36: C. Thi Nguyen - Measurement, Meaning, and Play

Speaker A: Playing is taking normally useful resources and wasting them for fun. Speaker B: Wasting them for fun. Speaker A: But, okay, here's the big but. It's only a waste galactically if you thought that stuff was pointless. The other notion of playfulness that I find really useful, what she says that playfulness is, is the ability to move lightly between worlds. There's worlds of rules and landscape and meaning, and sometimes you might be in the business world and you're focused on profits, and sometimes you might be in the family world, and sometimes you might be in the artist world trying to be expressive.

One way is to just inhabit one of of these worlds like permanently. But another thing you can do is to realize there are different worlds you can shift between and not be stuck in them. And she says, "To be playful is to inhabit the worlds lightly and creatively." There's two different things: really good at role shifting versus being willing to completely transform yourself and get yourself stuck in a role forever. One worry might be there's one thing, which is playfully being able to shift into different roles, and there's another thing that this world might reward, which is psychopathically committing yourself to a hyper-simplified role and never being playful with it.

Attention and value are so interlinked. What you value is what you pay attention to. One of the ways that games work is that the scoring system guides what you're trying to do, which deeply guides your attention. Uh, Reiner Knizia, who's my favorite game designer, has this moment where he's like, the most important thing in my game design toolbox is the scoring system because that tells the players what to care about. What to want in the game. Games are the art of agency, right? They work in the medium of agency. Some games are incredibly good because they give you enormous agency, but some games are really good because they hyper-constrict your agency.

Soccer is interesting because it takes away your hands. Speaker B: Welcome to Dialectic, episode 36 with C. Thi Nguyen. Thi is a professor of philosophy at the University of Utah where he studies values, games, agency, art, aesthetics, metrics and data, and more. His new book, The Score: How to Stop Playing Someone Else's Game, is out now. He's also the author of Games: Agency as Art, where he explores how game designers work in the medium of agency in the same way that a painter might work in the medium of what we see, a musician what we hear, and so on.

The game designer sculpts the player's agency by harmonizing their abilities, their goals, and their obstacles, making it easy for the person to act and also allowing the player to take on different forms of agency. I was first exposed to Thi and this idea in one of my favorite podcast interviews of all time, where Ezra Klein interviewed Thi back in 2022, where he talked extensively about this, as well as a paper he wrote called "How Twitter Gamifies Communication," other ideas like why QAnon is very much like a video game, and more.

I reached out to Ti about a conversation last year and was excited to hear that he had a new book in the works for January 2026. And here we are. I flew out to Salt Lake to talk to him and we got to dive deep on The Score. In many ways, The Score combines his earlier work on games with so much of his work on values and metrics and data. And specifically, he's interested in this question of why scoring systems are so useful in games. They allow us to explore agency.

They allow us to be more playful. They allow us to take on different roles and explore our values. And then scoring systems and gamification in the real world instead flatten us and flatten our values. He has a term he calls value capture to describe this. And in a world that is so value captured, one where we're in such a rush to quantify and measure everything, unfortunately we miss out on the things that are harder to measure. And thus, I think, and Ti would agree, that we strip our lives of meaning.

I split the conversation into two parts. The first is focused on the local, the individual side. Individual agency, how we explore individual values, what good values might be, what the shape of them are, how video games allow us to explore those, attention and why attention is upstream of almost all value, and specifically this really compelling bit where we talk about the difference between recognition and perception, and ultimately why playfulness and a playful approach is so powerful across all this. And then the second part of the conversation zooms out and goes to more of a global level, talks about society and how metrics and data seem to rule so many of our decisions.

We also talk about how we can still scale trust. We can still benefit from science and technology and trusting experts while also not being exploited by bad actors in the system or relying too much on just trustless systems or trustless contracts. One of my favorite ideas of Thies is what he calls objectivity laundering, and we talk extensively about why objectivity and truth are not always the same thing. And then finally, we end the conversation talking more about technology and why technology is not value neutral, as many of us often assume it to be.

In fact, it is laden with value decisions everywhere. Uh, this doesn't mean we shouldn't build technology, but it does mean we need to be much more thoughtful about the values that's inside of our systems and be much more thoughtful about the ethical decisions that go into making anything. I hope you are inspired to think more deeply about your values and what you care about and put more intention into how you create meaning. I also hope you're inspired to embody more playfulness as you go about your daily life. If you enjoy it, I hope you'll support T's work.

The score is out now, and he goes much more deep into so many of the things we discussed today. Before we get into the episode, I want to thank Dialectic's presenting partner, Notion. I'm now full-time on Dialectic thanks to Notion support, and I'm thrilled to be partnered with a company, product, and tool that is so aligned with Dialectic's values. Notion is built for people doing their life's work, And it's a tool in particular for teams who are collaborating in a modern way. That means not only being able to work on ideas together, but also work natively with AI to delegate the busy work, focus on the things that matter, and have everything fit together natively without skipping a beat.

It's how so many people turn their ideas into action. It's how I prepare for the conversations I have here on Dialectic. I throw everything I can find on a person, everything that stands out to me into a document. And then I'm able to synthesize, try to figure out what's actually worth asking them about, what are the connecting dots, and so on. It's been really fun to explore using Notion's agent to uncover things I might have missed in my research process or identify patterns, whether in an individual episode or across previous episodes.

Um, I'm excited to do so much more of that this year. I can only imagine how much more powerful it's going to be. If you don't use Notion already, you can check it out at com/dialectic. Thanks again to Notion for presenting Dialectic, and thank you for supporting, listening, reading, and so on. With that, here is T. Nguyen. T. Nguyen, it's a pleasure. Speaker A: What's up? Welcome to my insane home. Speaker B: One of my favorite things about this is I get to go inhabit people's worlds. Speaker A: Yeah. Speaker B: You have a— well, first off, congrats on the book.

Speaker A: Thank you. Speaker B: I guess congrats in the future when this is released, you will have successfully published the book. You have a bit early on in the book, uh, and you tell the story about how a student of yours kind of influenced this book. Um, it reminded me of a Kwame Appiah quote that I love that you may be familiar with, which is, "In life, the challenge is not so much to figure out how best to play the game. The challenge is to figure out what game you're playing."

Um, what a great place to start. I, I, I think I, I want to take that last word because I think it's such an important word that we'll come back to a lot. And my first question is pretty simple, which is, what does it mean to be playful? Speaker A: Yeah, this is a really good and really deep question. It's funny because there's a way that you can— the way the English language is, we have— we say that you play a game. And this is not true in other languages. The word play is always appended to games, and we assume they go together, that, you know, doing a game is always playing.

But the philosopher Bernard Suits, one of the people that I truly love, pointed out that this is not always true. So he was like, look, you can be playful and not be involved in a game, right? You can be screwing around with— you can be at your job and like starting to make up new stuff. You can be like fucking around with like new ways to approach your daily life or cooking. And you can also, he said, play a game, but it's not really play. It's work, right? Like you hate it or someone's making you do it or you used to be interested in poker and now you hate it, but it's like the way you make money.

And that's not playful. Work even though it's a game. So there are a lot of, like, attempts to say what it is to be playful, and there are two I would like— I've actually never— I've been trying to figure out what play means for, like, honestly 10 years, and I don't have a good single stable foundation. But there are two, I think, really good stabs. So Bernard Suits says that being playful is redirecting normally useful resources to autotelic activities. Autotelic means valuable in itself. So what he means is something like, look, you're, um, normally, uh, normally I use this like logical capacity to fix things or to like argue with people or get something.

But then sometimes I do like a puzzle and that's just exercising the logical capacity just for the sheer pleasure of doing it, often uselessly. Similarly, like, I mean, this house is surrounded with like weird skill toys, like yo-yos and kendamas. And they're all these like balance and physical things you would do with your body that you would normally use for, like, survival or getting food or getting from place to place, and now you're just screwing around with it for the sheer joy of motion. So that's one sense. That's Suits' sense.

Is that— Speaker B: one thing I'm hearing inside that almost is like a sacrifice of resources. Is that too strong of language? Like— Speaker A: That— no, that's great. So there's— there's a perspective by which the quick way to put what Suits is saying is that playing is taking normally useful resources and wasting them for fun. Speaker B: Wasting them for fun. Speaker A: But, okay, here's the big but. It's only a waste galactically if you thought that stuff was pointless. So to think, when you say that, I mean, that's an easy way, that's what I say to my students, like, you're wasting useful resources for fun.

But when you say that, you're already implicitly adopting the attitude that clear outcomes, making stuff, creating goods, accumulating resources, that's what's actually valuable. And action for its own sake is useless. And I think what Suits actually thinks is, no, that's, that's, I mean, like, that's, that's actually what's important. So it's not actual waste. The, from the philosophical perspective, the actual waste is if you spend all your time on useless activity and have a miserable life and have a pile of goods at the end and you die unhappy. And the actual, I mean, this is in some ways just utterly like the actual fulfilling life is one where you found activity that's valuable to you.

So, I mean, I mean, like, to say that wasting useful stuff for fun makes sense, and it's also like already using the language that is the trap. Speaker B: Waste is amazing. Speaker A: It's a— Speaker B: it's— I love that you use that word though, because it's— you have a visceral reaction to it. It's so not useful, right? Okay, so you have— that's, that's the first one. I think you had— you said you had a second, right? Speaker B: Waste is amazing. Speaker A: It's a— Speaker B: it's— I love that you use that word though, because it's— you have a visceral reaction to it.

It's so not useful, right? Okay, so you have— that's, that's the first one. I think you had— you said you had a second, right? Speaker A: There's two. So the other notion of playfulness that I find really useful, uh, my favorite articulation of it is from Maria Lagonis, the great feminist philosopher. And in this beautiful paper called Playfulness, World Traveling, and the Loving Gaze, what she says that playfulness is, is the ability to move lightly between worlds. And what she means is like the normative worlds. They're like, there's worlds of rules and landscape and meaning.

And sometimes you might be in the business world and you're focused on profits. And sometimes you might be in the family world. And sometimes you might be in the artist world trying to be expressive. And she thinks like, One way is to just inhabit one of these worlds like permanently and like stuckly. But another thing you can do is to like realize there are different worlds you can shift between and not be stuck in them. And she says, what she actually says is to be playful is to inhabit the worlds lightly and creatively, to both be able to move between them and also be able to like screw with them and like in your mind change the rules of the world that your soul is inhabiting.

So I think like, I mean, both they're related to each other. There's differences between them, but I feel like somewhere between those is some like deep sense of what it is to be playful. Speaker B: What I like about the second one too is it more captures what you would, when you describe someone as playful, that's kind of what you're pointing at. It's this sort of dancing. And I think we'll talk about this more later, but is creativity You used create— you used the word creative very early on in your answer, and so I'm curious if creativity is just very common in this idea of playfulness or something more paramount, right?

Speaker B: What I like about the second one too is it more captures what you would, when you describe someone as playful, that's kind of what you're pointing at. It's this sort of dancing. And I think we'll talk about this more later, but is creativity You used create— you used the word creative very early on in your answer, and so I'm curious if creativity is just very common in this idea of playfulness or something more paramount, right? Speaker A: I mean, this is what— this is when the two of them separate.

Like, I think Bernard Suits, the, the first one, he— I mean, he's the person, the philosopher that I learned the most about games from, and I think in that you can see the big difference. So if you're like hyper-focused, so on a sport, for example, like rock climbing, you are trying to perfect a movement and get exactly this movement exactly right. Get your body all in a line, and you might know exactly what you're supposed to do. Like some, some techniques, like, I know what the technique is, I know how I'm supposed to balance my hips, I know I'm supposed to move my hands, I can see other people do it, and I'm just trying to find it.

Speaker B: Yes. Speaker A: In a sense, that version isn't very creative, but it is like refining my movement and taking actions for the sheer pleasure of it. That's the case where they come a little bit apart, right? Speaker B: Yeah, yeah, yeah. That's helpful. I want to talk— well, super helpful context. I think this will come back a lot. This might seem strange, and you have— I think the way you outlay— you lay out your ideas in the book is quite compelling. I wanted to kind of attack them from two vantage points.

The first part being maybe the personal and the local, and then we can talk about the sort of global. Speaker B: Yeah, yeah, yeah. That's helpful. I want to talk— well, super helpful context. I think this will come back a lot. This might seem strange, and you have— I think the way you outlay— you lay out your ideas in the book is quite compelling. I wanted to kind of attack them from two vantage points. The first part being maybe the personal and the local, and then we can talk about the sort of global.

Speaker A: Right. Okay. Speaker B: Obviously, the name of the book is The Score. Foundational to both sides of this is the notion that we have scoring systems all around us. And I think one thing that thinking about as I, as I thought about playfulness is like we live in this highly gamified world, and yet we are increasingly or decreasingly playful, you might say. Scoring systems, as you illustrate quite well, I think, tell us what to desire. I think the challenges in games, they give us freedom. In the real world, they constrain us.

And so I think to start on the, on the personal and the kind of like local front, I actually want to start with agency and talk about agency in the context of values. So like in many ways, there's a central theme here to me, which is starting with, um, who am I? Like, explore and then exploit. What do I want? You have this, um, Carol Rovan quote, um, about agents that I liked. An agent is some entity that considers reasons, makes choices based on those reasons, and acts. And if you change the reasons that you act on, you change your agency.

Um, this notably is not necessarily that close to a popular conception of agency in my world, in the technology world. There's a popular conception of agency that is you can just do things, right? It's actually less about the reasons behind what you do and more about just doing right. You don't talk about this kind of frame of agency quite as much, right? And so you focus much more on kind of like agential exploration. I'm curious what you think about that idea of agency first and foremost. Speaker A: Okay, let me, can I take a long ass step back and do a run up to this?

Okay. This, this is going to be full of weird details that you may or may not care about. So I'll give you my personal history of working with the concept of agency. And it comes with trying to figure out games. So the reason I started working on games, which is not supposed to be a topic that philosophers are allowed to, there's not, there was not really, there's a tiny bit of stuff, but it was like definitely not something that you're supposed to, if you're a serious student of philosophy at a serious graduate department, ever work on.

I got into it because I was teaching this philosophy of art class and I wanted to do a case study. And so a case study I did was, are video games art? And I read a bunch of stuff. And this, I don't know if this will surprise you, but a lot of the stuff I found really emphasized, they were like, games are art because they're like movies. They have dialogue, they have scripts, they have characters. Right. And like, they would like celebrate these games that were the least like a game.

They're the ones that were the, where you had the least freedom. You had the most, like, you were most locked into like these cutscenes or pre-written. There were cinematic. And I mean, I like those games, but it felt like someone was like clutching for a familiar sense of importance and like ignoring— Speaker B: I mean, Orphic almost. Speaker A: Yeah. Like I would read a 300-page book on the art of games and never hear the word play or freedom or choice. And right. So I was kind of like clutching around for it.

And I think there was this moment, it was, I think like a lot of other moments later, like I was pretty drunk and I was like, you know what games are? They're like governments. They're rule systems, but for fun. Games are art governments. I started working with that idea. And I also found around then, uh, Reiner Knizia, who's my favorite game designer, has this moment in this talk where he's like, the most important thing in my game design toolbox is the scoring system because that tells the players what to care about, right?

It tells them what to want in the game. And I was sitting there looking at this thing that seemed to me as a game player, like completely, uh, obvious. You look at a rule book, it tells you, it tells you not only what you're trying to collect, but it also tells you your basic conception of victory. It tells you like, if we open up a board game, we might find out that we're trying to kill each other, or we might find out that we're cooperating with each other, right? Victory could be shared.

Like, so it just tells you. Speaker B: I mean, Orphic almost. Speaker A: Yeah. Like I would read a 300-page book on the art of games and never hear the word play or freedom or choice. And right. So I was kind of like clutching around for it. And I think there was this moment, it was, I think like a lot of other moments later, like I was pretty drunk and I was like, you know what games are? They're like governments. They're rule systems, but for fun. Games are art governments. I started working with that idea.

