or NIH which is as long as someone's proposal meets a certain like minimum threshold of quality.
45:02
What you don't necessarily want to do is find the consensus of like oh these are the people that everyone thinks are great and should fund.
45:08
want the high variance where it's like half the people think this idea is terrible and half the people think this is the only thing we should ever think about and fund.
45:16
Those are the people you want cuz I think that's where you're going and you might still have that like high rate of failure, >> but it's still going to be interesting.
45:25
Um, and then going back to kind of like this whole like like finding weird stepping stones and recombining them in unexpected ways.
45:31
That's probably where you're going to find the raw material of ideas that are going to be then used and productively recombined in ways you can't even imagine because they're the things that they're kind of like they're not like oh that's kind of interesting or that's an obvious thing.
45:45
It's these are the things that sound really interesting but half the people think yeah that has no relevance whatsoever or that's not even the the direction we should we should pursue.
45:53
So, I feel like that non-conensus kind of metric could be the way of helping like identify those kinds of things.
46:01
>> You know, I was uh again for the book that I'm writing looking up uh the origin of the term consensus.
46:06
And the actual Latin translates to when people feel together, not think together. >> Oh, like like sense. Okay.
46:19
>> When they feel together.
46:19
And that brings me kind of back to human OS, right?
46:25
Because you were mentioning scientists, right?
46:28
Like what I grew up believing in, you know, the scientific method.
46:31
And you know, Fineman, one of my heroes, no matter how elegant my theory, no matter how much I love it, if the scientific method says it's wrong, it's wrong. Right.
46:44
I love that way of thinking.
46:46
>> Has to like actually engage with reality. >> Exactly. Right.
46:48
The engagement with reality is where I really come down, right?
46:54
Because if you look at people who are really, let's say, weird, the ones that I have seen succeed, greatly succeed, are those where they're in a discipline or they're in an area of study that forces them to engage with reality. Right? And you know, Philip K.
47:17
Dick had that great quote, reality is that which once you stop believing in it doesn't go away, >> right?
47:26
>> And and like so you think of uh I had a guest on who learned a lot from US special forces. >> Okay.
47:33
And one of the things that I absolutely loved about it was the that they the the study group he was part of um banned PowerPoint, banned they wrote everything on chalkboards or whiteboards and they were kind of the epitome of no no consensus got us here.
47:58
We need to think of different ways.
47:58
But as part of our conversation, like I I have a friend who wrote a great uh short piece about Jed McKinna, the non-dual philosopher, and his name is Dan Jeff, and it is he was my gateway drug into Jed McKinna.
48:13
But his piece was basically saying the people who are closest to reality are special forces, er workers, and traders of all things.
48:27
And the way he put it was these are people who either metaphorically face death, the traitor, or actually face death.
48:37
>> And and he was like that's a really great forcing function. >> Yeah.
48:41
>> And and and so I kind of thought like what kind of constraint could you put in to a process to whatever to get people to engage more with reality because again back to science, right? again sort of my temple.
48:58
But when you look at the actual behavior of human scientists, it looks a lot like the movie Mean Girls, right?
49:03
Like Oppenheimer, David Bow came up with hidden variables, right?
49:07
And uh Oppenheimer's overseers in the military had said, "That guy's a communist.
49:13
We don't want any stuff from him."
49:16
don't want any stuff from him." And so Oppenheimer and I can't remember I because I did this research a bit ago whether Oppenheimer said it or it was recorded somewhere where Oppenheimer said to all of his other colleagues if we cannot disprove David's theory we
49:33
must ignore it now like wow >> so yeah I so I would say and that story sounds very unfortunate that being said I mean I wouldn't necessarily say that right like scientists are like mean girls to the exclusion of like and worse than I know I'm being hyper but I would
49:56
say I mean it's >> it is science I mean scientists are humans and irrational imperfect um and that being said like the like scientific process um not necessarily just the like like there's like the scientific method of kind like the very like simple thing you learn in school like that's that's
50:14
one thing like the process of science is like the rigorous means kind of quering the world that I think is a great way albeit imperfect of kind of harnessing our imperfect irrational humanity for actually better understanding of the world. Now right there's many places
50:28
Now right there's many places where it doesn't always work where I there's what is it um like Max Plunk had like the plunks principle kind of like like science proceeds kind like one funeral at a time.
50:38
funeral at a time. people have actually tested that and interrogated and said okay let's look at the ages of the scientists who decided to adopt um and like and adhere to Darwin and like like evolution by natural selection and it turns out um from what I recall it's been a while there is actually no
50:57
correlation with age so it actually turns out that some of the older scientists were just as willing to acknowledge this new theory as the younger scientists and so so I think I mean sometimes that kind of does like that kind of thing does happen and there's the idea like paradigm shifts and like things being overturned. You
51:10
You kind of have to wait for the new generation.
51:13
But I do think that scientists are more willing to actually overturn kinds of things.
51:20
And and of course, I mean, sometimes it's one of these situations where you might talk a great game in the abstract, but when it comes to your own ideas, you might fight tooth and nail.
51:27
Um, that being said, I I I can't remember if we if I told you the story already, but so one of my um professors in uh in graduate school, he told me this great story where he was uh he like went in one day and like gave some lecture uh on some topic and like the next day actually read a paper that invalidated what he had learned the day before.
51:47
So he went in the following day and he said, "Remember what I taught you? It's wrong.
51:51
And if that and if that bothers you, you need to get out of science."