And I also found around then, uh, Reiner Knizia, who's my favorite game designer, has this moment in this talk where he's like, the most important thing in my game design toolbox is the scoring system because that tells the players what to care about, right? It tells them what to want in the game. And I was sitting there looking at this thing that seemed to me as a game player, like completely, uh, obvious. You look at a rule book, it tells you, it tells you not only what you're trying to collect, but it also tells you your basic conception of victory.

It tells you like, if we open up a board game, we might find out that we're trying to kill each other, or we might find out that we're cooperating with each other, right? Victory could be shared. Like, so it just tells you. Speaker B: And we willingly opt in. Speaker A: Yeah, we willingly opt in. And so I ended up, what I ended up trying to articulate was that the heart of games wasn't that they told stories. I mean, they can, but the heart of games was they shaped your action so that actions, decisions, and stories like came out of you.

And the way I ended up putting it was that games are the art of agency, right? They work in the medium of agency. And I was reaching for this and I realized that people would say like, oh, they would misunderstand because agency just meant for them like activity and freedom. And that's not a good conception of games because some games are incredibly good because they give you enormous agency, but some games are really good because they hyper-constrict your agency, right? Like soccer is interesting because it takes away your hands. Like Tetris is interesting because it's like poker, like limit poker, which is so interesting.

It's interesting because at each stage you have almost— you're trying to do so much with such a tiny action space. And that's actually what's beautiful about it. Speaker B: Yes, yes, yes. Speaker A: Yeah, Reiner Knizia, who's like, borrows from poker, has this incredible game called Ra. And you, like, you're trying to affect people's incentive structure. You can only do it. And again, you're, you're, you're only opt— you have 3 coins and you get to bid them or pass. And that's it. And you're trying to do so much. And I realized what I was using was an older notion of agency.

So I think Carol Rovane, that quote you read, is a really natural version of this. And we have this in terms like when we say that you have a literary agent or a lawyer, your legal agent. Speaker B: Ironically, we now— I mean, ironic— we talk about it in AI agents. Speaker A: Yeah, right. Exactly. So what it is for you to have a real estate agent or a legal agent is that when they're performing their job, they're acting on your reasons, not theirs, right? They're shifting the reason structure. And at first you might say like, oh, this looks really weird.

Like, oh my God. Like it's very, it's this bizarre one-off thing that you do in games that you structure reason, you change your reasoning structure. But Carol Rovane, that amazing philosopher, is pointing out, she says that we do this constantly. And it's something as simple as, her example, because she's an academic, is, you know, I'm on a search committee and I'm trying to hire someone and I'm not usually using my own reasons. What I'm doing is a lot of the time I'm not supposed to hire who I like, who I want to hang out with, right?

Who would be good for my projects. We're supposed to, as a department, decide what we care about. Right? And then when I'm on the search committee, I, if I'm acting really in that role, I look at those reasons and I switch into— I mean, this is again, super familiar. So it's like, okay, Here's, here's another example. I think one of the things that happens in games is that we cancel out a lot of our reasons, right? Like if my, if my, if my, that's a good look. So if my spouse and I are playing a game, normally my standard reasons are I love and support her, right?

In that game, we're going to kill each other. Speaker B: Yes. Yes. Speaker A: Right. Speaker B: Subversion almost. Speaker A: Yeah. Right. And, but we do this all the time. So for example, this is. This will perhaps be embarrassing and revealing, but also I think it's very true. When I started teaching, I brought my full human self to the classroom. Speaker B: Yeah. Speaker A: And this meant I was kinder and more open to students who were of my tribe, who had my sense of humor, right? Who had like, who had my politics, who liked the same music as I did.

And that's a bad teacher. Speaker B: You were being quote unquote authentic in a way that was detrimental. Speaker A: Yeah. And I think what a lot of us realize is when you're in a particular role, you cancel out a lot of reasons. And I think like, imagine like going to like a government office, right? And having the person treat you as a full person and giving you better treatment if they like you. You don't want that. Speaker B: It's ironically in games we're doing it for play. In these contexts we're doing it for duty or obligation or whatever it might be.

But they're, yeah. Speaker A: Yeah, but this is the idea. So John Dewey, the great American philosopher, says that in a lot of the arts, we take something we do in normal life and we concentrate it and crystallize it for beauty or interest for its own sake. I think there's this thing that we do always in normal life where we enter a role and we cancel out some of our reasons and we change the reasons we act on. And then in games, we do the same shit for fun or richness or something else.

Speaker B: And that makes us see the thing that maybe we were typically subject to. We're seeing the water a little bit when we play games. Speaker A: Yeah, we— do you mean like we, uh, become more aware that— Speaker B: And that makes us see the thing that maybe we were typically subject to. We're seeing the water a little bit when we play games. Speaker A: Yeah, we— do you mean like we, uh, become more aware that— Speaker B: Yeah, when we're doing that, usually that whole thing you just laid out, we're not thinking about the ways we're taking on different forms of agency in most of our daily lives.

Like, we're— I think most people's perception would be like, yeah, of course I'm not going to be like— I'm going to be a little different when I'm at work. But they haven't fully— and I would argue many of the people who are most successful in modern society, the ones who are really good at this, right? Maybe it's sociopathic, but— Speaker A: or I mean, this is— sure, this is probably leaking into the later part. But there's really good— there's two different things. Really good at role shifting versus being willing to completely transform yourself and get yourself stuck in a role forever.

And I like— one worry might be there's one thing which is playfully being able to shift into different roles, and there's another thing that this world might reward, which is psychopathically committing yourself to a hyper-simplified role and never being playful with it. Speaker B: We will get to that. Yeah, we will get to that later. Um, on this note, maybe then of agency, and I want to talk about values too, because I think it's critical, but since you brought it up, like the, maybe, maybe one conception of this would be that games can make it easy to act to my earlier point, which is like the, the, you can just do things form of agency.

And the other is that they make it easy to explore the possibility space of actions. Speaker A: I think one thing that is important here to keep in mind, the kind of two levels of agency involved in games. So there's the kind of— there's one, there's one kind of agency in which a game, a specific game, provides you with one particular form of agency in the sense that we've been talking about, and it fixes it. And you plunge into it during the game. You suddenly become a being of only balance or a being of only like calculation or a being of only like deceit and lying, right?

Each of the the game focuses you. And then there's another tier of agency. I think of the other sense you're talking about, the freeing sense, the exploring sense, where games as a whole let you move between them, right? They give you the freedom to— I get to mean, I get to have a choice. You know, in a lot of my work life, I don't have this choice. The work life after this interview, uh, I'm gonna be grading. Like, I don't have any choices about this. Like, there is a kind of agency that's going to pushed into me.

But for my break, right, I can choose, am I gonna play with yo-yos? Am I going to run around the block? Am I gonna have a quick game of online chess? And each of these is a completely different kind of action and a completely different feel of action. And I get choice of them because of the enclosed nature of games and because the clarity makes that role shifting easier. I think that's something really interesting about games. The hyper-clarity of the rules and the points makes the role shifting easier. Yes. Speaker A: I think one thing that is important here to keep in mind, the kind of two levels of agency involved in games.

So there's the kind of— there's one, there's one kind of agency in which a game, a specific game, provides you with one particular form of agency in the sense that we've been talking about, and it fixes it. And you plunge into it during the game. You suddenly become a being of only balance or a being of only like calculation or a being of only like deceit and lying, right? Each of the the game focuses you. And then there's another tier of agency. I think of the other sense you're talking about, the freeing sense, the exploring sense, where games as a whole let you move between them, right?

They give you the freedom to— I get to mean, I get to have a choice. You know, in a lot of my work life, I don't have this choice. The work life after this interview, uh, I'm gonna be grading. Like, I don't have any choices about this. Like, there is a kind of agency that's going to pushed into me. But for my break, right, I can choose, am I gonna play with yo-yos? Am I going to run around the block? Am I gonna have a quick game of online chess? And each of these is a completely different kind of action and a completely different feel of action.

And I get choice of them because of the enclosed nature of games and because the clarity makes that role shifting easier. I think that's something really interesting about games. The hyper-clarity of the rules and the points makes the role shifting easier. Yes. Speaker B: Okay. This is pointing to something I think is actually really important, which is what I actually think you just described there is maybe part of the difference between incentives and values, which are two very different kinds of motivators. Speaker A: Yeah. Speaker B: The first one is like, I have to grade, right?

And I want to come back to the agency point because I think that part of what I'm really interested in is the you can just do things form of agency is sort of acting It's not acting based on incentives and it's kind of acting in the world of value. Maybe for a second, like you say incentives can provide some motivation, but they don't change your core values. Maybe to start, like, why do you think modernity tempts us so much to overweight towards incentives rather than acting based on values? Speaker A: Well, I mean, I don't— I'm not sure that's the right way to formulate the question for me, because my worry is about— there are always going to be incentives, and my worry is when incentives become values.

So an incentive— okay, so a value roughly is just, I think, whatever is your core motivator, whatever is the ultimate guide of your action, whatever sets your choices, whatever sets how you're going to change yourself. Your values are where all this springs from, whatever that is. Incentives are things the world gives you where it says, if you do this, you'll get those resources. And so I think there's one way that you can keep the world at arm's length where you say like, okay, the world is giving me certain incentives. It's saying I have to do things this way to make money.

I have to do this things this way for people to listen for me or to get, get enough people to tune into this show to even hear what I'm saying. So those, those are the incentives. And then the reason I'm entangling with them, the reason my reason for gathering those resources comes out of my actual values, right? So that's one structure. The thing I'm worried about is when they collapse and we suddenly forget to think about what our values are beyond the incentives. I mean, this is the— what I'm talking about is the simplest damn thing, which is the one frame of mind is to make enough money to do what you actually want.

And the other frame of mind is just be like, well, here's what I do. Here's the scoring system. I'm just going to max out on making money because Right. And not thinking about the thing it's for. I mean, it's, I think that's just, that's it. That should be a, that's, that difference should be familiar to everyone. And that's the difference between like having a firewall between your true values and your incentives and letting them be collapsed. Speaker B: Yes. I think maybe I was making too big of an assumption there and sort of assuming that when I, when I said the difference between incentives and values, I'm thinking of values as sort of the things we do despite incentives, despite clear incentives.

What do you think of willpower? Speaker A: Tell me what you mean by that question. Speaker B: Do you know who, like, David Goggins is? He's like the ultra marathoner. He's the guy who's like, wake up at 4 m. and carry the logs. And one of my jokes is I like, I like don't really believe in willpower. I think willpower is this sort of like grittiness despite maybe even clear incentives that says like, I'm going to do something hard, right? Because in the long run it's going to pay off. Speaker A: Right.

Speaker B: And I've always kind of related to willpower as sort of like the people who require willpower are the ones who haven't found a way to harmonize their real values and what the world wants or something like that. Speaker A: Yeah. I mean, that's pretty romantic. I get to be a philosopher, but let me tell you, I have to grade 10 more papers tonight. Yes. That's going to need a lot of willpower. Yeah. Okay. Um, I mean, I think, let me, let me try something. Maybe this will be interesting to you.

So when I was first trying to articulate, uh, we just introduced the value capture term. Sure. So, uh, one of the core ideas of my book is value capture. Value capture is what happens when you have values that are rich and subtle and developing, and then you get put in an institution or a social setting that feeds you clear, simplified versions of those values, like a metric. Speaker B: And then sort of the incentives and the values become— Speaker A: you were just talking about that. Speaker B: Yes, collapsing. Speaker A: Exactly.

Right. So I just, I just, and then they take over. So value capture is what happens when you go to school out of an interest in learning and you get focused on GPA. It's what happens when you go on social media to connect to people and you get focused on likes, or you start a podcast to get ideas and then you become focused just on subscriber count, not as a means to communicate what you really want, but changing what you're trying to say to just max out your subscriber count. Okay.

So I've been worried about value capture for a while and I've been trying to figure out what's wrong with it. And here's a first pass. One thing you might think is the wrong of value capture is that the world is— that you're losing control of your values, that the world is forcing your values out of something you freely choose. I don't think that's actually the right one. And it partially— one of the— okay, if that's true, if that were the right account, then if someone were forced to and brainwashed into forced to putting on a, uh, putting on a watch and just caring about their steps, or forced to like pay attention to their BMI instead of their health, that would be a problem.

But if someone freely chose and devoted themselves to weight loss over all else, that would be fine because it's a matter of choice. I think actually one of the most worrisome things is cases where people enthusiastically and freely to be value captured, right? They're like, okay, they, they embrace it. They lose the plot, right? They say, uh, and they lose the plot because in some ways it's easier, right? Because the world is giving you a quick, easy tracker and everyone else understands it. So the thing I'm really interested in is trying to explain.

I bet. Okay. I'm going to do some abstract philosophy. I think you'll like this. I think it will be interesting to you. One conception of what the human, human well-being is. And I mean, we, this might sound weird, but we've got to talk about what, like, well-being and flourishing and what makes a good human life. Because what we're talking about is how oversimplified values screw that up. Speaker B: By the way, that's, that's part of, I think, one of the reasons I wanted to set the table, at least on the more personal side, which is like, we're going to talk more about all the kind of like global problems we have.

But at root, like, these things are intuitive. We forget them. The point of living is to live a meaningful, flourishing life. I think we can all agree. Speaker A: So, Let me just say, there's so many things I want to say right now, but let me just say one quick way to do it. Like, uh, I'm worried about someone capturing your definition of meaning. I'm worried about someone, and this is why, like, this is why the willpower question is so interesting to me, because I think, like, if the world can change your sense of meaning, it can reorient your will.

It can make you send all your willpower and all your grit towards some simplified— Mm-hmm. Right. Okay. Does that make sense? Speaker B: Yeah. Speaker A: So let me give you this, this bit of like technical background that isn't in the book because it was a little bit too technical, but you might find it interesting. So there's a standard view in a lot of economics and rational choice theory, and it's a prevailing view that guides social policy that says what people's well-being is is just the satisfaction of their expressed preferences and desires.

Whatever they say they desire, whatever they say they want. Give them what they want, they'll be good. And the view is something like, well, we can't be intrusive, we have to let people be autonomous, we have to listen to what they want. Speaker B: This is sort of like the neoliberal late-stage capitalism. Speaker A: Right, but this is also like underneath all of economic theory, right? This is like, this is underneath actually a lot of political science. It's not, it's like very, very progressive, very positive, very help the world political science scientists often work with this view that what well-being is, is satisfying people's expressed desires.

Speaker B: This is sort of like the neoliberal late-stage capitalism. Speaker A: Right, but this is also like underneath all of economic theory, right? This is like, this is underneath actually a lot of political science. It's not, it's like very, very progressive, very positive, very help the world political science scientists often work with this view that what well-being is, is satisfying people's expressed desires. Speaker B: Also not being paternalistic, critically. Speaker A: Right, because it's not— that's true, that it respects people's autonomy and respect, and it is non-paternalistic if you just listen to what people want.

One of the most interesting criticisms of this came out of, I think, '80s and '90s feminist theory, and it came because of a worry about what's called adaptive preferences. So it turns out psychologically, a lot of this comes from a sociologist named John Elster. So if I start to limit your opportunities, your preferences will adapt to the opportunities that are available to you. And so lower my bar, you'll lower your bar. Exactly. So one of the things that turns out was that if systemically women can't find work outside the house and the— and they're not permitted to work in the workplace, then people will adapt their desires to be— to, to domesticity.

So here's the worry. Okay. We create a world where half the people are not allowed to work. They adapt their desires and to fit the limited situation we have. According to desire preference satisfaction theory, we've won. We've succeeded. The world is great. Speaker B: I mean, then you have a falling knife, right? Speaker A: What do you mean? Speaker B: Like, you have a fall— like, theoretically, like, if you wanted to paint a really, really cynical vision of the world, it's just this— that, that scenario you just described just seeps into more and more of— Speaker A: yes, yes, exactly.

Let me just finish that. So I, I just did this for my students. It was like, look, so if your view is that well-being, a good world, is one in which people's expressed desires match their situation, Imagine you have— here's a case where most of the world, people in the world get $20,000 a year and their desires are to have $60,000 a year. There are two ways to satisfy everyone's preferences: make the world better or get people to decrease their preferences. Yeah, right. So does it make sense why this is in the background?