51:54
science." And so like there is the sense and of course that not always adhered to like and sometimes like yeah more in kind of the breach or whatever but that that's ultimately like this idea that right scientific knowledge is constantly in d in draft form and science is less about a body of facts and more about
52:12
this like the process of quering the world I think that's the ideal now of course do we always get to that ideal not always but I'd like to think kind of along the way we're sort of like asmtoically approaching the truth um and >> exactly you are there's many but but it happens and it happens
52:31
unbelievably well at least kind of like in the limit like the fact that like over like if you look like over the past several centuries like we have made unbelievable advances and and that's kind of on top of the fact right that scientists are people too and people are really irrational and kind of suck in many different ways and yet we've still
52:50
been able to make those advances and so um I'm willing to look at it maybe as a little bit more optimistic but you're right there obviously are processes that we can kind of put into place to kind of make it even better and and and ways of thinking about like what should we be optimizing for? what should we actually
53:02
optimizing for? what should we actually be incentivizing because I think that's another thing of like when we think about what are the ways like what are the kinds of things we incentivize in terms of what scientists do that will also affect what we get out of it and so the way I kind of think about this is like you have like this this whole space
53:18
of like these are all the things that science like is valuable like these are all the things that are valuable for science and then you have this little subset of like the things that are valued by scientific academia like the things that get you tenure and that's a small subset of like the big space and we need to actually find ways of
53:34
incentivizing all the other things like I don't know building software building tools connecting different ideas together doing other weird kinds of things that are just as important but far less understandable to the mechanisms of tenure or whatever it is and so right maybe it's creating institutions that kind of incentivize some of those other kinds of things as
53:51
well that can just make science that much more of a successful process um but uh but that being said right we've we've done we've done pretty well so far >> uh you know you bring up Darwin And I just finished Tom Wolf's book uh the the uh basically he's making the claim that it was human language, >> not evolution, that made humans humans. Uh but he I love Tom Wolf cuz he's such
54:15
Uh but he I love Tom Wolf cuz he's such a and he just he's so good at just zinging people.
54:21
zinging people. But the thought as I was listening to you the about older scientists embracing well Darwin's grandfather and his father had advanced different ideas about evolution >> like Arasmus Darwin like there was like right so it was right the idea of evol
54:42
and it's interesting like the idea of evolution itself was kind of this evolutionary thing like it kind of took time to get there and and right like Darwin I was like evolution by the process of natural selection and like it was a very specific almost like algorithmic approach to evolution. And I
54:54
And I think that was kind of that was the key insight.
54:58
And of course, he spent decades like marshalling all this all this data and information and like it was like this very kind of like slow hunch that eventually kind of got there.
55:06
But you're right, it wasn't it didn't come out of >> it didn't come out of nowhere.
55:09
And I think right that is I mean ultimately all of knowledge like it's not it's always this kind of process of recombination whether it's like um uh like the idea of like like everything is a remix as well as like the idea of like science, right?
55:21
and standing on the shoulders of giants and like just kind of having this slow accumulation and and like weeding things out.
55:26
Um there's this great quote by Isaac Azimov where someone wrote a letter to him saying we used to think the earth was flat and we were wrong and then we then we thought the earth was like spherical and like a perfect sphere and we also and like that turned out to be to be wrong.
55:41
So like how can we know anything?
55:42
And and Azimov wrote back saying like if you because and we now know it's like an oblate sphere or whatever it is.
55:48
And he and Azimov wrote back saying if you think that thinking the earth is flat is just as wrong as thinking the earth is a perfect sphere then your view is wronger than both of them put together.
55:57
And so it's kind of like going to like like the asmtoic approach but like we have the processes in place to kind of like slowly but surely kind of get there and like build upon new different things.
56:06
And and sometimes right there's going to be a lot of turmoil and change.
56:08
Um, but it's still building upon multiple different things and over time kind of getting us to these new theories and new understandings and approaches to hopefully a correct view of reality itself. >> Yeah.
56:23
And it is inch by inch, right?
56:23
And I again completely agree.
56:29
>> Um, you might enjoy Wolf's book uh because he is just absolutely the takedown on Darwin in it.
56:37
the man, okay, is really, really funny.
56:42
>> And you know how he wrote, right?
56:42
He invented the new journalism.
56:44
So he he could get away with things that other people can't.
56:48
And it's just really a fun book because making the case for language being the thing that separates us uh from all the other animals is just interesting in and of itself.
56:58
Uh but, you know, he's like, uh, if we apply the scientific method to Darwin's theory, and then he goes, does it meet this criteria? No.
57:07
Does it meet this criteria? No. Does it meet this? And he just keeps going.
57:11
And then, you know, the way he has the text grow in the book. >> No. Oh, so interesting.
57:17
>> No. Oh, so interesting. I mean the the truth is and I think like Darwin was like pretty upfront about this like when he was developing his theory he like the then kind of cutting edge idea of like the way like genetics operated was sort
57:30
of this like mixing and he knew that mixing of traits would not work for selection cuz like you need to kind of have like a certain amount of like discrete quantitative things and and he like recognized like this was like a gap in his theory. Um but he was still like
57:44
Um but he was still like no no no this but it's still worth describing and articulating.
57:48
And of course then yeah you have to have like like mandelian genetics to kind of like be like like fill in kind of the missing piece.
57:54
But but I think that's okay like to have like like we don't and and this is and it's both I think important for science to kind of put forth incomplete things and subject them but it's also >> and almost like it's a good way to operate as a scientist.
58:09
If you get if you put forth the last word, you're not going to get you're not going to get cited because you're just you solved it all.
58:17
You want to have something that people disagree with or argue with or expand upon.
58:21
That's how you get really well cited.
58:22
So So I feel like there's even just like like that's that that's a good way to think about science.
58:26
And I I do think I actually going back to incentives and even like the way we think about publication.
58:30
The fact that right now scientific papers have kind of expanded and gotten more and more complex where it's like not a single experiment or a single idea.
58:36
It's often like a whole bundle of things.
58:38
In some ways, that slows the speed of scientific communication, but also means like you can't just like put forth a thing and then allow it to be tested and and and subjected to to debate and argument.
58:49
And and I feel like right, we might need to incentivize somewhat different times of publication.
58:55
And that being said, I if you think about like the scientific scientific paper, it's what is like a 400y old technology that is also ripe for re-examination.
59:03
I mean, I guess we have PDFs now instead of just print.
59:04
have PDFs now instead of just print. Um that being said it doesn't feel that different and people have a whole bunch of ideas how to think of like rethink publication as well which could potentially incentivize different kinds of scientific output as well >> and you know I was also reading about the republic of letters which led to of
59:22
course the creation of the royal society >> Henry Oldenberg he was like one of he was like the secretary and kind of like like sort of like the hub and like the node like central node of all the people writing together and >> and I was very taken by the deep dive on the republic of letters because I knew about it but I didn't know how varied
59:42
the participants were like Katherine the great was in the republic of letters Frederick the great also with Voltater all of these people and I was just like it got me back to see diversity that because what would happen is they would send the letters privately they would be read and they would only be forwarded if the uh person who received the letter
1:00:08
found something interesting in that letter but maybe had a different view or maybe added to that view and then that would get copied and forwarded and it's kind of like I was actually thinking about you when I was reading about this because >> I I'm like that's Sam's like, you know, way of just cludging it up but having these really great things come out of it. Yeah. Yeah.