Yes. So this is, this is the part of the worry is that it might look to you like, oh, it's great. If we just get people to collapse their values to incentives, then They will have a ton. We give them everything they want. They want something really simple. They want straightforward things the world can provide for them. And then things are great. And I think part of the deep thing I've been convinced of is that desire, preference, satisfaction theories of well-being aren't right. And this also means that strict autonomy about values isn't right, that you can have the wrong values.

Right. And a lot of what I'm worried about is the systems by which you might be convinced to fully commit yourself to very simplified values that diminish yourself. Yes. Speaker B: And it's reflexive. And, and yeah. Speaker A: Is this— did I, did I get— are we in the ballpark of what you want to talk about? Speaker B: Um, you might have the wrong values is something you said. Um, what is this? What is the— this is a thorny question, surely. And it's clear that maybe the wrong values— we don't want flattened values, right?

What is the shape or the texture directionally of good values? Speaker A: Okay. This is the most interesting question. Okay. There's one way I can imagine this conversation going in which you ask this question and someone else seated here would try to give a specification of what the right values are. That is not the way. can go. One of the things I think that I've been convinced by is that the right values for a particular person to have are incredibly dependent on a lot of details about the particular person, their particular context, their particular psychological profile, their particular place in the world.

Elijah Milgram, a philosopher who's been really influential to me, has this view that you don't calculate the right values for you from the top down by, like, thinking about some abstract conception of the good and then, like, yes, deducing it. You have to try them out and see if they work for you. And one of the things he ends up saying is you get these signals. If you have a value that works for you, uh, you thrive. And if you have a value that doesn't fit you in your situation, you fall apart.

And it's— some of it's dependent on your personality, but some of it's dependent on the place you're in. There's this great example. One of my favorite examples of anything comes from Jane Jacobs' The Rise and Fall of Great American Cities. And she has this moment where she talks about how she says a lot of people will come from rural areas to New York, and in rural areas they'll come in with a value— they highly value friendliness, right? Like making eye contact, chatting with everyone you meet. And then they come to New York and everyone seems like an asshole because no one's making eye contact.

And like, if you try to talk someone up, in the subway who got their headphones on, they'll like bite your head off. Speaker B: Yeah. Speaker A: And then you spend some time there and you realize the value of friendliness does not work when you're in the subway with people all day long. The big city is so packed that you need to actually deeply value respecting other people's privacy. And it's not that one of these values— Speaker B: like an evolutionary fitness for that environment. Speaker A: Exactly. It's a fitness.

So it's not like one of these values is better than the other. It's that that some values are suited for some contexts and some values are suited for others, and cross-multiply the context sensitivity of values with the fact that different values will be good for different personality types. And what then, what you get is, is the, the view is something like value should be tailored to you. But this is not the same view as you have the freedom to pick whatever values you want. It's that your values need to be carefully tailored sensitively to your environment and place, often using as a guide the particular signals of your emotions, how you feel.

Speaker B: This is kind of what I'm— I guess I'm glad you answered this way. What I guess I'm trying to ask when I say what is the shape of good values, I think is inside of that last statement that you made, which is the point here. Also, I think so much of this is running against like there's a broad feeling that we have like a meaning crisis, especially for young people. Your central contention is like one of the main reasons is people need to choose their own values. The history of the world is actually that, like, values are issued to you top-down and not necessarily in this, like, post-modernity metrics or, excuse me, incentives and values flattening, but in, like, the state tells you what to value or the church tells you what to value or your family tells you what to value.

And so I guess there's like, I'm feeling some tension, which is like, I think it's really profound. I, and I, I'm 10, maybe, maybe it's because I'm a young person in 2025. I tend to agree that we should choose our own values. And yet that doesn't mean you should just choose any values, right? Right. Like there are good values, right? Speaker A: There's, I mean, in the background, like, hopefully it's all right. You're, you're, you're getting a particularly wonky philosophy techie version. Speaker B: This is what I was looking for.

Speaker A: Okay, good. Um, there's, I just want to go back and say like, I think we should be really careful about about the difference between you choose your own values and you tailor them to the specific context, right? It's not just a matter of choice. I think this is similar, like, I was just talking to my spouse about this. A lot of people want to collapse this to this, like, distinction between objective and subjective, like either values are objective or they're fully subjective. Speaker B: Almost like morals and feelings or something.

Speaker A: And if they're objective, they're universal. And if they're subjective, they're just you and your feelings. And I'm saying, no, you can have better and worse values. You can get the wrong values. But whatever the right ones are, deeply tailored to what you are. So it's less about choice and more about sensitive detection. It's a mixture of— does it make sense? Speaker B: Yes. Speaker A: It's a mixture of both invention and like, yes, listening. You can decide, you can just— I mean, one of the things that Elijah Milgram's— his— this beautiful— you would love this paper, it's called "On Being Bored Out of One's Mind."

It says you might have a theory that this is the right value for you, and you go to grad school and you think, I'm going to do this thing, and then you're just miserable and you're that misery is a detection signal. Speaker B: And then you start relying on willpower, by the way. Speaker A: Right, then you start cranking through, and at some point, right, at some point, you have to listen to the signal that this is a terrible value, you are not flourishing, right? Yes. Speaker B: Okay. Yes, yes.

Speaker A: So, oh my God, we, what was the question? I had gotten lost again. Speaker B: Okay. Yes, yes. Speaker A: So, oh my God, we, what was the question? I had gotten lost again. Speaker B: I think what I'm trying to square is, is— Speaker A: Oh, from outside, from outside. Speaker B: Yeah, yeah. Speaker A: Okay. I think this is— so one of the reasons I also really like this kind of feminist '90s value literature is that before this, there's this kind of like fantasy, and I think some of it we inherit from existential philosophy, that like, look, your own true values, your authentic values, come from you, and values from the outside are alienating and terrible.

And that can't be right. Like, we get value, like, we soak up our values from the world. Speaker B: That's sort of the choose your values, like sit in a cave and choose your values. Speaker A: Yeah, like pure choice. There's this great There's this great comment from a philosopher economist named Audrey Colney that he says that there's some conceptions of value that are just too heavy and thick that don't have any freedom in them at all. But then the existential conception of value is too thin. It's too narrow. It's just pure choice.

Like, just make something up. Out of what? Ignore the world. Just make something up. That can't be it. So I think we get our values all the time. And even if a lot of our values— I mean, and I think like there's a simple version of this. Like a lot of the ways We learn to value things is by learning from other people who guide us through activities. This is a lot of what games do. You show up, you start doing some weird new activity like climbing, and you come in and you think to yourself, oh, climbing is for like getting ripped and getting a workout.

And then people are, and then, I mean, and then someone tells you like, you're climbing really brutally, like try a little more sensitivity in your feet. And you're like, what? And then you suddenly learn that actually. So much of the beauty on offer and so much of the value in this activity is something you never realized before, which is there could be like delicate poetry in your own movement, right? And you learned this— like, I learned that from other people, right? Pure existentialism of that kind of like choose your values kind doesn't have room for learning from other people.

Speaker B: Well, and it's more top-down too, right? To go back to your Jane Jacobs or Christopher Alexander, any of these ideas are about finding it through emergence and experience. Speaker A: Well, I mean, there's two. Pure top-down is the world tells you your values and you take them on. That can't be right. Pure bottom-up is like, make it up. Speaker B: Immaculate conception almost. Yeah. Speaker A: Yeah. And in between is something about learning and negotiation. But one of the differences is when they're not fixed from the top down, when you receive a lot of value and candidates and proposals from the world, you can balance them and reinterpret them from yourself.

Like the world may tell you, you know, Yeah, family. Speaker B: It's a bit like taste. Like, it's a bit like taste. Speaker A: Like, explain what you mean. Speaker B: Taste has been a common— a big discussion and something I've talked about with people. And I think people in technology figured out taste mattered a few years— a year or two ago. And I think the conception of taste is often just talked about as this, like, judgment. It's just the judgment. It's the judgment isolated. He has good taste because he knows what things are good.

And taste, of course, intuitively, but also, uh, we forget, is eating a lot of food first and foremost. It's a lot of inputs, which is maybe the connection I'm drawing, which is part of what you're maybe illustrating is like perhaps what games can do. And we can talk more about that, but other things might do too, is to allow us to, um, refine our taste and our values. Speaker A: I see what you're going. I think taste is great in the following way. When you're developing taste in something, going it completely by yourself isn't going to get you there.

And accepting external authority states isn't going to get you there. What you need to do when you learn about something like jazz is you listen, you learn, you let people point things, and then you slowly start to also find your own way and refine your own tastes. And you do it through this intense exposure and careful attention to lots and lots of examples. Um, and I mean, I think maybe that's one way to put it. I do think if the world is like forcing a very specific value conception on you rigidly, this is not good for human beings.

But a thing that often happens, I think, that we're losing in the metrofied world is more open. The world might give you a bunch of values, honor, courage, loyalty, family, community, but it doesn't tell you exactly how to apply those concepts. It doesn't give you the precise borders, and it doesn't tell you how they count against each other. So you, even if the world is generally communicating values to you, you have like a lot of, um, freedom of interpreting particular open-ended terms and finding balances. And that's very different from the world saying, from you saying, I will value a higher subscriber count.

That is a non-interpretable, non-plural unidimensional thing that there's no free play in. And that's really different, I think. Speaker A: I see what you're going. I think taste is great in the following way. When you're developing taste in something, going it completely by yourself isn't going to get you there. And accepting external authority states isn't going to get you there. What you need to do when you learn about something like jazz is you listen, you learn, you let people point things, and then you slowly start to also find your own way and refine your own tastes.

And you do it through this intense exposure and careful attention to lots and lots of examples. Um, and I mean, I think maybe that's one way to put it. I do think if the world is like forcing a very specific value conception on you rigidly, this is not good for human beings. But a thing that often happens, I think, that we're losing in the metrofied world is more open. The world might give you a bunch of values, honor, courage, loyalty, family, community, but it doesn't tell you exactly how to apply those concepts.

It doesn't give you the precise borders, and it doesn't tell you how they count against each other. So you, even if the world is generally communicating values to you, you have like a lot of, um, freedom of interpreting particular open-ended terms and finding balances. And that's very different from the world saying, from you saying, I will value a higher subscriber count. That is a non-interpretable, non-plural unidimensional thing that there's no free play in. And that's really different, I think. Speaker B: Yeah, you have a, you have a thing where you say precise values embody a closed-minded spirit about what's important in the world.

And then conversely, you write about poets using like a meaningful inarticulateness and how values can have these imprecise edges. Like, do you have any— maybe this is a lead into sort of the game role-playing stuff, but like, what, how do we How do we move towards these fuzzy values? Like, how do we sit with them? Speaker A: I mean, there's a sense in which they've been there all along. We just have to let them— I mean, what we're talking about is basically the value of art. Like, this is not unfamiliar, right?

This is what poetry is. Like, the philosopher Elizabeth Camp, who's this incredible philosopher of language and philosopher of mind, has this beautiful set of essays about what metaphors are. He says what metaphors are is when you know this thing is like that thing, but you don't know exactly how. You're kind of gesturing roughly, being like, "I'm not sure, but somehow your soul is like the ocean in some way, but I don't know exactly which way." And it's a way of pointing at something without defining its edges. And I think, I mean, it is— it's so common to think like, uh, the more precise the language, the better.

And there are two cases where this falls apart, um, both of which I'm fascinated by. One is when the world is actually vague and fuzzy as boundaries, when the real world— when we're talking about something that is— I mean, a lot of the times I think these stupid debates like, is something a sandwich or a taco or a hot dog? The answer is those aren't well-bordered concepts. They are essentially— we have to accept their fuzziness. And we not pretend that we know things. The other case where we really get fuzziness is when we're uncertain and we want to express that uncertainty.

We want to mark that uncertainty. We remind ourselves we're uncertain. And we do that by having language— Speaker B: We want to sit in the uncertainty almost. Speaker A: What'd you say? Speaker B: We want to sit in the uncertainty. Speaker A: Right. I mean, a paper I'm writing right now is about the term vibe. And I think, I mean, I think it's often pointing to that. So like, good vibes, really, it's very openly fuzzy. It's like, There's something good going on and I can't put my finger on it. Speaker B: Getting more of these, auras was the word last year, right?

Speaker A: Yeah. Speaker B: It's interesting that society seems to be, or at least young people seem to be trending towards more of these words that are— it's the, it's the finger pointing at the moon or something. Speaker A: Yeah, I think we're— I do think new slang— I mean, this is, this is a paper I'm writing right now, actually. I think new slang terms are often people trying to find language to express something that's important. And the rise of vibe, and I think you're right about aura, is people wanting to point to the need to sit in unclarity.

Yes. Speaker B: And it's not because it's not real. It's actually very real. Speaker A: It's very real. Speaker B: Maybe, maybe a lead into one of the earlier conceptions we were talking about of agency, like your sort of like central idea of games is that they allow agential fluidity. We humans have an enormous capacity for agential fluidity. Imperial trained me in this mode of getting people to do what you want by giving them a piece of the action. And it's not just training some technical skill. Imperial, which is a board game, gave me a whole outlook, a whole attentional focus.

Speaker A: I love that. Speaker B: Like, why does this begin with attention? Speaker A: Yeah, I think attention, attention and value are so interlinked, right? What you value is what you pay attention to. I think one of the core things, one of the ways that games work is that the scoring system guides what you're trying to do, which deeply guides your attention. And so setting the scoring system is a way for a game designer to sculpt your attention, right? So it's like rock climbing. The goal is to go up.

The rules are don't use any rope. And suddenly your attention has to be on tiny details of the rock and the way you balance, right? Speaker A: I love that. Speaker B: Like, why does this begin with attention? Speaker A: Yeah, I think attention, attention and value are so interlinked, right? What you value is what you pay attention to. I think one of the core things, one of the ways that games work is that the scoring system guides what you're trying to do, which deeply guides your attention. And so setting the scoring system is a way for a game designer to sculpt your attention, right?

So it's like rock climbing. The goal is to go up. The rules are don't use any rope. And suddenly your attention has to be on tiny details of the rock and the way you balance, right? Speaker B: Like, so, uh, which you've never paid any attention. You never looked at that crevice before. Speaker A: Yeah, you never looked at it. And suddenly it's also, I think it's really interestingly, It's like an amplifi— like if you're inattentive to your balance on the rock, you'll fall. And so that game is constantly like not only telling you to pay attention to, but refining your attention by slapping you over and over.

Speaker B: We were talking about this earlier with the yo-yos. It's like, what a great way to just lock in. Speaker A: Right. Speaker B: Yep. Speaker A: Like there it is. It is. I, some people are, my spouse is very good at attending to herself. I am not. And so I find, um, I think this got cut out of the book. Godfrey Devereaux, one of my favorite yoga writers, says something like, the reason we do hard yoga poses is because it's a tool for meditation, 'cause it amplifies a wandering focus.

'Cause if you're trying to meditate just seated and your focus wanders, you won't notice 'cause your focus has wandered. But if you're in a hard pose and your focus wanders, suddenly you wobble, right? And you feel it's a, it is so, So a lot of, a lot of the times, a lot of games, there are deception games where all the kind of normal, like, board play is taken away from you, and all you have is to stare at someone in the face and try to read their face. There are other deception games where you're not even allowed to look or talk to other people.

I'm thinking of The Mind. Yeah, yeah, you're moving stuff around. Well, The Mind's a cooperative game. It's something you're moving stuff around on the board, and you're trying to signal and deceive people by, like, like showing, and each of these things like focuses your attention on one particular modality of the world. And I think it like, it like refines it. And I mean, I think we, hopefully it's clear that like the downside of this is if the world says, like if my university says, what matters is student graduation rates, not, that's what we measure.

And we don't measure happiness or wisdom or ethical growth. We just measure graduation rate. Then the entire institutional attention becomes hyperfocused only on those features that immediately poop out lock-in, a measurable outcome. Yeah, lock-in is like— lock-in is such a useful term now. It's like, this is— scoring systems can be— give you the most beautiful part of lock-in and the most soul-deadening, society-destroying parts of lock-in. Speaker B: What's the difference between recognition and perception? Speaker A: Oh my God. Thanks for hitting that one. I don't know, this is, um, obviously very related.

This is from— I think it's from Dewey. Speaker B: Um, my favorite bit, just maybe as a prompt, is you say, uh, we recognize and categorize something, we stop. Perception keeps going. Speaker A: Yeah, yeah, this is, this is from Dewey. So one of the things he says is that— I mean, a lot, a lot of what, what this is really about is how we categorize things. Yeah. Um, and the clarity of our categorization system, like the whole point is the whole point of a fuzzy term, like interesting or rich is that, uh, you have to ask yourself when you do an activity, whether it's interesting, whether it's rich, you have to deliberate and fight and interpret.

Um, and the interesting thing about a lot of these other terms that are associated with metrics for reasons I'm sure we'll talk about later is that they're very mechanistic easy to apply, and so it's very easy to, uh, to stop. I mean, the example I've been thinking a lot about is the example of screen time, right? So if I, if I target— I want my child to be involved in creative or, or interesting apps, I have to make a complex decision. With screen time, I don't. It's automatic. But also, screen time is a lousy category, totally.

Lumps together, like, I don't know, my kid coding on Minecraft with the worst YouTube Shorts ever. Anyway, so I'm wondering, so the difference between recognition and perception is that in recognition, you apply a category and then you stop looking at the thing. The category is the end of thought. And with perception, you apply the category and that helps you look at it and you keep looking further and further. And I think of like, I don't know, like a version of this is I know people where if you do something odd, they look for an explanation for it.

And when they can put a name to it, they just stop thinking. They're like, "Yes." "Oh." "Check." "He's just goofing off." Or, "Oh, that's like, that's vacation." And then they stop thinking about it. They've categorized it and that's done. Perception is the ability to look at something, have a name for it, put it under a category, and then keep looking at it for its peculiarities and differences. I mean, one thing— Speaker B: You really see it. Speaker A: Yeah, one thing you might think about recognition is the problem of recognition is that categories are very abstract.

And it just assumes that when you, when you say like, oh, that's a coder. Oh, that's a business person. Oh, that's a Gen Zer, right? It assumes that that's all the information you need to know. Speaker B: Yes. Speaker A: And it stops. Yes. Speaker B: There's no more information here. Speaker A: Yeah. It stops at a very specific level of abstraction, typically a level of abstraction that's been established socially. And it doesn't worry you. I mean, I mean, you're You pegged this from the very beginning. Like a lot of— this whole book is about the puzzle of why scoring systems are fun in games and so soul-deadening in institutions.

And the answer is often that in games, we have a playful exploratory attitude where we keep looking. Not always. Speaker B: Yeah. Speaker A: But sometimes. Speaker B: Yes. Speaker A: And the big interesting puzzle is why the nature of metrics as they occur in large-scale institutions tends to promote this closed, dismissive vision that categorizes things very quickly and then stops looking. Speaker B: Playfulness and perception are maybe on some kind of continuum, like, or some kind of similarity of vector space. Speaker A: This is— okay, let me just vomit a bunch of associations at you because this is super interesting.

And, um, I haven't figured out all of this associational network, but the modernization I really like is Jerome Stolnitz's. What Stolnitz says is, in normal life, We have a very practical vision. We have a goal and we go through the world and we classify things according to our goal and we just stop looking at things and at features of things that aren't immediately related to our goal. It's very filtered vision. Speaker B: Which is almost animalistic, right? It's like evolutionarily— Speaker A: I think that gives animals a bad rap, man.

That's very corporate. Speaker B: I think that's— Ah, huh. I'm thinking of, I guess what I'm thinking of is like survivalist. Speaker A: Right, it is very survival. Speaker B: But it's not necessarily natural. To your point. Speaker A: I, I suspect that many animals play far more than many, uh, it's a good check, many modern whatever. Okay, then he says, Solnit says that, and this is his translation of the Kantian thought, that aesthetic vision is vision that is stepped back from purposes and goals. And so it's attention that roves freely over all the features of everything, open to whatever there might be there to find.

He actually has this great moment where he says, like, what aesthetic vision is, is you let the object take the lead and show you what there is to love about it instead of having your own goal. Right? Right. So this is like, this is network, like, where the, the, the hyper, the more hyper clear the goal and the focus ahead of time, the more your vision seems to be closed and dismissive and non-exploratory. The more you pre-specified what's important to you, And then there's this other thing, call it art vision, call it aesthetic vision, call it beauty orientation, call it play, where we seem to be, one of the characteristics seems to be a kind of openness of vision to newness.

Yeah, you'd be surprised. Like, try, try, why the fuck not? Right? Fuck around and find out, but good. Speaker B: What a nice lead into maybe a critical part of what you talk about, how games can allow us to explore this fluidity is, is the process and outcome stuff. Yeah. A couple of things, um, from you. In games, the value of the outcome is inseparable from the value of the process. In normal life, we struggle in order to attain some goal that we really want. In striving play, we adopt a goal to get the struggle we really want.

Really nice packaged, uh, bit there. And then finally, when I started trying to exercise, I had only the barest conception of what it could do for me. I didn't realize how much I would find in it, how much else I would find in it. I think we've talked about this, but maybe I'll ask again just in case there's anything else is like, what is— what about process allows us to maybe just what is the link between process and values? What about process allows us to sort of fluidly express values? Speaker A: I mean, I think, I think it's— this is going to harken back to something we said at the very beginning of the conversation, but I'm worried that that already adopts a modern frame that has crapped on processes too much.

So I think, I mean, okay, let's get, let me, I'll take, I'll go, I'll take a running, I'll take a few steps so I can take a running start again. One of the core ideas animating this book is Bernard Tuts' definition of a game. For Bernard Tuts, to play a game is to voluntarily take on unnecessary obstacles to create the possibility of striving to overcome them. So one way to put it, this is in the quote that you read, is that for Suits, the struggle and the constraints are an intrinsic part of the goal.

Speaker B: It's not the end themselves. Speaker A: Well, it's gonna— there's a space, there's some very— there's a little wrinkle there. So Suits says in practical life, what we care about is the outcome in and of itself. So if I'm trying to get to a particular spot in the city, I just want to get there. Any method will do. If I'm playing a game, if I'm running a marathon, I have to get there by prescribed means. I'm not allowed to take a taxi. I'm not allowed to take a shortcut.

It only counts as crossing the finish line if I did it a particular way. Speaker B: You have a great line in there, by the way, where you say like cheating in a cosmic sense. Speaker A: Yeah. Speaker B: Which is so good. Speaker A: So what this means is in games, there's some incredibly powerful connection between the struggle and the goal. Now, that's stage 1. I've added my own little wrinkle to this. I think in games there's 2 kinds of play: achievement play and striving play. Achievement play is playing for the value of winning.

Striving play is playing for the value of the process. Notice, though, that an achievement player in a game still cares about the struggle. They want to have won that struggle. Speaker B: Right. And they wouldn't cheat because it would, it would disqualify the achievement. Speaker A: Yeah, it would mean that they didn't do the— like, they want to win, but it doesn't matter Like someone that just wants to win the marathon is not going to take a taxi because then they wouldn't have won the marathon. But they still want to win.

The striving player, which is one kind of game player, one motivational state, is the person that wants to win for the sake of the process. Speaker B: Winning is actually just this thing that it's a constraint that has to exist for the process to be good. Speaker A: Yeah, exactly. So it's like, I mean, a lot of the times I think about like I think about how I play board games with my spouse. So my spouse and I are good at very different things in board games. Once in a while, we'll find a board game where we're matched, and then we'll have a delicious struggle.

And then I will find a strategy guide afterwards. And I think, here's the argument from the book. If there's, uh, if I'm an achievement player, there's only one logical thing to do. Read the guide. Speaker B: Win. Speaker A: Crush her. Right. Crush her. But I don't, because that would make the game boring. So what's interesting is, is galactically I'm avoiding making moves in life that would make it more likely to win. But during the game, I have to try all out to win, to have fun. So when I'm like kind of, I don't really care about winning because I'm not like reading the strategy guide, but in order to have the process I want, I have to try really hard.

Speaker B: You're taking on a form of agency. Speaker A: Yes, I am adopting a win-oriented kind of agency. To have the pleasure of an interesting struggle. Okay, let me go back to your original question. So you said, what is it in the process that helps us explore values? I think what I want to say is, the process is where all the values were in the first place, right? Like, it's only this weird delusion. Mm. Speaker B: That there are values without process. Speaker A: Yeah, I mean, this is just from Aristotle.

Bernard Suits, by the way, the game scholar I love, was an Aristotle scholar, attributes his notion of games very openly to Aristotle. What Aristotle says is that the value in human life comes from rich exercise of our capacities, our intellect and our body and everything and our social capacities and that outcomes, tools, resources that we make, they're useful insofar as they allow the exercise of the capacities. But in many cases, what we're trying to do, we're aiming at an outcome but the thing that is valuable is the activity, the process, right?

And then, and there are some, I have some theories about why we have somehow been persuaded that processes are unimportant and all that's important is countable outcomes. The products you make, the money you make, the increased measurements that are applied to your skill and not the actual, I mean, I mean, if I actually wanted to rack up the numbers of success in games, I would play intellectual games because I am physically mediocre. I'm a terrible climber for how long I've been trying to climb. Yeah, right. I cannot justify it in any outcomes-oriented way.

The only way to justify it is to think, no, this is valuable because I get to be moving, because I get to be— because the process of skill refinement, even if I never end up at most mediocre. The process of refining the skill is valuable in and of itself. I think my response to the question of what is it about processes, why is it that that's a place to explore value? My response is something like, that's where the value is in the first place. How did we get to think that you had to look in stuff and piles of things that you made for the value?

Speaker B: That there are values without process. Speaker A: Yeah, I mean, this is just from Aristotle. Bernard Suits, by the way, the game scholar I love, was an Aristotle scholar, attributes his notion of games very openly to Aristotle. What Aristotle says is that the value in human life comes from rich exercise of our capacities, our intellect and our body and everything and our social capacities and that outcomes, tools, resources that we make, they're useful insofar as they allow the exercise of the capacities. But in many cases, what we're trying to do, we're aiming at an outcome but the thing that is valuable is the activity, the process, right?

And then, and there are some, I have some theories about why we have somehow been persuaded that processes are unimportant and all that's important is countable outcomes. The products you make, the money you make, the increased measurements that are applied to your skill and not the actual, I mean, I mean, if I actually wanted to rack up the numbers of success in games, I would play intellectual games because I am physically mediocre. I'm a terrible climber for how long I've been trying to climb. Yeah, right. I cannot justify it in any outcomes-oriented way.

The only way to justify it is to think, no, this is valuable because I get to be moving, because I get to be— because the process of skill refinement, even if I never end up at most mediocre. The process of refining the skill is valuable in and of itself. I think my response to the question of what is it about processes, why is it that that's a place to explore value? My response is something like, that's where the value is in the first place. How did we get to think that you had to look in stuff and piles of things that you made for the value?

Speaker B: One of my favorite examples you use that links to this is the difference between a recipe and a dish. Do you want to talk? I think this comes from John Thorne. Yeah. You want to talk about that just briefly for the listener? Speaker A: Yeah. So John Thorne, who's one of my favorite food writers, who it turns out was a philosophy major as an undergrad. Speaker B: Some kind of link. Speaker A: Some kind of connection. Yeah, some kind of link. Has this marvelous distinction between a recipe and a dish.

He says a recipe is a dead thing, a writing down of how something was made by someone once, and a dish is a live thing, an idea of balance in a creative cook's head that gets remade anew each time. And one of the things, I mean, A, creative cooks who are making dishes are typically actually better cooks. This is, a lot of people, I think, my generation, your generation mostly cook from recipes and we wonder why our parents' generation was better. And it's because they don't have a fixed recipe. They're like adapting to.

Speaker B: You have a great line in the book where you say, you were mad that your mom wasn't giving you a quote unquote real recipe. Speaker A: Yeah, she was giving me this thing where she was like, you gotta taste this and you have to adjust and you have to taste this. Taste the pineapple and like see if it's sweet or sour today and adjust your vinegar and sugar. And I was like, this isn't real cooking. Give me the answer, Mom. Yeah, give me the recipe that I can follow.

And you know, of course, now that I cook, I'm like, no, that's the real thing. It's not a recipe. The recipe is not the real thing. But I think the reason this is related to processes is I think a lot of people, I've been really interested in this thing that people have that's like, the perfect, the perfect cookbook with the perfect recipe for the perfect dish. And what that often has you do is following something precisely and measuring things precisely, but it's been engineered so you don't have to make decisions.

And you do often get a good outcome, but it's a very fixed outcome. Speaker B: I think there's something profound in that sentence you just said that applies to much of what we've been talking about today. Yes. Speaker A: Yes, exactly. Speaker B: Which is the challenge. That's the trade-off is, man, it would be nice to have somebody make the decisions for me, to simplify things, to reduce the complexity and be able to get a pretty good outcome. Speaker A: Yeah, but let me, let me, so let's think about what you get and what you don't get.

'Cause I, I do think for me, cooking is the perfect metaphor. Here's what you get for a clear mechanical recipe. It's easy. You don't have to make decisions. You don't need any experience. If you follow it correctly, you will get a pretty good result and a semi-reliable result. And here's an important part. The more the ingredients are fixed, the more it'll be reliable. The more you're using the same canned tomatoes and the same flour that's been standardized and is stable, the more you'll get a reliable outcome. But it'll be kind of the same one.

When you cook from a dish, here's what you get. A, it'll take a while to learn. B, you will slowly over time develop the capacity to see the decision space and move around it to see when you can make it crispier or saltier or softer. C, you'll be able to adapt to changing ingredients and roll with the fact that the tomatoes today are really sour and not sweet. You know how to compensate for that. And 4, instead of being in the mode of rigidly following someone else's rules, you'll be constantly engaged in your senses and making decisions out of your senses of tasting, being something like, mm, that's good, but it could use a little bit more.

You'll be engaged in that process. Speaker B: You might enjoy the cooking. Speaker A: You might enjoy the cooking. Speaker B: The funny thing about all this too is, when I was hearing you list the pros and cons of the first one, is the most valuable, one of the most valuable parts of the recipe is that you're way less likely to waste the food and your time. Speaker A: Right. Speaker B: Goes back to what we talked about earlier. Yeah. Speaker A: Yeah. Speaker B: We're so afraid to waste. Speaker A: I love that.

It is, there's a perspective from which, oh, you'll get it right each time. You won't waste something. There's another perspective from which you could have had a lovely hour being engaged and making decisions and being free with your senses and tailoring something to yourself. But instead you spend an hour following someone else's rules. Speaker B: Being a robot. Yeah. You don't get to cook. You don't have to cook. You get to cook. Speaker A: Yeah, I mean, Jon Thurn says this. He says something like, we have persuaded ourselves to turn into the restaurant mindset where we've turned ourselves into our own menial laborers and we go into the kitchen, close the doors, and follow the recipe precisely in order to have a guaranteed good outcome.

Where instead we could invite our friend into the kitchen, cook together, get a little drunk together, make decisions together, taste together, and the outcome might not have been perfect. Speaker B: But we lived. Speaker A: But you lived! You did the thing with the person. And the thing— Speaker B: We were there. Speaker A: And we have somehow been persuaded that the value isn't there. Speaker B: We've covered this a bit, but I wanted to hit it briefly. You talk about object beauty and process beauty. Speaker A: Yeah. Speaker B: Uh, you say in games, the beauty shows up not in the game, but in the player.

Game designers work a step back. They shape the general contours of our action, not the precise details. I know you've also done a lot of work on aesthetics broadly. Um, and aesthetics come up in bits and pieces. You talked about a little bit with the rock climbing or maybe the beautiful experience of cooking. Why, how do we underrate the virtues of aesthetics? Right. Speaker A: And we have somehow been persuaded that the value isn't there. Speaker B: We've covered this a bit, but I wanted to hit it briefly. You talk about object beauty and process beauty.