1:00:33
>> And then of course the the institutional capture of the Royal Society, right?
1:00:40
Like it that was the other part I didn't really think about.
1:00:43
It kind of killed the Republic of Letters. >> That's interesting.
1:00:46
Well, and I know and my sense is like the Royal Society, it also had a diver like a diverse number of people, but a lot of them were just kind of the the moneymen where it was like, okay, we need to kind of bring them in.
1:00:58
They're not really doing like quality science, but they We need the money.
1:01:04
money. But I also just like the right there was both in early royal society as well as kind of the republic letters there was this kind of democratizing feature because I mean certainly scientists was not really a job at this time >> right >> it was a natural philosopher >> natural philosopher but a lot of them like they were not really doing it as their main job they were kind of doing it as other things um because it didn't
1:01:25
really exist or make sense it it was a different sort of category um but >> it was also just like >> there was I don't know if was like I don't know if pre-paradigmatic is kind of the right term for it but it was people just need they like one of the most important things and like if you look at like the early like um like uh like proceedings of the Royal Society or communications uh it was just like
1:01:49
people saying this is an interesting thing that I noticed or I did this weird thing and I'm not really sure how it makes sense and they kind of just throw it out there and I love that very kind of early stage in a field where people are just collecting bits of knowledge and bits of information or like facts or saying here's something that doesn't really fit and I want to kind of just share it with other people because maybe
1:02:11
they'll have a different different kind of insider approach and I I think about this and certainly in like the tech world you have like collecting bugs and glitches often times they are actually the precondition for actually better understanding a system of like finding that gap like and reducing the gap between how you think the system operates and how it actually does operate. um you need the glitches and
1:02:27
um you need the glitches and the bugs to kind of narrow that gap.
1:02:29
And I feel like when it comes to science, that's the same thing.
1:02:35
Like you need to find all that kind of weird stuff that doesn't make sense.
1:02:39
And in those early Royal Society days, that's what they were doing.
1:02:43
They were just like, "Oh, I found I heard this weird thing or I tried this thing and I'm not really sure what it adds up to, but it's worth sharing with everyone else."
1:02:49
And and I kind of feel like we've we've lost a little bit of that.
1:02:53
And yeah, there's something to be said for for that kind of just like sharing things that don't add up and so therefore merit further consideration, >> you know.
1:03:03
Um, we have our own uh AI setup hardware and I was going to ask you you because I also very much agree with your idea that there's just a gold mine of information in the past.
1:03:18
So, if I were to come to you and say, "Okay, Sam, I'm I'm going to try a project over here.
1:03:25
We're going to let the AI loose and we're going to let our fellows loose and all of that."
1:03:29
Like, what would you tell me about how I should populate that model and fine-tune it?
1:03:35
Like, what I'm looking for are you should really look at, you know, the writing on computers in 1977.
1:03:46
you should really look at, you know, the social conditions that led doctors to ignore Seml Weiss's advice.
1:03:54
What what what periods would you find most fertile most fertile?
1:03:56
Um, and yeah, I would say and any time where there's like the grudging after the fact, like after the fact acknowledgement of like, oh yeah, there was something really interesting here, then you kind of want to go like several years earlier and see, okay, when there were like those really intense debates, I feel like that's that's something there.
1:04:20
that's that's something there. But I also so one other thing and I'm this is a little bit different than what you're asking but I actually think and with AI this is even more possible now than ever is the extent to which we can think in terms of like jargon barriers because like often times not only are can
1:04:40
something be useful when you kind of combine it with something else that maybe is in a different sub field but often times people don't even realize that they're talking about the same kinds of things because of >> because ofar And so I remember this uh when I was when I was doing my postto and I was
1:04:57
doing things like network science there was this mailing list that I was part of and it had lots of people from lots of different domains and fields and I feel like every week or so there would be someone saying like what's a really good metric to measure the following thing and invariably someone would email back
1:05:13
and say oh this has been known for like 30 years in sociology and it was just like it was unbelievable to see and I I felt I actually experienced this once like in my uh my like for myself in my own research where I was trying to find some sort of metric for I don't know clustering data
1:05:27
couldn't figure it out I was working with a friend of mine and we were like we were going to just kind of create our own we knew it wasn't going to be great and then we said let's just talk to the statistician down the hall and of course he immediately told us what we need to look at and and now AI can kind of help
1:05:39
overcome those jargon barriers but I still feel like that you kind of really have and and maybe I'm wrong about this but there probably still is some work to be done for productively overcoming those jargon barriers and like really saying okay how do we actually translate one idea to another so such that like some mathematical model is not
1:05:57
reinvented eight or 10 times throughout like a hundred years which these are the kind of things that have actually happened and so being able to find ways to like short circuit those kinds of things and so it's almost like at the sort of like semantic or kind of conceptual level like what are these concepts the same how do we kind of make
1:06:15
sure that even though the jargon is very different how do we kind of recombine these kinds of things um so I I would say that's another thing like another approach that needs to be focused on because otherwise even if there's all this really interesting stuff in the literature. It's not even just like how
1:06:29
It's not even just like how do we kind of get people to have an open mind.
1:06:34
It's how do we get people to even be aware that this is something they should be considering. >> Yeah.
1:06:40
And um again to your earlier comment that like it's pretty amazing that a lot of the advances that we enjoy today are new are relatively new.
1:06:50
So would you concentrate on literature from a certain period?
1:06:57
I love the idea of something that's obvious afterwards and really contentious before.
1:07:04
really contentious before. That's a I mean I'm not sure and there might be like certain time periods that are better than others for so like for example like earlier in the earlier days of computing when people were thinking about not necessarily just like like technical abilities but more okay like
1:07:22
thinking about computing in the sense of like how do we kind of use it for the following use cases or like children's education for example whatever it is and it had kind of a broader sense that being said depending on the field sometimes s there's really something to be said for going really far back. And
1:07:36
And so so my um my so my father he's a he's a retired dermatologist.
1:07:41
He this is many many years ago.
1:07:43
Um he was on the um the platform incentive where it's like like they kind of like provide like challenges and people kind of like try to find and often like trying to find um people who are in somewhat different fields that can maybe come up with something really interesting and relevant.
1:07:57
He saw there was some challenge for I think someone try like it was to create a non-invasive biioarker for the progression of ALS like the neurogenerative disease and my father in looking into that I think he found it was it was probably over a hundred years old.
1:08:18
It was the one of I think it was like the article that first described ALS.
1:08:23
It mentioned almost in passing the idea that and I'm have I might have gotten this wrong.
1:08:29
I'm reaching back quite quite a ways but but it was um I think it was the idea that they um that the patients didn't get bed sores and it was like oh they kind of just mentioned it and my father realized maybe there could actually be some sort of biioarker around skin elasticity where you could actually look at the pattern of the like the uh of like the progression of the disease by measuring skin elasticity.
1:08:50
so it' be noninvasive and kind of leaned into like his dermatological expertise, but it was from this really old paper that was just like here's like this weird like this new medical disease and we kind of have to think about it and then I kind of mentioned this one thing in passing.
1:09:03
And so I'm willing to almost say like let's like I want to keep it all. I want to keep it all.
1:09:08
I want to search through it all and and obviously it's kind of overwhelming but that's one of the beautiful things about these massive large language models is you kind of don't have to choose.
1:09:18
And and I think right now like one of the things we need to really just focus on is preserving all this kind of information and digitizing it.
1:09:26
And I feel like like or like like the Internet Archive and similar kinds of organizations that are just trying to kind of make sure that this information is preserved, digitized, accessible, they are doing really important work because that is going to be sort of the grist and the raw material and kind of the precondition for all these kinds of advances.
1:09:45
And and and right now like great if if storage and and like and hard drive space is basically infinite keep it all like keep it all and and and find some way of actually making meaning out of it. Yeah, I agree.
1:09:59
And I was shocked to learn uh that say for example, William James, >> the majority of his writings are not digitized and we actually have a project going on where we are going up to Boston or we have people up there doing it for us.
1:10:20
His archives like most of them are paper and we are digitizing them.
1:10:24
And the interesting thing about that is it's a massive project and I'm talking about one thinker, William James, right?
1:10:34
And and so I'm a huge proponent of keeping it all, right?
1:10:41
Because you know, I kind of think when the library at Alexandria burned, like how much knowledge did we lose? >> Right. Right.
1:10:52
So like that's why like the um uh like the scroll prize and like the visious project of like these like a movie about that actually. >> Oh that's amazing.
1:10:59
Yeah cuz like right like that kind of work like and well first of all the actual like the actual work of that was unbelievably exciting and like just amazing to use kind of these computational advances.
1:11:09
But I feel like more broadly just the the act of digitizing and preserving these kinds of things.
1:11:15
It might not be the most glamorous, but it is foundational and kind of like the precondition for all these other kinds of things.
1:11:23
And um and you think and you look back at like the um like the early humanists like in kind of like the Renaissance era.
1:11:31
I mean, part of what they were doing was like I thinking about what is human, but a lot of it was also just trying to rediscover and find some of the best ideas of like a thousand years ago or like a thousand years before them of like ancient Greek writers and ancient Roman writers because they wanted to learn and rediscover from these like previous thinkers.
1:11:52
And I think right we need to kind of do that kind of thing at scale and like find find like the best of like the best ideas that are out there from whatever time period wherever they are.
1:12:05
And part of that is just simply preserving or rediscovering or finding these kind of things or making them accessible. >> Yeah.
1:12:10
And humanism is uh interesting to me.
1:12:13
Uh it plays a part in the fictional novel that I'm writing.
1:12:16
Um, and I learned so much about how it was possible for the humanist during the Renaissance to emerge.
1:12:25
And and one of the things that I hadn't thought about was that one of the reasons why Italy in particular um and certain parts of Germany uh were so fertile was because they had no central governing authority. >> Oh, interesting.
1:12:43
There was no king with absolute power.
1:12:46
The Germany was not united.
1:12:49
It was a confederacy of duchies.
1:12:52
Same with Italy with the city states.
1:12:52
So it was very much nonentralized.
1:13:00
And I think as I was reading about it more and more, it was that lack of centralization that contributed to the explosion of new ideas.
1:13:10
there wasn't a central authority to say no, right? You can't do that.
1:13:16
And it bleeds over into the printing press.
1:13:20
Uh there's a great book about the history of money.
1:13:22
Uh it's an Irish author and he's very funny.
1:13:25
And so he presents Gutenberg as kind of a grifter and but you know how he came up with the idea because he grew up in a wine region, right?
1:13:37
Was very familiar with the wine presses. He was a jeweler.
1:13:40
Um, but he really got, hey, what if I use those presses for this and the the >> it was it was like a bundle of technologies.
1:13:52
It wasn't just a single thing.
1:13:54
>> To your point to your point, it was a bundle and he just happened to be in the region where they were all operating.
1:14:01
But the the the further part of my analysis is humanism basically was the first I think of Raphael's portrait of a young man.
1:14:11
It's the single greatest piece of art that is still missing.
1:14:14
It was looted by the Nazis.
1:14:16
And Dur also did the first uh self-portrait in which he created himself his portrait like they had reserved only for Christ uh prior to that.
1:14:27
And so humanism has this kind of in-your-face to authority.
1:14:30
In other words, the art of the time was the like the portrait of a young man by Raphael.
1:14:38
It's a self-portrait, but he's staring at you and he's like what what he's implying is I don't need your uh permission.
1:14:46
I don't need your imperator.
1:14:50
I am a human and I can figure this out.
1:14:53
It's one of the reasons I love humanism, right?
1:14:55
right? But the decentralized nature was something I hadn't thought a lot about and because for example China had the imperial throne and they suppressed a great number of technologies that they came up with first right and imagine if there wasn't this s by the way Gutenberg
1:15:18
got his way into the church because again he was an entrepreneur too and he was looking and saying, you know, one of the biggest businesses for the church are letters of indulgence, which essentially was your get out of hell free card, right? You would give money
1:15:33
You would give money to the church.
1:15:36
They would have the scribes do these beautiful letters of indulgence saying, "No, Sam is getting into heaven.
1:15:43
He's getting into heaven."
1:15:45
He might have made a rather significant contribution to us, but >> that's just kind of by the buy. >> That's by the by.
1:15:51
And so what did Gutenberg do?
1:15:52
He went to his local bishop and said, "I got to believe that the demand for letters of indulgence is way up here and that your ability to fulfill that demand is way down here."