Speaker A: Yeah. Speaker B: Uh, you say in games, the beauty shows up not in the game, but in the player. Game designers work a step back. They shape the general contours of our action, not the precise details. I know you've also done a lot of work on aesthetics broadly. Um, and aesthetics come up in bits and pieces. You talked about a little bit with the rock climbing or maybe the beautiful experience of cooking. Why, how do we underrate the virtues of aesthetics? Right. Speaker A: I mean, I think this is, this is a duh with games.

It's a double underrated, right? A, we're underrating aesthetics, and B, we're underrating the aesthetics of doing instead of objects. But I mean, I don't know, like, we are in the world where people that are really good at optimizing industrial processes make a ton of money, and that people have soaked their soul into making completely beautiful, moving, emotional, personal indie comics can, like, barely survive. I mean, as, as a world, we underrate it. And I think— I mean, my suspicion is it's because the aesthetic value is one of the harder things to count in an objective way.

There's not a good metric for aesthetic value, and I don't think that's an accident. It's because whatever aesthetic value is, it is by its nature subtle and variable. Speaker B: And it's also not recognition, it's perception. Speaker A: It is. I mean, yes, it is. It is. Aesthetic value is about the value of perception. And here's the thing about perception in that sense: it is slow as fuck. If you want to be really efficient at hitting some simple target, you should be a recognizer and not a perceiver, because you'll move quickly, you'll ignore everything that's irrelevant, irrelevant, and then you'll be able to optimize for your target.

And that is great as long as there's nothing of value in what you threw away and decided to ignore. Speaker B: And it's also not recognition, it's perception. Speaker A: It is. I mean, yes, it is. It is. Aesthetic value is about the value of perception. And here's the thing about perception in that sense: it is slow as fuck. If you want to be really efficient at hitting some simple target, you should be a recognizer and not a perceiver, because you'll move quickly, you'll ignore everything that's irrelevant, irrelevant, and then you'll be able to optimize for your target.

And that is great as long as there's nothing of value in what you threw away and decided to ignore. Speaker B: You mentioned earlier autotelic, which is a wonderful word, um, kind of one of the more compelling philosophies for like how to live, finding love for its own sake, finding your passion. You, you actually earlier reacted to my willpower comment about maybe it being a little unrealistic, right? Naive or idealistic. We aren't— Suits writes about a theoretical future utopia where we live in a world of abundance. We have— we live in a pretty abundant world, but not a profoundly abundant one.

Great things are clearly not always playful. You do all kinds of things that suck and are hard to get to, either whether it be the aesthetic process you want or outcomes that are important. And yet I think like aspirationally, we all hope to get a little closer to— me doing this now is a little closer to things I— to the autotelic than things I've done in the past. I'm curious, like, how you've— what your relationship in your career has been to this sort of like finding the love and the joy and the internal motivation with also managing the real messy external things.

Like, is this just a thing we strive to until we die? Is it like— I think people out there want to believe it's incrementally more possible. Perhaps the answer is not to naively think you can just purely be autotelic, But right, I think you're kind of asking me about whether technological progress is good. Speaker A: Is that what you're asking, or are you asking— Speaker B: it certainly leads into what we'll talk about next. I don't know if I, I, I, I suppose I'm maybe more asking just for a personal reflection on— a friend of mine who I interviewed, he has this frame that's inspired by Christopher Alexander, this idea of unfolding into a life that fits you.

Yeah, um, Kevin Kelly talks about, uh, don't be the best, be the only. The goal of life is to become yourself by the time you're on your deathbed. Yeah. A playful orientation to life, a way of finding beauty. All this stuff we just spent the last hour talking about certainly feels kind of the way to directionally how to get there. And I'm curious, as someone who is spewing these ideas in a profound way and also has to live in the messiness of being a professor and all these, like, is it just— is that just the struggle?

Like, how do you relate to this? Speaker A: I mean, the I mean, every profession has its grind, and you got to do the grind. And the, the question is whether you devote yourself entirely to the grind or whether you make space for— I mean, my, my, my career through philosophy was really— it's like, this value capture stuff is in part just coming out of me pulling myself out of a bad trap in my own career. Like, I went to philosophy because I loved And then the same thing happened as everywhere else.

I went to grad school and I got the metrics in philosophy. There's like, you know, status rankings for universities and status rankings for journals. And you're aiming at getting a lot of journal articles published in highly ranked journals. It becomes really clear how you would game that out, which is to write fair— to hyper-specialize in a small domain, write very technical small move articles and, like, get published by being a super specialist. And I should also say that a lot of really good work happens that way, but that path made me almost die of boredom.

But I was doing it. I was walking that path. I went, in the course of my professionalization, from someone who was, like, deeply excited about philosophy to somebody who, by the time I left high school, I mean, by the time I left grad school, I was like grimly doing philosophy and I hated— I like didn't look forward to it. I had to work on things I wasn't interested in. I was writing things I wasn't interested in. And like, like I had to have a dark moment of the soul. And I think I was actually saved, I don't know, by my impatience and my intolerance of boredom where I was just like, I can't do this anymore.

I have to do something else. And now, I mean, I mean, still, like, I mean, it's really fun here to talk here. And there's this fantasy that you might imagine where I spent all my life talking about— I mean, I get maybe, you know, at best a quarter of my life to think about this stuff. The rest of the time, it's administration, it's teaching, it's grading. It's like going through policy changes in the university to figure out if there's like some horrible trap that's been laid for us by some fund— like, it's— there's, there's a lot of grind, and I think you always have to do the grind.

But a previous version of myself, instead of like carving out this little spot where I could do what I wanted, like threw the rest of me into the grossest part of the grind too. I mean, is that— is that— does that answer the question? Yes. Speaker B: Um, but what a privilege to have the 25%. Yeah, what did— Speaker A: I mean, I, I will say, like, getting 25% of my life to think about about this junk is like pure play. I recognize that I'm one of the luckiest people in the world that I get to like just play and roam weird-ass ideas for some small part of my life.

Speaker B: We've talked around it a bunch and we already talked about the value capture stuff. I think the best place to start is metrics and the reason maybe it's, it's particularly relevant for me. I think the world I've spent a lot of time in meaning the tech and business worlds particularly, they have a classic kind of guiding principle: measure what matters. Of course, the implication of doing so is that we tend to only value the things we can measure. A few excerpts, choice excerpts from you in the book on metrics.

Metrics are technology that standardize attention. Data is engineered information and metrics are engineered values. Public metrics get rid of intuition. They force us to justify ourselves in the cold light of general comprehensibility. They kill opacity. And finally, scoring systems don't just discover a convergence that was already there. They produce convergence. There have been many benefits to living in a quantified world. I think we are— speed of progress, our collective understanding, collaboration, all these things. And yet you You basically spent a third of this book just ripping into the ways that metrics are ruining us, for lack of— maybe that's too strong a language.

Speaker A: Why? Speaker B: Why can't we tolerate? Why can't we just tolerate? Maybe to go back to the first part of the question or the conversation, why can't we just tolerate a quantified, metricified world at a global level and leave the subjective value, qualitative stuff for our personal life? Speaker A: I mean, that would be great if we could do it. And I think the worry is that there's this constant intense suction. We're constantly being— I'm not saying get rid of metrics. I'm not saying metrics are bad. I mean, metrics are clear, comprehensible, accessible, and portable.

And we can unpack all of what that means in a bit. But that's good for a lot of things. And if we just treated them as these simple, low-quality but useful proxies that were usable in limited ways as limited heuristics, as like guidance mechanisms for large-scale activity. Great. Cool. But instead, what we get, we find over and over again, there's lots of empirical evidence about this, is that, um, When you put a metric in a space, everyone starts to care about it and hyper-orient to it. I mean, here's a really interesting example.

We all know that BMI, body mass index, is a terrible health measure that varies from person to person. It was originally not, I mean, it's been horribly abused. It was originally proposed as a useful proxy at the population level. So BMI, I mean, we all know that people, some people are perfectly healthy at high BMI, some people are perfectly healthy at very low BMI, right? It's this huge personal variance. BMI was originally introduced as an epidemiological measure to see like, oh, if you have a whole population, a whole country, and suddenly there's a huge BMI shift, that's probably a sign that something's going on.

And it works great for that as a rough first proxy at the population scale, looking at national populations and shifts in nutrition for national populations. It's a way to identify among our like food— large-scale food deserts. You can use it for that. But of course, what we find is people, once you get that number out there, tend to hyperorient towards it. Speaker B: It's like a personal scoreboard for them. Speaker A: Yeah, it becomes a personal scoreboard, and its proxiness is lost. It's— people forget about the fact that it's this just really rough population-level measure.

And I think that is the worrisome thing. I mean, the thing you said that I really want to talk about is this measure what matters. I think, I mean, I'm going to vomit forth a lot of bad examples of metrics. And I think the standard response is, oh, those are just bad metrics. Let's fix them and get better metrics. And the thing that I'm worried about, the thing that I spent a lot of this book arguing, is that metrics are by their nature unable to measure certain things. That metrics— not the metrics are bad, but they're very good at measuring very particular kinds of things.

Really roughly, there's going to be a lot more to say about this, but they're good at measuring are things that it's easy to count together. The things where everyone can recognize the borders, everyone can pick out the same things and count them in the same way. That is very— so lifespan measured in years, easy to measure. Whether or not some intervention leads to death or not, or save lives, easy to measure, right? Changes in graduation rate, that's just counting how many semesters a student gets through and whether they pass, easy to measure.

Another, I mean, I think another example, uh, one of the things that's really interesting in the history of attempts to diversify various institutions is early people in these efforts, we're always like, we need to diversify among all these dimensions. What this should not become, please God, don't let it become a quota where you need a certain number of women or a certain number of minorities. And then years down the line, because that's— because diversity along lines of intellectual style, creative style, background, cultural background, that's very hard to measure. Number of women hired, very easy for everyone to measure.

Together, right? So, so the worry is that the basic intrinsic nature of metrics is very conducive to targeting some things and does it really well. Like, there is no accident that, uh, that large-scale data collection systems have given us miracles like antibiotics, because antibiotics lead to a highly measurable result. Bacteria goes away, you stop being sick. But there are whole other swaths of human life, and here I want to put art, beauty, wisdom, happiness, richness, connection, friendship. All these things are very hard to measure. Speaker B: But also critically, I would add, like, as you talk about in the book, health.

Yeah. Like, I just, I think it's important to acknowledge, like, art, people might be like, oh, but there are a lot of things that are really important, even if you view them as not that subjective, that apply. Speaker A: Yeah, no, I think this is right. We should navigate to health last. I think it's one of the trickiest examples, but I think one of the things I'm really concerned with is when you have something really rich, like flourishing or well-being or even physical health, and then you have near it a simplified proxy, like how long your life was or how low the heart attack rates were, and that proxy begins to capture our sense of health and then minimize, and then we start forgetting about the other stuff.

And like, I mean, again, it's not that, it's not that, that, lives lived isn't important, and it's not that we can't target it. It's like in the war of trade-offs, what the metrofied world seems to do is get us to hyperfocus on what's easy to count at together and kind of like drown or shout out— yes, the subtler, quieter, more variable things. Yes. Okay, now let me, let me give you— I, I think you're teeing me up for the vomit, so let me give you the vomit. So, um, basically Basically, when I was trying to figure this out, I was basically, I spent a lot of years trying to figure out the question of whether there's something intrinsic about metrics that made them, institutional metrics that made them hard to, made it really hard for them to capture a lot of what was really valuable for human life.

And I found a bunch of scholarship that really helped me. Two key figures here are Theodore Porter and Lorraine Daston. So Theodore Porter is a historian of quantification culture. For the geeks among you in philosophy, he was deeply influenced by a philosopher of science named Ian Hacking. And what Porter ends up trying to figure out is why politicians and bureaucrats become so motivated to justify things quantitatively, even when the quantitative measures are obviously bad. And his answer is to think about the two different kinds of knowing. He thinks there's qualitative knowing and quantitative knowing.

Speaker B: Ways of knowing. Speaker A: And he says that qualitative ways of knowing are rich, open-ended, context-sensitive, dynamic, but they travel really badly between contexts because you need a lot of shared background to understand them. And then he says quantitative ways of knowing, and here, big asterisk, we're not talking about quantification in principle. We're talking about institutional quantification. We're talking about how bureaucracies and large-scale organizations count. He says the way that institutional quantification works is we identify a context-invariant kernel, a little nugget that everyone understands the same. And we create this by removing high-context detail and so create something that's portable that everyone can understand.

And now we can all understand what each other means by this single thing, and we can all collect into it and it can aggregate. So my standard example from my life is qualitative assessments are the long paragraphs I write in response to student essays that can talk about their relative originality or clarity. It can assess what they're doing in particular. It can pivot based on what they want. It can, on the person that's more creative, I can focus on their creativity and also, right, it can do all kinds of things.

Speaker B: Really meaningful to that student. Speaker A: Very meaningful to that student. Very meaningful maybe to other philosophers. Very hard to interpret for someone in the business department, the school department, law school, whatever, incomprehensible to someone hiring in Silicon Valley. And also crucially, it doesn't aggregate. And I think this is really important. Yes. And it's by nature, right? If a lot of different people are being open and responsive and context sensitive and issue thousands of different qualitative responses, right? Because of the fact, the very fact that these responses are dynamic and tracking different qualities, it means that they don't aggregate, right?

Each of the variability in the open-endedness is what makes them not able to aggregate. The fact that we fix the meaning of A, B, C, D in the letter grade and we hold it the same is what makes that information travel well and what permits automatic aggregation. So here's Porter's insight that I find so compelling and terrifying, which is that institutional quantification is socially powerful by design, and the way it's been designed to do so is that nuance Context and sensitivity have been stripped out of it. It is an artificially created, easy communication mechanism, and what it's missing is the source of its power.

Speaker B: That's the feature. Speaker A: Yeah. Speaker B: It's not a bug. Speaker A: It is the feature and the bug. This is, this is the trade-offs view, right? It is, it is like, this is, I mean, this is literally the thought that keeps me up at night, that this is the thing that gives it social power. Is its very insensitivity. Speaker B: Yes. Speaker A: So that's stage one. So that's something that— so, so what is blotted out? Any kind of value that requires a lot of context to understand or a lot of experience.

Speaker B: It's systematically removed. Speaker A: It's systematically removed, right? Okay. That's one. That's one. The other— Speaker B: Here's Lorraine. Speaker A: The other main lesson is from Lorraine Daston. Lorraine Daston is this incredible intellectual historian, one of the most important intellectual figures in the last, like, 100 years. She has this incredible early work about the nature of objectivity and how it changes. And you would be so interested in this. And this book that really basically broke open the secret heart of things for me on rules. And she says that, and what we're talking about when we're talking about scoring systems and metrics is rules for evaluation.

They're rules for counting. They're rules for saying, here's what we pay attention to and here's Here's what makes the number go up. It's rules for what counts. So she says there are different conceptions of rules and older conceptions of rules are— she says the dominant older conception of rule was what she calls a principle. And a principle is an abstract generalization that admits of exceptions and requires discernment and judgment to apply because you need to know when you might be in an exception case. Speaker B: Mm-hmm. So the exception proves the rule kind of structurally.

Speaker A: I, I maybe— I have never understood the phrase the exception proves the rule. Speaker B: I think, I think the essence of the, the point of it is that when you find an exception, it helps you model that the rule is almost always typically taken. Speaker A: Right, right. I get that. I mean, one way to put it is, so one of my favorite examples of a principle is in creative writing. I learned show, don't tell. Yeah, yeah, yeah. And people break that. But also, if you understand why they break it and when, you will understand why the rule generally holds.