1:16:05
And the bishop are like, "Yeah."
1:16:05
And Gutenberg goes, "I have the answer for you."
1:16:08
And and sure enough, the church embraced it for that reason.
1:16:12
And then the pope of the time, I think it was innocent.
1:16:16
And my joke about the innocent popes are they were anything but innocent.
1:16:23
um was very very vain and he would uh in during those times he would give readings from the Bible to congregations and so Gutenberg published a Bible with huge text so that he wouldn't have to wear his glasses and he was smitten right he was instantly smitten but but the point about the idea of decentralization it got me thinking a lot differently about how a modern organization could be formed.
1:16:55
Is that a important part of your thinking on this?
1:16:59
>> I mean, I would say I mean, I like I I'm partial to decentralization, especially kind of in the face of like managing and handling complexity of like having like competition, having that kind of like that going back to like the peace meal engineering kind of like that sort of like slowly but surely experiment experimentational kind of approach.
1:17:20
I think that's really important because like when when you are confronted with a complex system and you don't really know the best thing to do, you just try a lot of different things.
1:17:28
And so decentralization is really good for that kind of thing.
1:17:30
Um, and in some ways actually going back to like organizational structures like it like if you can get like the department of one or two people that's decentralized and it allows you to then kind of have this like it you have the kind of legible structure to do your thing but it's distinct enough from everyone else that then you can kind of do things maybe a little bit differently and kind of having a lot of those could be could work really well.
1:17:56
But I and but I I wonder if cuz I I've thought about cuz there a number of people who like consider themselves like independent researchers.
1:18:03
>> Of course it's as an independent researcher it's harder to get funding and things like that.
1:18:08
And so there are like going back to like kind of like the theory of the firm there are like returns to scale and kind of doing everything together.
1:18:15
But there might be ways of in kind of a more modern way kind of having things that kind of re like that recombine in a sort of looser way where you can have maybe a group of independent researchers that work with like some like one administrative person who kind of helps them get funding but then kind of allows them to all do their own thing.
1:18:35
Or there's actually another there's a um a research organization called Inc and Switch which they they do things related to like um the like like computational tools for thought and human computer interaction and ideas related to kind of like programming um as well as many other things.
1:18:50
as well as many other things. And one of the models that they adhere to that they kind of talked they've talked about is this like Hollywood studio model where so in the same way that when you make a movie it's not all one large company
1:19:02
it's like I mean some there's companies but it's people like the teams often are assembled for that project they work on those things and then everyone goes off and works on another movie or or other kinds of things right and and I feel like and and so incin switch does that
1:19:16
they they have some people who are maybe a little bit more longterm but one it's also just a great way of getting very highc caliber content or high-c caliber talent um in the tech world where it's like they might not be able to get them for a long term but they're they have 3
1:19:29
to 6 months free in between like a company a corporate exit or they left something or they're thinking of doing something else and then they they'll come and kind of join a little project and then they have the long-term people kind of helping set the longer like more long-term vision of the organization. Uh
1:19:40
Uh and so I think like having that ability for researchers to kind of come together for certain kinds of things in this kind of distributed way is really interesting.
1:19:51
Now that being said, it can work better in certain kinds of research that maybe is a little bit faster.
1:19:55
If it's like a longer term kind of thing, then maybe it's harder to kind of have that sort of swarm kind of approach.
1:20:01
But I definitely think there's something to be said for that kind of like decentralized approach.
1:20:06
Uh and I think it's yeah, it could be really powerful. >> Yeah.
1:20:09
Kind of back to the fictional book that I'm writing.
1:20:11
We're we're trying the Hollywood model.
1:20:13
I actually have a writer room with both humans who are great writers.
1:20:17
I'm lucky that we have infinite books and we have a bunch of great writers and editors.
1:20:21
Uh but we're putting AIs in there as well with different types of personalities, etc.
1:20:29
Um and uh Jimmy Sony, our editor and chief and CEO of Infinite Books, he he he was skeptical about doing a writer room because he's mostly non-fiction.
1:20:40
And after the first one, he's like, I think I'm going to start doing these for my non-fiction books. >> Interesting.
1:20:48
>> Because what happens is you throw the world that you're building out there and it's really kind of magical. >> Yeah.
1:20:55
>> Because like for example, in my book is is a thriller and it covers a long period in history, right?
1:21:02
Uh it starts in World War I and it ends in 2027 or World War II, excuse me, and it ends in 2027.
1:21:09
It's a hunt uh that that goes on.
1:21:14
The the villains are very villainy, but the people hunting them are very talented.
1:21:19
Um and anyway, uh in our first writer room, Jimmy was listening and he goes, "You know what's interesting about all the characters and some of the uh real life per people you're putting in that?" And I went, "No."
1:21:32
And he goes, "They were all orphans."
1:21:37
And I went, "I never thought of that."
1:21:41
And so it opened this incredibly rich vein of looking into like orphans, what drives them?
1:21:49
Are they bridgeuers or are they wall builders?
1:21:52
And so I went down this and it actually affected the plot. >> Oh, wow.
1:21:56
and and so I I'm a huge fan of the writer room approach for for this particular purpose, but we why they're so fun is because again back to the I I I would have never thought of that.
1:22:16
Um, but also from the point of view of just kind of like AB testing with smart people, like does does this this sound like something our villain would say?
1:22:27
And and there's a lot of controversy and like no, he would never say that because he's this way to but it really helps me as the primary author >> to whittle it down to Yeah, he he would say that.
1:22:40
The other cool thing about writing fiction that I had heard from fiction writers but never experienced is when you get to know a character really really well they start writing themselves.
1:22:55
>> It's the weirdest I've heard people in the world.
1:22:59
>> It's like I was writing what the villain and I looked at it I'm like >> I would have never thought of that.
1:23:04
So you kind of get embodied >> there's almost this like emergence of Yeah.
1:23:11
Oh, that's that's so interesting.
1:23:12
>> Um, so I I definitely am a big fan of trying a lot of different models for o old ways of doing things, right?
1:23:19
Where like the single author versus the writer room.
1:23:24
It works very well for TV and for movies and like I'm a huge fan of Curb Your Enthusiasm and you know his his entire process is they they just write outlines, >> right?
1:23:36
And then and then a lot of things happen and then yeah they try many different things. >> Yeah.
1:23:41
>> Um so anyway I agree that experimentation see what works see what you can learn from it.
1:23:47
Now of course not all of it's going to work and ultimately it's going to be my name on the book.
1:23:51
So um what what right now are you obsessed with?
1:23:58
Because I'm always interested in what is obsessing you.
1:24:01
Um this is I think we I believe we spoke about this last time but it shows that I guess my obsession is still lasting which is uh so the um we talked about the company Maxis.
1:24:11
It was like the studio that um developed Sim City and Sims and Sim Life.
1:24:16
Sim City and Sims and Sim Life. And it was this weird moment in the um like in in like the I don't know early to mid 1990s when it was kind of this like intersection of like gaming and simulation and complex systems and all these other interdisiplinary science
1:24:34
approaches and they just did all these weird things and then the company it I think it took a lot of investment on and then eventually went public and then kind of was not able to sustain that and then eventually got acquired by Electronic Arts and um and now does not exist as as a studio any longer. And so
1:24:47
And so it's kind of had this like kind of crash and burn kind of thing.
1:24:51
Maybe not quite crash and burn, but an end of an era, we'll say, >> right?
1:24:55
>> But I've been just I'm still preoccupied with like what what is still kind of like perennial and valuable about that like that kind of a mental approach to this kind of clashing of different things.
1:25:07
And can we actually like is it possible to like reinvigorate a Maxis 2. 0 or whatever it is?
1:25:12
And so, um, because I like making lists, I've currently been like working and, um, like working on a list of more modern equivalent like games or simulation toys or these kind of like softwarebased miniature worlds that you can kind of play with cuz there are a lot of these still around.
1:25:31
But I think people need to recognize like, yeah, this is I don't know if it's a genre, but it's a thing that should be a genre.
1:25:37
We need more of these kinds of things.
1:25:38
these kinds of things. But I've also just been taken with the fact and maybe this is also just more broadly like when how I think about like simulation like because simulation like there's high fidelity simulation of like predicting the weather and and that that's very
1:25:52
important and powerful and useful um and it's valuable for prediction but there's also something to be said for these small models that are toys but give you a great deal of insight into just how a complex model works and they are so valuable like giving you a certain set of like intuitive hooks or leading you
1:26:15
to learn further about urban dynamics or whatever it is and um and actually so I I I've actually been um been teaching this this course at uh the university in Cleveland Case Western um about the the art and science of decision-making and it's it's this seminar course and we kind of talk about mental models and
1:26:30
complex systems and and like nonlinearity and feedback and all these different things and at one point one of the things I have my students do is I um I have them play an emulated version of um Sim City 2000 that's like available on the internet archive and >> my daughter my daughters were crazy. That was like that was that was my
1:26:48
That was like that was that was my childhood. I love that game.
1:26:49
And and it's not because like Sim City 2000 is like has this great degree of veric similitude, but the thing is >> it's this complex systems model that's just complex enough to have things that like b like they bite back in unexpected ways and >> and you have to make a huge huge amount of decisions.
1:27:09
You have to kind of play with these and and it's just it's a lot of fun.
1:27:13
Like some students get it right away and play with it.
1:27:14
Other ones kind of crash and burn and that's fine too.
1:27:17
But the whole point is like just kind of actually come to grips with a complex system.
1:27:22
And I just want there to be more of these kinds of things because those kind of simulation tool toys are just they're so much fun and they're they're so wonderful and I want there to be more of them for basically every domain of like complex knowledge out there.
1:27:34
So that's still I mean I think we talked about it last time, but I'm just going to keep on talking about it because I I find it so fascinating.
1:27:42
>> Well, I'm also a huge fan of incilica sims, right?
1:27:45
sims, right? like um you you can put together huge audiences for example and have them read your work or listen to your music or watch your movie and you get insights that you're not expecting right like oh I wouldn't think that that kind of ter like we started by building ocean profiles from the big five uh but
1:28:08
then we refined them down and so we can create huge populations depending on the media that we're trying to test And I gotta say that we've seen some like really interesting feedback that I would have never guessed like from you know the anxious processor is one of the names of one of the ones that we have in there. Um, so I'm a huge believer in I
1:28:29
Um, so I'm a huge believer in I mean that was the first book I wrote, Invest Like the Best, was how you could clone your favorite money manager by taking all of the stocks in his or her portfolio, paying no attention to what they said. >> Yeah. Yeah.
1:28:47
>> Paying all the attention to what they did, i. e.
1:28:49
what they bought, >> right?
1:28:51
and and then you could build a rule-based factor-based way of coming up with portfolios with those exact characteristics.
1:29:01
So I I definitely and again that's a temporal thing as well, right?
1:29:03
Like the only reason I was able to do that was I was lucky enough to be born in 1960, right?
1:29:11
If Ben Graham had all those computers, he would have done all that stuff and and and I would have never been able to write what works on Wall Street.
1:29:19
I would have never been able to do that.
1:29:21
But because I was coming of age when we were getting these extensive data sets and the computer power was fast enough, I just got lucky. >> Right. >> Yeah.
1:29:33
>> So, so simulations, what what other lists right now are are really occupying your >> another list?
1:29:38
I mean one see so I mean I guess this list I haven't updated this that recently but there I started creating a list of um sports teams named after technologies cuz of course like there's sports named name named after like like things from history and animals but like there needs to be more named after technologies but it turns out there actually are a non-trivial number.
1:30:04
I mean, like you have like in like the Jets and the Pistons and the Spurs and the Rockets.
1:30:09
And then of course once you get into like minor leagues, there's a whole bunch.
1:30:11
You have like I think there's there's um I don't even this might even just be like a high school team.
1:30:16
There's like something called like the I think I found a team called the Spark Plugs.
1:30:19
Um it turns out there's a ton of soccer teams named I think Dynamo.
1:30:23
Um uh then there's I think one named after like some sort of bicycle that has like the big wheel and the small wheel.
1:30:30
There's and I just love this idea that at least in certain times like technology is such a part of the culture that people actually name their sports teams after them.
1:30:40
So I find that interesting.
1:30:41
Another weird list is it turns out there is also a very large number of companies named after things from like Lord of the Rings and like the Tolken world and and of course a lot of them are kind of connected to kind of like the I think like the extended kind of like Peter Teal world because he's like he and his people are very interested in kind of Tolken.
1:30:58
That being said, and maybe these people, maybe these companies are all connected to that, but like most of them are sort of like the good guy kind of related Tolken stuff. >> Yeah.