Yes. And also, I need to break it. Speaker B: And the point isn't to throw out the rule. The point is that the rule should hold until it doesn't. Speaker A: Right. And there's no mechanical way to say that. You have to get the spirit behind it. It's a vibes thing. Exactly. Speaker B: I mean, Wisdom. Speaker A: In some sense, wisdom is vibes. Okay, that's the next paper I'm writing. Wisdom is vibes. I mean, exactly. That's exactly the point, right? So— Speaker B: That's a principle. Speaker A: That's a principle.

Second kind, she says, is a model where, like, basically a role model. Like, so she says the rule of Saint Benedict was just the person Saint Benedict. To rule yourself that way was to think about what they would do in that situation. Speaker B: Ah, okay. Speaker A: So both these rules require judgment, expertise. Speaker B: Every single time. Every single time. There's no automatic way to apply it. Speaker A: Yeah, there's no automatic way to apply, like, you know, what would Jesus do? Exactly. Um, uh, because it's, because the model, the roles are often complicated and subtle.

And as a result, those two have some travel and some scale. Speaker A: Yeah, there's no automatic way to apply, like, you know, what would Jesus do? Exactly. Um, uh, because it's, because the model, the roles are often complicated and subtle. And as a result, those two have some travel and some scale. Speaker B: There are principles there, but like they are harder to repeatedly scale. Speaker A: Right. You need to teach For someone to really learn show, don't tell, they have to learn it in a context. I learned to apply it in a context over several semesters in a creative workshop.

Speaker B: Apprenticeship, whatever. Speaker A: Yeah, it's the kind of thing that travels exactly in an apprenticeship culture. Speaker B: Yes, yes. Speaker A: Then the third kind of rule, she says, is an algorithmic rule or a mechanical rule. And she says this is something that's meant to be applied unthinkingly, automatically, with no exceptions, exactly as written. And then she says the thing that I found to be utterly mind-blowing, which is she says, people thought that mechanical rules and algorithmic rules arose with computing machines, but they didn't. They arose about 150 years earlier in an attempt to cheapen labor so you didn't have to hire experts who had judgment.

You could just hire equivalent, you know, basically— Speaker B: Making labor fungible. Speaker A: They make labor fungible. They make it so you can hire anybody and fire anybody because the rule's been made explicit. So I mean, again, think about like, like recipes. McDonald's has mechanical rules, which means they can hire anybody and slot them in and fire anyone. Speaker A: They make labor fungible. They make it so you can hire anybody and fire anybody because the rule's been made explicit. So I mean, again, think about like, like recipes. McDonald's has mechanical rules, which means they can hire anybody and slot them in and fire anyone.

Speaker B: In Korea, in Mexico City, in LA. Speaker A: Right, doesn't matter where you are. And note also, it works particularly well when you standardize the inputs, when you standardize the bread and the flour. Speaker B: Yes, yes, yes, yes. Speaker A: So in that case, what it is to be a mechanical rule is to be a rule that's applicable consistently by anybody. Speaker B: And when you say mechanical rule, you mean algorithmic. Yeah, same thing. Speaker A: She, she shifts back and forth between them. In my book, I use the term mechanical just because I think the term algorithmic has already shifted in its use a little bit.

Speaker B: And I think it also harkens back to the incentive stuff we were talking about a little bit earlier, which is when values and incentives combine, you get mechanical value sets. Speaker A: You get, you get something mechanical. Speaker B: Mechanical. Speaker A: So here's the next way to put it. I mean, I should say one more thing. I think you might find— I think you'll find this interesting. When you're talking about this, and a lot of her examples are mathematical, people freak out because they're like, wait, mathematics is by its nature mechanical.

And I think you have to understand how much of mathematics is not mechanical. So a lot of the times, so in many cases, what you That is a complex choice of which procedure or formula you're going to apply. You have to decide, am I going to do statistics? Am I going to do Newtonian mechanics? Am I going to do modeling? Speaker B: They might be mechanical within those. Speaker A: Right. It might be mechanical within those. So here's my— maybe here's the easiest example. I've been trying to find an example here for a while.

So let's say that you want to split a pie in half. What methodology do you use? You could split it by weight. You could split it by angle. You could split it with the eye cut you choose. Speaker B: Which is so wonderful. Speaker A: Right. And each of them is a different— so by weight is good for nutrition, like if you're counting calories. By angle is good for visual appearance. Eye split you choose is good for a sense of equity and fairness between two kids. Each of these is a different procedure.

And the point is, there's actually— there's not not. Here's another way to put it: half is kind of already itself a subtly complicated thing, and half by angle is different from half by weight is different from half by deliciousness or appealingness, right? And so there's a complex choice of procedure. But if you mechanize it, then— Speaker B: by the way, if we lived in a nuanceless world, a detailless, or a world of perfect detail, you could do— you could mathematically figure out half of a circle, but no pie is perfect.

Introducing all of that, right? It's such a good example. Speaker A: This is— I mean, it is. If things— the more— I mean, this is gonna— this is gonna point to the stuff we're gonna say later, I think. But the fewer complex overlapping details there are, the more everything is evened out and the same. If all pies were completely identical, this— and there was no variation texture in them, there wouldn't be a problem. Yes, but they're lumpy and delicious, like people. Pies. People are like pies. So, um, not being delicious.

Speaker B: Yeah. Speaker A: So here's the second stage. What metrics typically— not always, but typically— prefer mechanical rules for counting, which means that they tend to recognize differences between things that are easy for anyone to recognize and highly accessible, and they tend not to pick distinctions between things that require high discernment. So one, I mean, one example is, I mean, this is a very complicated example. And it also, this is an example I find interesting because it tells us that mechanical procedures are sometimes great. So you might think that the right to vote is tracking something really complicated like intellectual and emotional maturity.

But that's something that requires a lot of discernment. So we offer a mechanical rule. Speaker B: Here's your age. Speaker A: 18. And 18 does not track intellectual maturity. Speaker B: We have chosen inside of choosing 18, we have made a set of compromises around it. Like, this is the best we can do. Right. Speaker A: And in this case, I think it's totally great that we make that compromise, right? We make, there's a case where the cost of not getting it exactly right to intellectual maturity is lower and the cost of bias is so high.

But it's not always like that. Speaker B: Right, right, right, right. Speaker A: Here's something else. I think I'm getting more of a vibe of things you're into. Michael Endicott, who's a philosopher of law, has this great moment where he says, when you're switching between discerning judgment and mechanical judgment, you're actually trading off between two kinds of arbitrariness. Speaker B: Right, right, right, right. Speaker A: Here's something else. I think I'm getting more of a vibe of things you're into. Michael Endicott, who's a philosopher of law, has this great moment where he says, when you're switching between discerning judgment and mechanical judgment, you're actually trading off between two kinds of arbitrariness.

Speaker B: Yes, I remember this. So good. Speaker A: With discerning judgment, you let in the bias of individual bias. Speaker B: Yes. Speaker A: With mechanical lines, you shut that out, but you introduce instead the bias of arbitrarily sharp lines. Where things are fuzzy and complicated and gray. Speaker B: What a profound example that it's— that, that example travels so wide. Speaker A: It's— Speaker B: yeah, no, I mean, we are, we are deluding ourselves into thinking that one example, one choice is arbitrary and the other is objective, right?

Speaker A: This— I mean, this is over and over again where I've ended up thinking about metrics is not metrics are bad, but there's this complex set of trade-offs and costs, and we forget we have a fantasy that there's not a trade-off. And in this case, what we're actually talking about is the trade-off of accessibility. And you can see it back in, it's like the recipes trade-off again, right? If you make a procedure more accessible, and you make everyone follow that procedure, you also cut off expertise and sensitivity. Speaker B: Yes, yes, yes, yes.

Speaker A: And sometimes you want to do, sometimes it's worth it. Speaker B: I want to talk a little bit about elegibility and legibility, trust on that note maybe. And you talk about this is kind of one of the core dilemmas we have in this, like, world where we have a huge world. Science is really complicated. You have amazing work on conspiracy theories, which we'll have to save for another time about how what's so appealing about them is that they make the world, like, fit into your head. But in the real world, there's so much complexity we have to specialize.

You say a few, a few bits I love. First off, from the outside, posers and visionaries can be awfully hard to distinguish, which maybe perfectly illustrates almost the problem. And then you say you have this great section section on transparency is surveillance. You say, we limit the harm that bad and incompetent people can do, but we also limit what good and competent people can do. Transparency leashes both kinds of people, forcing them all to operate within the public's comprehension. Back to accessibility. And finally, we often assume that expertise is just technical.

Experts are there just to run the machinery, like the McDonald's people, the, the fungibility. But the goals and values guiding it all are always obvious and accessible to everybody. But this is a mistake. Expertise involves Seeing more deeply into what our true goals should be, grasping the subtle values of the terrain. The whole reason you go to a doctor is that they understand things you don't. Like, this is, this is a profound problem that, like, I don't think has obvious answers. But I do think, like, at root, it's about the success.

It's almost about— we were talking earlier, like, how much we can compress and how much we can make accessible. Like we are at an all-time low in institutional trust. Yep. Um, and so like the— I, I guess the challenge is like, to go back to all the metrics stuff, like there, there are all of these benefits we get from the— from living in metrics world. Yep. Um, and yet metrics world kind of, I think, makes us want to trust philosophers and academics and doctors less. Like, what is— maybe I know this is like a very long-winded question— what does trust need to scale, maybe, is my question.

Speaker A: And sometimes you want to do, sometimes it's worth it. Speaker B: I want to talk a little bit about elegibility and legibility, trust on that note maybe. And you talk about this is kind of one of the core dilemmas we have in this, like, world where we have a huge world. Science is really complicated. You have amazing work on conspiracy theories, which we'll have to save for another time about how what's so appealing about them is that they make the world, like, fit into your head. But in the real world, there's so much complexity we have to specialize.

You say a few, a few bits I love. First off, from the outside, posers and visionaries can be awfully hard to distinguish, which maybe perfectly illustrates almost the problem. And then you say you have this great section section on transparency is surveillance. You say, we limit the harm that bad and incompetent people can do, but we also limit what good and competent people can do. Transparency leashes both kinds of people, forcing them all to operate within the public's comprehension. Back to accessibility. And finally, we often assume that expertise is just technical.

Experts are there just to run the machinery, like the McDonald's people, the, the fungibility. But the goals and values guiding it all are always obvious and accessible to everybody. But this is a mistake. Expertise involves Seeing more deeply into what our true goals should be, grasping the subtle values of the terrain. The whole reason you go to a doctor is that they understand things you don't. Like, this is, this is a profound problem that, like, I don't think has obvious answers. But I do think, like, at root, it's about the success.

It's almost about— we were talking earlier, like, how much we can compress and how much we can make accessible. Like we are at an all-time low in institutional trust. Yep. Um, and so like the— I, I guess the challenge is like, to go back to all the metrics stuff, like there, there are all of these benefits we get from the— from living in metrics world. Yep. Um, and yet metrics world kind of, I think, makes us want to trust philosophers and academics and doctors less. Like, what is— maybe I know this is like a very long-winded question— what does trust need to scale, maybe, is my question.

Speaker A: Oh my God. Speaker B: That feels like the antidote to the metric. Speaker A: You, you, I, the whole reason we were talking about Daston and Porter is to understand what metrics miss about values. Speaker B: Yes. Speaker A: So what Porter teaches us is that large-scale institutional metrics typically remove high context. And what Daston teaches us is that large-scale metrics typically remove expertise. And they both in some way are about different kinds of sensitivity and specificity. They tend to emphasize the things that everyone can see consistently and recognize consistently.

So metrics world— Speaker B: There's no room for context. Speaker A: Yeah, there's no room for context. What metrics world, um, I mean, I'm experiencing— here's the simplest, dumbest version of this. Our department was just cut again, like the philosophy department being defunded in favor of AI programs in the business school. And part of it is because we've been labeled an unproductive department. Even though lots of people, like highly ranked department, you know, lots of important publications. Speaker B: Lots of waste. Dare I say it? Speaker A: Well, actually, here's the interesting thing.

The reason is that the measure of productivity in my university has become grants, research expenditures. Speaker B: Right. Speaker A: Right? Speaker B: Right, right. Speaker A: Philosophers don't need grants. There's a sense in which actually we're very efficient You just need a book budget and a little, like, you don't need a lab, but because the metric has become research expenditures, and that metric can't make the contextual shift of being like, this little group over here. Speaker A: Right? Speaker B: Right, right. Speaker A: Philosophers don't need grants. There's a sense in which actually we're very efficient You just need a book budget and a little, like, you don't need a lab, but because the metric has become research expenditures, and that metric can't make the contextual shift of being like, this little group over here.

Speaker B: Shouldn't be measured by grants. Speaker A: Yeah, yeah, should not be measured by research expenditures, 'cause you don't need grants, right? That's an oversimplified example. Speaker B: Sure. Speaker A: I think maybe an, A more interesting example. The reason I'm worried about this is because this is, this is the answer for why metrics can't capture values because values are context sensitive, highly expert, right? And metrics by their nature target what is portable, consistent, and accessible. Speaker B: Yes. What is legible. Speaker A: Yeah. And another really example that I found really fascinating here is the example of Charity Navigator.

Charity Navigator was a nonprofit— is a nonprofit watchdog that was designed to tell us which charities were good and which charities were bad, which were good and which were wasteful. Speaker B: And it's, by the way, to go back to the posers and visionaries, like the root of this, by the way, is that there's a whole bunch of people, if you don't quantify the world, will abuse systems, right? Speaker A: This is exactly— so the whole reason we want transparency is there are fakers out out there, right? And then we impose a method of transparency that makes them, that tries to root out the fakers by seeing who can succeed on some publicly legible target.

But that will take out two groups of people. It'll take out fakers and it'll take out people who are trying to target something important. Speaker A: This is exactly— so the whole reason we want transparency is there are fakers out out there, right? And then we impose a method of transparency that makes them, that tries to root out the fakers by seeing who can succeed on some publicly legible target. But that will take out two groups of people. It'll take out fakers and it'll take out people who are trying to target something important.

Speaker B: That isn't quantifiable. Speaker A: But not legible or not easily quantifiable. In fact, another worry you might see is then the fakers will simply adapt and game. Yes. The very now clear— Speaker B: You have this great concept in the book of the gap, which is almost like the gap between what we can measure and what actually matters. Yep. Speaker A: The gap is the gap between what is easy to measure and what actually matters. And I think the Charity Navigator case is so interesting to me because for a long time what Charity Navigator used, and I was convinced by, and I'd let it guide my charitable giving, was a throughput rating.

So the throughput rating is Efficiency. Yeah, the ratio of how much money is given to the nonprofit versus how much it expends out on the other end, right? Seems good. As it turns out, it means that— Speaker B: Don't hire anyone really talented. Speaker A: Exactly. So it assumes that a nonprofit is like— Speaker B: Free research. Speaker A: Is just there to like redistribute resources and not to do internal resources, not to hire experts, not to make decisions. Right? So, but here's the interesting— here's why I think it matters.

I didn't emphasize as much as I should have in the book, but I think this is super interesting. In order to actually judge nonprofits' actual efficacy, you would have to understand the specific domain of each nonprofit. If you wanted to compare nonprofits that worked on housing versus nonprofits that worked on food, you would have to actually understand the complexity of how you improve an ecosystem, how you improve like nutritional delivery services. But throughput rating is a matter of accounting, and that's the same between each nonprofit. And so there is a single way to judge them all in an apparently objective mechanical accounting system.

Speaker B: Free research. Speaker A: Is just there to like redistribute resources and not to do internal resources, not to hire experts, not to make decisions. Right? So, but here's the interesting— here's why I think it matters. I didn't emphasize as much as I should have in the book, but I think this is super interesting. In order to actually judge nonprofits' actual efficacy, you would have to understand the specific domain of each nonprofit. If you wanted to compare nonprofits that worked on housing versus nonprofits that worked on food, you would have to actually understand the complexity of how you improve an ecosystem, how you improve like nutritional delivery services.