1:31:08
>> But I've increasing I think I found a company named Mordor.
1:31:10
There was one called Sauron and like it's a very interesting branding choice. Um but that that exists.
1:31:18
that exists. Um but yeah then I've also and another thing I've been thinking about this is not quite a list but I think also just kind of like a framing um related to some of the things we're talking about kind of like the history of computing and like the people's computer company is um I was involved in this group that made this resonant computing manifesto and the idea behind
1:31:35
it is in many cases when you're engaging with technology um and certain kind of computing things the the computing experience kind of leaves you drained or you feel really bad or like this is not something you want to like you really enjoy or want to be a part But there are and this has been true throughout computing history those experiences that are more resonant that actually leave you enriched. And the
1:31:56
And the question becomes how can we kind of try to uh incentivize or articulate kind of things that are more likely to kind of leave you enriched and kind of this more resonant computing kind of experience.
1:32:10
And so, um, and certainly now with AI, there's the possibility for both like personalizing things in very bad ways, but also personalizing things in very good ways and making things that are kind of more pro-social kinds of experiences.
1:32:21
Um, the way I kind of think about this is that and obviously you want kind of like human scale sort of experiences or things that kind of privilege the human even in the computing experience.
1:32:30
computing experience. But um there was the there was this great television show Halt and Catchfire about kind of it's a fantastic show and like I think it's like in the first episode one of the characters has this quote where they say like the computer's not the thing it's the thing that gets you to the thing and I feel like >> often times we forget that we just we
1:32:50
get obsessed with things that are technically sweet or we're not doing we're not thinking about what is the goal with comput like the computing like computing are these technologies that should make our lives better and more
1:33:04
enriched and more resonant and how do we make sure that we make sure computers are the thing that gets us to the thing and so that's another that's another topic that I've been very obsessed with. >> Yeah, I'm I'm interested in the new
1:33:15
>> Yeah, I'm I'm interested in the new educational models like what what is drawing you there and saying wow this could be really cool.
1:33:24
>> So you mean that space? >> Yeah.
1:33:25
So often times the the thing that draws me to make a list is not necessarily a very clear thesis or idea.
1:33:36
It's more something interesting is happening here and it's worthwhile like keeping track of.
1:33:42
I kind of I I think I described this once in maybe some essay I wrote about I kind of call it like like the lenan instinct.
1:33:47
it like like the lenan instinct. So you have like Lanaeus like tax like taxonomizing like that like there's just this like >> I'm not doing like very sophisticated taxonomies but like especially early on in science and we're going back to like natural philosophy stuff as well the precondition for understanding the world whether it's collecting glitches or
1:34:07
things is just finding things that all kind of seem related and worth keeping track of and I feel like that's a kind of like the len lenan instinct of like whether it's weird things in computing industry or right like weird like companies or sports teams with interesting names and kind of some theme like I just think there's something there and I feel like with when it comes
1:34:27
to the educational models right I I don't necessarily going back to what I was saying what we were saying before I don't feel the need for like throwing everything away but I do feel like we're in this interesting moment where people are trying new things but in a way that it's not quite one-offs anymore And even just the act of the act of list making for me kind of gives me a sense okay
1:34:51
there is a larger space but I also would like to think that maybe sometimes those lists will also allow other people who are playing in that space to realize they are not alone like they're doing things and maybe there can be something to be learned by connecting these different approaches and so I uh yeah so I often times the list making is like the precondition for getting a sense of what's going on. It's more just like
1:35:13
It's more just like there's something happening and I and I want to just at least chronicle it because it's interesting.
1:35:18
But in terms of like do I have a larger theme?
1:35:21
No, it's it's really just that that that Lenan instinct.
1:35:26
>> But uh so on on that topic like what is a recent example of something where you've been keeping these lists of very desperate items that you're seeing emerge from the like you're having your Eureka moment.
1:35:41
Oh, that's why all these things work together.
1:35:44
So, the overedge catalog, which is like the one about like nontraditional research organizations, that one, that one maybe arose when I had a little bit more kind of theory of what was happening there.
1:35:57
Um, but it was still just a matter of okay, there are interesting things happening and it was more I just wanted there to be more.
1:36:02
And so that act was so that act was even it was less about eventually finding a theory and more about trying to make people realize that there needs to be more happening here.
1:36:16
And so it's like okay like like if there's enough happening or or maybe like not like if the list is too short like people go out there and actually expand the list like make more things that can go onto that list.
1:36:27
But I would say I mean in terms of the educational stuff there's glimmers there of that something at the intersection of fellowships and residencies or like and people people talk about like the unschooling movement and like like the recurse center which is kind of like a >> retreat for programmers.
1:36:50
Um they they talk a lot about the unschooling movement.
1:36:54
I feel like these like creating informal or we'll say unstructured spaces to allow and the thing I would say I wouldn't say it's unstructured because there actually I think and I and I think they've actually talked about this like there is a lot of structure or structure available but we'll say non-traditional kinds of environments.
1:37:12
There is a growth there for like people like creating like collections of people for these kinds of things.
1:37:16
Um but I don't I'm still not sure what it adds up to.
1:37:21
Um, then again, maybe maybe I'm just not good at figuring out what what these things add up to and I just have that lenane instinct of like I just want I want I want there to be more lists and I I can leave the sort of like paradigm making to other people.
1:37:33
I'll just be the list maker.
1:37:38
>> When have you just to finish on lists?
1:37:41
um what was the oddest compulsion to start a list on like that you know friends, colleagues, family are like Sam what's going on here.
1:37:57
>> I mean definitely the sports teams named after technologies that one's like a weird that one I don't even know where that came from.
1:38:03
I was just like I mean it was almost one of these kinds of things where like in the same way that people in like the progress movement were like we need to find ways of like valorizing innovation.
1:38:10
I was like this is another weird way of valorizing technological advancement and it seems like we're not starting from scratch.
1:38:18
There's actually a lot of technologies that have been used as names for sports teams.
1:38:22
Um, and it was also one of these things where in the act of creating it and then sharing it, uh, and then sharing it publicly, I then discovered that there were many, many gaps in my knowledge and like certain areas of like sports that I was just like unfamiliar with.
1:38:35
Um, and then people kind of gave me even even more examples.
1:38:37
And that was definitely a weird one.
1:38:39
But, uh, I'm trying to think of even an even weirder one.
1:38:43
Um, oh, there was this list.
1:38:43
This was done actually I wrote this for a I think it's like a now defunct like science humor magazine but it was originally I I have no idea how this started but it was I found a non-trivial number of like anatomical terms that sound like things you could visit on a a vacation.
1:39:08
So like the eyelets of langanger hands or like like like and it it was a very weird list but that one that was a lot of fun to come up with as well. >> I love it. So what's next for you?
1:39:22
>> What are you working on now?
1:39:23
>> What am I working on now?
1:39:23
Um I mean I'm still thinking a lot about like the history of computing and like what can be done with with that.
1:39:30
I I still think there's a space in the tech world where it's almost like there's a need for this kind of translation where it's not necessarily like historical scholarship of computing because I feel like there's a lot of people doing that very very well.
1:39:44
Um but there's there's a role for like bridge building of saying like how can we kind of get people who are already in the tech world more excited about actually engaging in the history of computing.
1:39:57
um which can be as simple as like I don't know reading old computer magazines on the internet archive or actually like I don't know playing with really old computers and hardware and software.
1:40:06
computers and hardware and software. I feel like that's something also that's worth trying to explore because yeah, I feel like sometimes we've kind of we too quickly narrow the space of computing possibilities and then kind of forget all the other weird paths we can
1:40:24
take whether it's like user interfaces or hardware or software whatever it is and it's worth revisiting and so yeah there just needs to be a mechanism for for that and that's definitely that I that it's definitely one thing that I'm kind of constantly struck by and I have no idea what it'll end up. I mean, it
1:40:37
I mean, it could be it could be as simple as like maybe there just needs to be like like in the same way that like Buckminister Fuller would go around and give these like public lectures on crazy ideas, there needs to be more of that around the history of computing in the tech world. I don't know.
1:40:50
But those are the kind of things I like thinking about. >> Yeah.
1:40:53
And um as I was listening to you uh as one who is an early adopter of all technology, so I'm 65, right?
1:41:00
I, you know, on Twitter they have the but are you this old?
1:41:05
And they, you know, they show like Windows 95.
1:41:06
I'm like, I'm way older than that.
1:41:10
Um, and and I I got to thinking about that and the the experience that I had in 1980, right, when I was trying to uh have the computer calculate a black Scholes implied volatility for me and it took five minutes.
1:41:32
But at the time, I'm a big journal keeper, so I was rereading some of those journals.
1:41:37
back then I was like I can't believe that it can do it this fast. >> That's amazing. I love that. Right.
1:41:44
And like we've like forgotten, right? Like that like Yeah.
1:41:48
We and and that's and I would say that's another interesting lesson of just like understanding like technological history which is humans are really good at adapting. Yes.
1:41:56
Which >> is both >> very powerful because it allows us to handle lots and lots of change but leads us to kind of almost like overwrite our memories of how things used to be.
1:42:06
And and I and I feel like sometimes yeah things are lost when we kind of like yeah forget how it was or kind of understanding yeah maybe maybe some of maybe maintaining some of that friction could be useful sometimes it probably was not and like that's fine.
1:42:20
Um but uh yeah but I but I think that uh yeah like just revisiting some of those experiences can be at least uh very powerful for like understanding >> and that's where I was delighted that I was such a journal keeper because we do You would definitely not remember that.
1:42:39
>> No, I would absolutely not.
1:42:39
And we do overwrite our memories.
1:42:42
I I have a I have >> nearly 50 years of proof.
1:42:45
I started when I was a teenager with these uh journals.
1:42:50
And um it's very interesting to me because because of them I I learn, oh, I didn't think that at all.
1:43:01
And and it's it's really helpful because it teaches more broadly than just that specific example.
1:43:07
And and I think that we overwrite another part of human OS, right?
1:43:12
We overwrite our memories to make them consistent with what we believe now.
1:43:20
And um that that can be a challenge.
1:43:20
Um a and or it can be like when you go back and have the ability to go back, you can see the chain of how you came to believe what you believe now, which is really interesting.
1:43:35
So I'm all in favor of uh your your notion of let's keep everything.
1:43:42
Let's explore everything.
1:43:42
Uh because you know there are a lot of connections that we just don't intuit it, right?
1:43:50
like we we see in a very limited part of the electromagnetic spectrum.
1:43:56
We like our our senses are fabulous, but they're very very limited. >> Yeah.
1:44:03
>> And so that's why I'm such a big fan of AI because it can in fact look into all of those. >> Yeah.
1:44:10
>> And and say, "Hey, look at how this, this, and that way over there combined to make something like really cool and interesting." >> I love that.
1:44:20
Well, Sam, I could talk to you forever.
1:44:23
I know you have another engagement here in the city that you have to get to.
1:44:26
Um, you do remember, I hope, where we make you emperor of the world. >> Yes.
1:44:32
>> And and we're you can't kill anyone.
1:44:32
You can't uh put anyone in a re-education camp.
1:44:37
But what you can do is we're going to give you the magical microphone, which is sitting right in front of you now.
1:44:41
Um, and you can say two things that will incept the entire population of the earth whenever their tomorrow is.
1:44:49
They're going to wake up with these two things and think these are my ideas.
1:44:53
They're going to think that they had come up with them, >> but they're also going to make the commitment unlike all the other time that I had these great unwaking or shower thoughts, I'm going to actually act on these two things.
1:45:05
What two things are you incepting?
1:45:10
>> So, I think the first one is around and getting people to ask more questions.
1:45:14
getting people to ask more questions. I feel like like it's one thing to say be curious like I definitely want people to cultivate curiosity but I think the key to cultivating curiosity is spurring yourself to ask more questions like why like asking the name of like like the term for something um because
1:45:32
it will often lead you to realize oh there's this like I don't know entire entire domain of architecture around these things that I didn't even know or some weird thing in woodworking or whatever it is and so it can be as simple as like asking the name of something but just more We just ask more questions. I feel like that would be the
1:45:46
I feel like that would be the first. I love that one.
1:45:49
>> And the second, walk more. I I like walking a lot.
1:45:52
Um, and I think however much walking you do, you can always do more. So, walk more. >> I love both of those.
1:46:01
You're in the perfect city for walking. >> Correct.
1:46:05
>> Sam, thank you so much for rejoining me.
1:46:08
I'm already looking forward to recording number three. >> This is great. Thank you so much.