But throughput rating is a matter of accounting, and that's the same between each nonprofit. And so there is a single way to judge them all in an apparently objective mechanical accounting system. Speaker B: And do it efficiently and fast. Speaker A: And do it efficiently and fast. And so it highlights what is mechanical and similar, which is accounting, and it ignores what's actually important but highly variable. Speaker B: So how do we scale trust? Speaker A: To me, I think this is super interesting. The Charity Navigator example is super interesting to me because it's an attempt to scale trust or it's an attempt to get around the problem of trust by finding some Okay, here's the problem.

It was an attempt to eliminate trust. That's what— Speaker B: that's right. Right. Speaker A: Right. Speaker B: Which is, which is very different. By the way, trustless systems. I have a question later I wanted to ask you about markets. Like trustless systems are interesting and can be really valuable for the world, but they can't replace trust. Speaker A: To me, I think this is super interesting. The Charity Navigator example is super interesting to me because it's an attempt to scale trust or it's an attempt to get around the problem of trust by finding some Okay, here's the problem.

It was an attempt to eliminate trust. That's what— Speaker B: that's right. Right. Speaker A: Right. Speaker B: Which is, which is very different. By the way, trustless systems. I have a question later I wanted to ask you about markets. Like trustless systems are interesting and can be really valuable for the world, but they can't replace trust. Speaker A: Right. This is, here's one way, one way to put it. Well, I was thinking about transparency metrics, a transparency metric, which is made to make institutions accountable to the rest of the world to see if they're biased or not.

They're trust eliminators, right? They try to, instead of trusting an expert about their specific domain of what's important, they look for some public way of counting the goods. But what that means is that they're now forcing institutions not to use their expertise about what's important, but to only focus and target. Speaker B: Only be automatic. Speaker A: Yeah, the simple, easily countable values, the simple, easily countable targets. Um, and my favorite examples of this was like when, uh, Congress put the National Endowment for the Arts under oversight because they were afraid of bias.

They started measuring artistic success by box office receipts. Speaker B: Yes, engagement. What a way to measure things. Netflix. Speaker A: Exactly, exactly. But that's their box office sales, ticket sales, uh, uh, page views, engagement hours. All of those are mechanically countable. So the problem is, here's one way to put it, the problem of the world is that there are different domains where people understand the special value of different things. And to actually access that, we need to trust people. Speaker B: Yes, engagement. What a way to measure things. Netflix.

Speaker A: Exactly, exactly. But that's their box office sales, ticket sales, uh, uh, page views, engagement hours. All of those are mechanically countable. So the problem is, here's one way to put it, the problem of the world is that there are different domains where people understand the special value of different things. And to actually access that, we need to trust people. Speaker B: Yes. Speaker A: But we need to trust people beyond where we can go, because that's the whole point of trust, right? That people are— Speaker B: And the point of specialization.

Speaker A: Right, and the point of specialization. I mean, the whole The whole paradox of transparency and accountability is the whole reason we want experts and specialists is because we don't understand them. And then we're like, but then you can only attempt to explain the things that we can understand, right? That's not possible. Like there is a tension between transparency, accountability, accessibility, and trust in expertise and sensitivity. There's another trade-off for you. So your question is how trust scales. I don't know. The problem is that I understand how trust works on small-scale intimate life.

I understand why it's hard to get trust in people at large scale and why we substitute things like metrics. And I understand why that creates an enormous degree of loss. And I don't have an answer. I don't have an answer, but let me tell you two things I find fascinating. There are two moments from my favorite texts that I've been obsessed with, and I think if I can understand them, then we will understand the heart of the modern world. One is from Theodore Porter, this quantification guy. And he says, because what data is, what information is, is understanding that's been a special— is a special mode of understanding and knowledge that's been pre-prepared to travel and be understood by distant strangers.

Speaker B: You even use the word engineered to do that. Speaker A: Right. Speaker B: Yep. Speaker A: Right. And then over, there's this other text I love. One of my favorite pieces of philosophy is Annette Baier's Trust and Antitrust, where she starts by complaining. This is a feminist philosopher from the, in the '80s. She starts by complaining against social contract theory. And she says, there's this mistake people make where they think that morality can be bounded on contracts, where contracts are envisioned as like voluntary agreements between free people. And she says, that's something only rich dudes in a gentleman's club could have imagined would be the root of morality.

Morality depends, begins in dependence and vulnerability and relations between parents and children and dependent. And she ends up saying that the heart of trust is vulnerability. And that part of the mistake is trying to secure that vulnerability perfectly. Because what it is to trust someone is to be vulnerable. Speaker B: Yeah, I need a contract to trust you. Speaker A: This is— okay, exactly right. Okay, this is where she's going. Okay, what she ends up saying towards the end of this beautiful article is she says the real reason social contracts are a weird place to build your morality is because it's a very specific metaphor, because contracts are a specific social technology to make fines and expectations explicit, to ease and secure one-off transactions between distant strangers.

Speaker B: Yes. Yes. Which by the way is beautiful. It's allowed immense scale, but the whole premise is actually not about trust. Speaker A: Yes. So, I mean, I kind of think if you can find— I think that Byers' comment about social contracts eliminating trust, uh, and using one-off transactions between strangers, and Porter's comment about how data information has been prepared and engineered to travel to distant strangers. Those are like two pointers to the heart of the modern world. Speaker B: Yes. Yes. Which by the way is beautiful. It's allowed immense scale, but the whole premise is actually not about trust.

Speaker A: Yes. So, I mean, I kind of think if you can find— I think that Byers' comment about social contracts eliminating trust, uh, and using one-off transactions between strangers, and Porter's comment about how data information has been prepared and engineered to travel to distant strangers. Those are like two pointers to the heart of the modern world. Speaker B: Well, maybe it's just the last thought. I guess my, like, my reaction to the scaling to trust thing would just be— and I'm sure you even talk about some of the challenges here from the velocity standpoint— would be like, we trust the other experts.

Speaker A: Yeah. Speaker B: Like, why? Maybe just quickly, like, what are the things that go wrong when we defer? Theoretically, the doctors should all regulate the doctors, right? That we run into the same problems you're describing even in those cases. Speaker A: I mean, the problem is that we have to trust experts from distant expertises. And then we have— I mean, this is— I was working when I was a graduate student. The problem I was obsessed with, which I think is still a version of the problem I'm obsessed with, it's a problem that's actually as old as Socrates.

The problem is how does a non-expert recognize an expert? And the dumb way to think about the problem is to think, oh, there's some class of special experts. But really, Most of us are non-experts in 99% of the world and experts in at most 0.01% of the world. So we're constantly having to recognize non-experts and figure out who to trust. But we're constantly having to overextend ourselves and become vulnerable. And then we try to secure it with hyper-accessible metrics. Speaker B: Yeah. Speaker A: Which imagine away the complexity they suppose that there's some easily accessible moment, some test for real expertise.

But I think the worry is if there's not a mechanical, easy test for expertise, then we're plunged in the, I think, the true awful existential dilemma of the modern world, which is that we are surrounded by people that are true experts and sensitives about forms of value and forms of life that we know nothing about, and we're surrounded by posers and fakers and exploiters. And the difference requires expertise as we don't have. Speaker B: The challenge of so much of this that I think maybe leads into what we'll talk about next is we want security, we want objectivity, we want answers.

We don't want to have to consider the possibility we might get scammed. Speaker A: Right. I mean, this is— I had this moment moment I was talking about this stuff, about trust and vulnerability, and I had a student from the back of my class, like big guy, tank top. He's like, this is why I never trust anybody. You can't trust any— like they might screw you over. You can never trust anybody. You always have to take care of yourself. And I was like, how'd you get to class today? And he was like, I drove.

I said, did you go on the highway? He said, yeah. I said, how many other drivers and car mechanics have you trusted with your life today? And he actually had a meltdown. Speaker B: Down. Speaker A: One of the things Annette Beyer says is that trust is so intense and deep that we, we forget how much we're trusting because trust to us is like water to a fish. We just swim in it all the time. So it becomes invisible to us. Speaker B: Down. Speaker A: One of the things Annette Beyer says is that trust is so intense and deep that we, we forget how much we're trusting because trust to us is like water to a fish.

We just swim in it all the time. So it becomes invisible to us. Speaker B: Are you an optimist in the cosmic sense? Speaker A: I don't know. You tell me. But does that make sense? But I think so. Sometimes I walk my students through this exercise of trying to figure out how many people they're trusting with their lives in this moment. Sitting in this building? And like, what it introduces is vertigo, because you suddenly realize how big your trust is. And you realize, and I think there's this fantasy that we can secure it and know for certain.

I mean, there's this, in philosophy, I think this is Descartes' fantasy. Descartes' fantasy is you could start over from the beginning and only believe in things you're sure by trusting only yourself. Speaker B: Yeah, if we just rebuilt the whole world, right? Speaker A: By the way, without science. Speaker B: Yeah. Speaker A: Um, funny, uh, again, this mentor, Elijah Milgram, in his book The Great Endarkenment, he— his joke is that he thinks the Great Enlightenment, um, undid itself because it started with the idea of intellectual autonomy and rethinking things, and that created so much science that intellectual autonomy became impossible.

Right. And that the idea that we can think for ourselves is an old, uh, out-of-date illusion. Speaker B: The best count— and this is a whole separate— you ever come across David Deutsch? The, uh, uh, it's like science. His, his articulation of good explanations, it, it maybe rhymes a little bit with your articulation of good science where you talk. Let me see if I can find it. You, I think you talk about it as being like, um, having a good error metabolism. Yeah, it's like something that's a sort of somewhat atomically verifiable by an intellect, like an intellectually reasonable person.

Maybe that's our best hope. And then otherwise we mix up— I mean, I, maybe what part of what I'm left feeling here is like on one hand holding a loose grip, which is just like actually objectivity is not something we're ever going to have. We are going to have trust. We are going to have failures and also trying to make more of the world have good error metabolism. Speaker A: Right. Okay. Speaker B: A lot there, dude. Speaker A: I think I have found the best tool to fuck with your mind.

Okay. Lorraine Daston's first book is about what objectivity means. And she ends up saying there are very different senses of objectivity and they mean very different things. And the notion of objectivity she thinks that we have settled on in the current era, modern era, is what she calls aperspectival objectivity. Objectivity, or what it is to be objective is to be a kind of fact that would be recognized no matter what person is looking and what kind of person they are. So in this case, objectivity and truth come completely apart. Objectivity is the land of highly accessible, consistent judgments, but that isn't necessarily— and there's some things that where it's easy for us to get objective about, again, the world of the easily countable.

And there's some things in which aperspectival consistency is incredibly hard, but they might still be important things. Speaker B: They might still be true. Speaker A: They might still be true. Right? So part of the, I mean, this is, this is the whole, I mean, the reason we're talking about all this stuff is because the dream of metrics is that by narrowing things down to entirely objective mechanical rules, we can secure our intellectual behavior and we can secure our judgments. So we will always know for certain we're right. Theodore Porter actually says the reason that bureaucrats and politicians reach for numbers is to avoid responsibility.

Right. Speaker B: Oh, it's so good. Speaker A: By not having to make a judgment or exercise their discretion, they take themselves out of the apparent stream of judgment, say like, it's It's not me, it's just the numbers. Speaker B: I don't have to trust you, we have a contract. Same thing. Right, right. Speaker A: It's a dream of, if all that was important was easy to count together instantly and we could recognize it, then we could be secure in making decisions together, right? There would be a mechanical method. But it's not.

You have subtle values that require context and sensitivity to detect, but you are so obsessed with the dream of security and so obsessed with the hope of objectivity that you will only reason using easily countable metrics, then you achieve security at the price of any sensitivity. Speaker B: Yeah. We have a little time left and I want to hit— I think this ties well into this last kind of section about the way that value judgments are hidden everywhere. Yeah. Which maybe is just— it's another thing adding to the point you were just making, which is the real lie of objectivity.

Speaker A: Yeah. Speaker B: Yeah. Well, I think first off, it's worth noting you have a great line. You say standardization may crush souls, but it also saves Lives. You are, you are decidedly not anti-progress, not anti-science, etc. And yet you say when we start using any technology, we're always outsourcing some of our values. Why are technologies not value neutral? Speaker A: Yeah, this is, this is because like part of this is the second attack on this dream of objectivity, which is that many of the metrics we think you think of, they look objective, but there's also a value choice hidden at their core.

So this is, this is this massive— this is, I think, a basic insight from the philosophy of technology and from a field called science and technology studies. So, uh, there's a presumptive view that seems really strong in our culture that tools, technologies are value-neutral. Yes. That, you know, people just make— scientists and engineers just make tools and just empower people, and then the people make the choices. Um, and this Sometimes once you look at the actual details, obviously wrong. So one of— so there's some classic examples. I mean, some of the easier examples are straightforward bias.

Like technologies can be biased in all kinds of ways. One of my favorite classic examples is Robert Moses and the New York bridges. Do you know this example? Speaker B: I know a bit about Moses, but I'm not sure I know this specific one. Speaker A: He, he, um. Managed to keep out what he perceived to be the rubbish from the good parts of New York by carefully setting the standard height for bridges and overpasses as slightly lower than the average bus. So buses— Speaker B: oh my God, right? Speaker A: So there's, there's an easy— that's an easy— that's like case one, right?

Speaker B: Right. Speaker A: To commit, like, so you can encode a bias. But maybe that's— Speaker B: let's back up for a second because, because just, just to say, like, the counterargument would be like, that's not a technology. Speaker A: Exactly. Speaker B: Maybe buses are, but yeah. So I was going to say decision. Speaker A: That's an easy first example, but that's not the real thing. So Langdon Winner, who's one of my favorite philosophers in this space, he has this beautiful article called Do Artifacts Have Politics? And he says, but he says, one of the interesting things is that technologies actually shape and push society into certain directions, often irrespective of what their designers and users hope So his example, one of his first examples is the printing press.

So one of the things that he thinks is really interesting is that oral communication is deeply decentralized. Like, you know, if I say something to you and you say something to them, there's no centralizing power, right? Like, each of us can change the news. Speaker B: Yes. Speaker A: The printing press, no matter the democratic and anti-elite hopes of its inventors, the printing press concentrates communicative power and communicative authority. Speaker B: It requires capital. Yeah. Speaker A: And whoever has enough capital to have a printing press. And then it's instantly demer— that's the official news.

So he thinks that— Speaker B: Yes. Speaker A: The printing press, no matter the democratic and anti-elite hopes of its inventors, the printing press concentrates communicative power and communicative authority. Speaker B: It requires capital. Yeah. Speaker A: And whoever has enough capital to have a printing press. And then it's instantly demer— that's the official news. So he thinks that— Speaker B: well, this is the challenge of technology too, though, is like so many technologies, they actually start this way and then they democratize. And so we can convince ourselves of these ideals of the, all the ways that will democratize access to power.

And yet this, this, this, you could jump way ahead to 2025. The slope of how artificial intelligence is adopted matters a lot, not just its ideals. Yeah, yeah. Speaker A: Anyway, so, so in a very abstract sense, like many technologies have world-shaping powers. In the specific case of metrics, one of the things I find really interesting is people think that metrics are neutral and objective, but metrics capture What— so to have a metric to count something, we need a cat— a categorization system, uh, to count it together, right? Speaker B: Yeah, counting, counting can't be value-laden, can it?

Speaker A: Right, counting can't be value-laden, can it? Um, so Jeffrey Barker and Susan Lee Starr have this great book called Sorting Things Out where they look at classification systems, and what they're really interested in is the interestedness of the classification systems that are the foundation decisions of data and metrics. So here's a simple example. What they say is every category, so we can't keep track of everything in the world. We need to reduce the granularity in order to store it and aggregate it. But there are decisions about where to reduce that granularity.

So a simple example, US Census has categories for Black, Caucasian, Asian, Latino. That is very interested in the difference between Asian and Latino and uninterested in the difference between South Asian and East Asian. It forgets the granularity there. Speaker A: Right, counting can't be value-laden, can it? Um, so Jeffrey Barker and Susan Lee Starr have this great book called Sorting Things Out where they look at classification systems, and what they're really interested in is the interestedness of the classification systems that are the foundation decisions of data and metrics. So here's a simple example.

What they say is every category, so we can't keep track of everything in the world. We need to reduce the granularity in order to store it and aggregate it. But there are decisions about where to reduce that granularity. So a simple example, US Census has categories for Black, Caucasian, Asian, Latino. That is very interested in the difference between Asian and Latino and uninterested in the difference between South Asian and East Asian. It forgets the granularity there. Speaker B: And by the way, that has seeped into how people believe about— like, we just say Asians, right?

Speaker A: We just say Asians. Similarly, they're really interested in medical record-keeping. So then they— there's this astonishing moment in their book where they look at the ICD-10, which is the classification manual that's the basis for mortality and accident statistics that are the— that are used for large-scale epidemiological and medical research. And they point out, for example, that in the falls category, there are separate codes for the following urban falls. There are different codes for fall from a balcony, fall from a stair, fall from an escalator, fall from a bed, fall from a commode, fall from playground equipment, fall from hospital equipment, fall from, right, there's about 10.

And then for rural falls, there's fall from a cliff and fall other, right? So you can read the interestedness. So metrics seem objective. Speaker B: Yeah, yeah, yeah. Speaker A: But they track— Speaker B: We have forgotten the value judgment that was made way back when. Speaker A: Right, we've forgotten. There's so many of these cases where we forget the value judgment that's made way back when. One of my favorite examples, this is a geeky example, but I suspect you'll be interested in it. A lot of Theodore Porter's book is about the history of the cost-benefit analysis.

And he notes that cost-benefit analyses look really objective, But at the starting points, there are all kinds of weird-ass interested decisions. So here's two examples. One of his examples is if you're trying to do a cost-benefit analysis of, say, how much you spend on a national park, you have to insert into your analysis the value to a visitor of a recreation day. You have to give, attach a number of dollars. Speaker B: Yeah, yeah, yeah. Speaker A: And then you set one. So it's like, you know, in 1914 they said it was like $0.14 per visitor day.

That's the value they're setting. Speaker B: $0.14 is the value of one person visiting a park. Speaker A: Yeah, right. And then you run that and then it looks objective at the other end, but one of the inputs is— Speaker B: and we just made up— we just made it up. Speaker A: We just made it up. It expresses our sense of valuation. My other favorite one, and I think this is one of my favorites. So, uh, one of the most important numbers in any cost-benefit analysis is the discount rate.

Speaker B: Okay. Speaker A: Do you know this? Speaker B: Basically, yeah. Speaker A: So the discount rate is the relative amount you discount the future compared to the present. Speaker B: How we— it's essentially how we keep the present— or excuse me, the future from being wildly overvalued. Speaker B: Okay. Speaker A: Do you know this? Speaker B: Basically, yeah. Speaker A: So the discount rate is the relative amount you discount the future compared to the present. Speaker B: How we— it's essentially how we keep the present— or excuse me, the future from being wildly overvalued.

Speaker A: Right. So by the way,, if you set the discount rate to zero, what you get is long-termism, right? And but— Speaker B: right, right. Of course. Yeah, you would all— yeah. Speaker A: 17th century economist and like Adam Smith worked this out. He's like, well, if we set the discount rate to zero, you get all these absurd effects for any minor change in the future through compound interest. Sorry, any minor change in the present will be justified because of swamping effects in the future. So you got to have some discount rate.

Speaker B: The present has little, basically no value, right? Speaker A: Yeah. So you have to set some discount rate because— set it at— there's no correct— we made it up, right? It is the discount rate represents a value choice about the relative value of the future versus the present. And then someone sets it at the bottom of your calculation and then it gets hidden. And then things look objective. Speaker B: By the way, you could, I mean, you could so easily imagine how arbitrary discount rates might affect our broad sensitivities for how much the future matters, how much, because it goes back to the adoption of technology thing.

Like, is it okay if we build this technology because in 20 years everything will be great, right? Or we'll have amazing abundance. And in the, so much of our thinking is we, it's almost like we're avoiding the messiness of these ethical questions. Speaker A: This is, this is exactly, I mean, that is exactly the goddamn point. So the phrase I have in my book for this effect, I'm currently calling it objectivity laundering. Like money laundering is you take dirty money, you pile on calculations. Here, you take a subjective choice and then you pile on calculations.

I think that's a good— I mean, the whole thought in the background, the opening thought for this book was something like, games are beautiful because they simplify things. For once in your life, you don't have to worry about conflicting values. There's a victory point scale. You know exactly how much things are worth. You know exactly who won. On. And it's so tempting to export that, simply oversimplify the rest of the world. Speaker B: Simplicity contained is great. Speaker A: Yeah, simplicity contained is great. And if you manage to convince yourself that your metrics measure, measure all that matters, matters, then you won't experience the tension of what you're missing.

You'll think, oh, it's easy. And then actually, you'll be much more efficient in achieving and optimizing for your metric because you don't get any drag from worrying about all the other stuff. All you had to do was delete from your vision everything else that was important. Speaker B: Maybe that ties into one of the last things I want to talk about, which is, um, many people in my audience are technologists. Um, I joked with you when we first met, you are a philosopher and think a lot about games, both of which are kind of like wildly low status, or especially games, but maybe philosophy too, in an area of technology that should almost certainly be learning a lot from, from those two domains.

Speaker A: Why? Speaker B: Why can't we do ethics from first principles? Maybe it's just a super simple starting point. You joked to me about that, and I think it's profound. Speaker A: Why? Speaker B: Why can't we do ethics from first principles? Maybe it's just a super simple starting point. You joked to me about that, and I think it's profound. Speaker A: That's a really intense question. Speaker B: Maybe a better question would just be like, what? What is your caution there to people who think ethics can be simple?

Speaker A: Okay. If ethics is about treating people well and fairly and doing it well, involve, then doing it well will involve deep attention to the particularities of people and their contexts and sensitivity to the emerging complexity of what matters. This is, I mean, this is again from Aristotle. I learned this stuff from Martha Nussbaum's version of Aristotle, which is like what practical wisdom is, is being soaked in the moral and value complexity of particular situations and being able to see all— Speaker B: It's perception, not recognition. Speaker A: Yeah, it is perception.

Exactly. It is perception. I mean, there are some abstract print things I could say that, like, morality, treat people well, right? But as an actual thing that guides action, if what actually matters to people, what actually hurts them, if what actually helps them is highly dependent on interaction with particular context, particular personalities, and particular values, then it's going to require require enormous sensitivity and context. And if you expect not just to have a general vague principle of morality, act well and be sensitive. Sure. Speaker B: Right. Speaker A: If you actually expect a decision procedure that will resolve ethical debates and you expect it to be mechanistic, then you will start to concentrate on those moral features that are easily countable.

Speaker B: Right. Speaker A: If you actually expect a decision procedure that will resolve ethical debates and you expect it to be mechanistic, then you will start to concentrate on those moral features that are easily countable. Speaker B: Yes. Yes. And you will ignore the others. Speaker A: And you'll ignore the What do you say to— Speaker B: we actually didn't talk about it. You give an example in the book that I love, which is you talk about how maps are value-laden as a technology as well, and how super simply maps have elevation because somebody made a decision 100 years ago for battles and they don't have sound quality.

And critically, the answer here is not to not use maps. The answer is to not participate in— not to not participate in the world. And so like like we have benefited so much from compounding and a ladder of abstraction, particularly in technology, benefiting from the work that others have done in the past, even if they were value-laden, right? Technology, I think to a fault, loves to solve for hero metrics and simplicity and solve for X. But like even for technologists who are mindful of the ethical thing, who want to build quickly and with impact and with, with global coordination, I'm like, what do you say to those people?

Like, part of this is maybe listen to the conversation, read the book. But like, if you, if you were to maybe a different way to ask this question, that's like a little silly is if like I could give you 30 minutes in a room with Sam Altman, Mark Zuckerberg, and Elon, what you would try to persuade them of, which I realize is different question than like thoughtful person who's listening. Speaker A: Don't give me that question. Speaker B: Okay. But what would you try to have them them. You even, you have another bit where you talk about reflexive control and part of, so much of what I think this is, is like remembering, remembering to put on a mindset that gives way to these things while still operating in the real world and benefiting from all of these.

Speaker A: So there, it's interesting. A lot of the times I've been asked this question about how we're supposed to survive as individuals, not as your technologist. So what I say about the individual question is often something like, it's very much like the maps thing. We have to use maps. But what we should hope to do is choose, be aware that different maps reflect different values and choose our maps with care and sometimes make our own. And maybe an echo of this is at the structural level, if you have controls over the structure, then one thing to do is to try to make a map for everyone and force it out And another thing to do is, and I mean, this'll sound super simple, but like, help create a variety of maps.

Speaker B: Yes. Speaker A: And help people figure out. Speaker B: There are choices. Or there could be choices. Speaker A: Make tools that let people build the maps they need and want. And be, to be careful. I mean, okay, let's focus on the map. I'm going to focus on a simple case. I've been thinking a lot. I've been running into people from the technology space who are concerned about the world, and they have a particular world of what's wrong with— a way of what's wrong with the world, a view of what's wrong with the world, which is that polarization has screwed up a lot of politics in the world.

And so they're trying to solve for it by optimizing. And the way a lot of people are trying to solve by optimizing for it is to reduce polarization by algorithmically boosting using content that's equally agreed upon by both sides. I think they think this is a value-neutral way of proceeding. I think it's a way that clearly emphasizes politically centrist and in particular, uh, I mean, here's the uncomfortable version of it. Imagine you went back to 1830 America, where half the population still believes in slavery, and then you had your bridging content moderation algorithm that boosted the things that everyone, both sides, agreed with, right?

That is a very value-laden, very choicey— I mean, I think there's this, there's this fantasy. I'll speak directly. I've been thinking about this, and I think there's this weird fantasy in the technology world that you're gonna be able to make a, not have to make moral decisions, not have to make political decisions, but somehow improve the world and change it for the better and never have to think any complicated thoughts about what better is. Does it make sense? Like there's this— Speaker B: It's a little bit, I think it's a little bit oversimplified, but directionally I think you're right.

Speaker A: Yeah, I mean, maybe we might be thinking about different people, but I have— Speaker B: Big AILA, like Anthropic and AI Labs, they talk about ethics. It's not that it's not part of the discussion at all. So I think we've moved past that. But, but I think that the push that I hope a conversation like this helps people is, is like, you need to perceive this way more. You need to be well, way more thoughtful about all of the places that values are laid out. Speaker A: Right? Yeah.

I mean, I— if you think that there are some values that are easy and you can optimize for them. Speaker B: Yeah. Speaker A: Right. Cool. But if you think values are tangled and complicated and you might be missing a lot of it and anything that you do is going to vastly change the value landscape, in a substantive way, and there's no easy neutral way to make the world better without making value and political choices, you might have to be a lot more careful. Speaker B: Man, I have so many other things I want to ask you.

I think we have time for just 2 more, um, maybe 3. Very quickly, you mentioned to me you have another idea that you think you'll probably spend the next 5 to 8 years working on. Could you give us just the tease? Speaker A: We've already done it. I mean, the biggest, most interesting question for me is that it's like the question about data spun up. Whenever we coordinate and we have to communicate, this will require making decisions together about what to ignore together and what to track together. And how do we think about the essential pluses and minuses of coordinated communication, like not just data, but for everything, for our concepts.

So cool. Speaker A: We've already done it. I mean, the biggest, most interesting question for me is that it's like the question about data spun up. Whenever we coordinate and we have to communicate, this will require making decisions together about what to ignore together and what to track together. And how do we think about the essential pluses and minuses of coordinated communication, like not just data, but for everything, for our concepts. So cool. Speaker B: Uh, you said we give things power by believing in them. What do we need more belief in?

Speaker A: We've answered this already. Play. Speaker B: Art. Speaker A: Like, I mean, in particular, maybe I was gonna say play or humility, but I kind of think they're the same thing. I mean, my— I guess one worry, one way to put my worry about metrics metrics is that the metrics— the attitude of optimizing for a metric encodes behind it the attitude that we know what's important and we just need to max out for it. That there's no process by which we might wander the world figuring out what we've missed.

Speaker B: Yes. Speaker A: And I think I think the spirit of play is like, encodes in it a spirit of humility, because you're trying out shit, even if it looks weird and silly. Speaker B: Ready to be surprised. Speaker B: Ready to be surprised. Speaker A: And you're open to being surprised. Speaker B: I have just one last question, which obviously relates. Near the beginning of The Grasshopper, there's a line from the grasshopper, and he says to two of his disciples, I have the oddest notion that you are grasshoppers in disguise, that everyone is really a grasshopper.

How do you remind yourself that you're a grasshopper? Speaker A: I have sometimes— I've had some professional success lately, and I used to be the person that walked into the room and like no one wanted to pay attention to me because I was the one working on the dumb stuff like games. And now I'm getting to the thing where I can see the path of becoming, like, a senior person where everyone, like, wants to listen to you. And I, like, I can start to trust myself too much. I can start to become overconfident.

And, uh, the way I respond in my context, the way I remind myself of the fact that we are all just clumsy, playful, idiotic mud things These days I bring really weird toys. I bring some yo-yos. I have a new one. I've got these, like, really silly spinning tops, and I play them with people and fail. And there's something really weird about doing something dumb and hard that you're bad at with other human beings. Speaker B: Being a beginner. Speaker A: Yeah, being a beginner, um, being Soaked in the oddity of it, not being particularly good at something, being soaked in an activity where you don't know exactly what it's for and exploring it with people that, uh, I don't know, reminds me that I don't know much about anything.

Speaker B: Being a beginner. Speaker A: Yeah, being a beginner, um, being Soaked in the oddity of it, not being particularly good at something, being soaked in an activity where you don't know exactly what it's for and exploring it with people that, uh, I don't know, reminds me that I don't know much about anything. Speaker B: What a great way to end it. T, thank you very much. Speaker A: Thank you. Speaker B: Thanks for listening. I hope you were inspired by my conversation with T, and before I leave you, I'd just like to thank Notion one more time for being the presenting partner of Dialectic.

If you missed my announcement of the partnership late last year, I wrote up, uh, just some thoughts on both what patterns had emerged as I had 35 conversations last year, as well as the things that stand out to me about the show, what I feel when I'm doing it, the audience, and more. Those three themes were ideas turning into action. Emotion, craft, and soul. And I wrote about those and I also wrote about why I think the overlap in those values, um, with Notion made them such an amazing partner for me.

Uh, I think they're a company and brand and product that embodies that as a tool that you can use to turn your ideas into something real, whether it be solo or with a wide range of collaborators. It is a tool that is filled with craft at every level of Um, and I think I really admire the way that the Notion team has been able to scale craft. It's not something that's easy to do. And all of these years later, it's something that still goes into so much of what they do.

And then finally, soul. Again, probably a thing that's hard to pin down, but something that you can feel and something that is kind of enriched in humanity and aspiring to do your life's work, to do something great. I'll link to that in the description. In the description, uh, if you'd like to read it. And once again, thanks to Notion. I'll see you next time. Thanks for listening. I hope you were inspired by my conversation with Ti. And before I leave you, I'd just like to thank Notion one more time for being the presenting partner of Dialectic.

If you missed my announcement of the partnership late last year, I wrote up, uh, just some thoughts on both what patterns had emerged as I had 35 conversations last last year, as well as the things that stand out to me about the show, what I feel when I'm doing it, the audience, and more. Those 3 themes were ideas turning into action, craft, and soul. And I wrote about those, and I also wrote about why I think the overlap in those values, um, with Notion made them such an amazing partner for me.

Uh, I think they're a company and brand and product that embodies that as a tool that you you can use to turn your ideas into something real, whether it be solo or with a wide range of collaborators. It is a tool that is filled with craft at every level of detail. And I think I really admire the way that the Notion team has been able to scale craft. It's not something that's easy to do. And all of these years later, it's something that still goes into so much of what they do.

And then finally, soul. Again, probably a thing that's hard to pin down. But something that you can feel and something that is kind of enriched in humanity and aspiring to do your life's work, to do something great. I'll link to that in the description if you'd like to read it. And once again, thanks to Notion. I'll see you next time.