Authors in August: Thi Nguyen’s “The Score”

In this episode of Motley Fool Rule Breaker Investing, Motley Fool co-founder David Gardner talks with philosopher and game scholar Thi Nguyen about rankings, metrics, investing, institutions, artificial intelligence, and the subtle difference between playing a game and letting the game play you.

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A full transcript is below.

This podcast was recorded on Aug. 5, 2026.

David Gardner: I'm a lifelong gamer. I was playing stratomatic baseball and Dungeons and Dragons as a kid, and then along came Pong, the first video game. Then about 10,000 more board games, video games, card games, word games, mobile games, games, games, games, which is the podcast I do every December listing my year's favorite games. Then I met Thi Nguyen, author, professor, philosopher, and philosopher focusing specifically on games. In our first Rule Breaker Investing podcast conversation in 2023, Thi helped us answer, What are games? Really? Why we do voluntarily embrace unnecessary obstacles? What games do teach us about ourselves and how they shape our agency?

hen, in our second conversation in 2024, I asked, why do games matter? Why do games deserve to be considered one of humanity's great art forms? Thi gave us a deeper dive this time into his book Games Agency As Art, exploring striving play, achievement play, games as works of art, and why some of life's richest experiences come from pursuing goals we ultimately don't need. In case you think this is just about board games or video games, by the way, it isn't. All games are included, including, if you will, the games of business, of investing, of life.

Well, this time, kicking off Authors in August, in 2026, Thi has written a fantastic book, possibly, I don't know. His magnum opus. We'll see where he asks, What happens when life starts keeping score? Not just games anymore, scores, metrics, rankings, performance, how the numbers we invent to measure success can quietly reshape what we value and what we become the score, how to stop playing somebody else's game only on this week's Rule Breaker Investing.

Welcome back to Rule Breaker Investing. It's August. Therefore, it's time for authors. Authors in August now in, I don't know, sixth or seventh year of doing this. What a delight getting to meet and then sometimes re-meet some of my favorite authors, always featuring books that I personally read and deeply enjoyed, wanting to share that with you, hoping you might read along, too. Many of you have. I tend to foreshadow these a month or so ahead, and I've already heard from some fellow fools who said I wouldn't have known about the score. I loved. Well, I did, too. Let me mention next week, Vasant Dhar, New York University professor, AI pioneer, his book, Thinking With Machines. Looking forward to talking. I'm sure we'll talk a little bit about AI this week too, but especially focusing next week on thinking with Machines by Vasant Dhar, DHAR. When he first joined me in February 2023, I was noting at the time that he had no Wikipedia page entry. I thought this outrageous, and I suggested aloud to you, my Foolish listeners that maybe you could help remedy that. Now, I'm not saying any fellow Fools did this. I couldn't know.

But I am happy to say that this little bio that I've cobbled up now comes from reading Thi's Wikipedia page, and after I share it, my first question for my esteemed guest is, is it accurate? Here we go. After graduating from Harvard University, where he majored in philosophy, C. Thi Nguyen lived in the Boston area, working as a tech writer. He quotes, made a lot of money but hated it, and enrolled in a philosophy PhD program at the University of California, Los Angeles. Nguyen completed his dissertation on the epistemology of moral testimony while working as a food writer for the Los Angeles Times. After completing his doctorate, Nguyen taught as an adjunct professor while doing work on the philosophy of aesthetics. His first book, Games Agency As Art, won the American Philosophical Association's 2021 book prize. Welcome back, C.Thi Nguyen, and Thi, do they get it right on the Wikipedia?

Thi Nguyen: They got the Wikifacts right, but they left out all the temperamental. There's no despair, sorrow, absurdity, and chaos in just the bare skeletal bones. But that's about right.

David Gardner: Well, this represents progress from three years ago, so we can't go in and edit our own pages, but perhaps others will listen and hear you, and maybe it'll self-improve over the course of time. Ralph Waldo Emerson used to ask this question of friends, whom he hadn't seen in a while. I'm going to ask it of you, Thi, what's become clear to you since we last met?

Thi Nguyen: This is a cruel and unusual question. What's become clear to me is basically the entire book. Basically, this book started as a question that I talked myself into backwards. I spent a lot of time, as we talked about in our previous podcast, talking about the beauty of games. That theory was a love owed to scoring systems. That original theory was like look, what makes games magical is an art form. What makes them special is the constraints and the point systems. What the point system lets a game designer do is reach inside your soul and set desires. They let game designers shape us like plastic putty or something and then create these beautiful experiences through setting alternate selves with alternate cares. Then after that, some people a lot of people would talk to me and they oh you love games. You must love the gamification of education, and you must love the gamification of work. I was like, hell no.

The gamification of education is the worst possible thing. It is the opposite of the true spirit of games and play. Then I went off and I wrote a bunch of other papers about something that I'm sure we'll talk about today, which is value capture. Value capture is what happens when you have your own rich values and you get put in a setting that gives you simplified versions, typically metrics or rankings, and the simplified versions take over going on Twitter to connect to people and then getting obsessed with your likes and follows or becoming, I don't know, a podcaster to connect and edify and create interesting ideas and then becoming obsessed with, say, your subscriber account. I ended up telling the story about how I thought the problem could be best described as outsourcing your values and outsourcing your values to a massive institution. But the problem of value capture was that instead of these rich, subtle, poetic, ineffable values, you had to suddenly put at your center something that was clear and simple and very usable by a large-scale institution. You couldn't talk about joy or happiness. You could talk about productivity numbers or sleep numbers, or weight or lifespan. It was all stuff that was easily measurable at scale. I was proud of this paper.

Then at some point, I realized I'd written two things that completely contradicted. One thing that said point systems and especially clear point systems are beautiful. Are the site of joy and fluidity and delight. Then the other thing that said do you know what really destroys human life and human value? It's metrics and rankings. It's clear, explicit validative criteria locked into institutions. Then I realized the two major things I'd written conflicted with each other. I had this puzzle, which I didn't know if anyone else cared about, which I thought was the most interesting thing, which is why is it that clear scoring systems are in half my life the site of everything great and joyful and fun and delightful? The other half of my life, the worst enemy, the great drainer of value, the great destroyer of joy.

Another way I sometimes thought about it was I would go to my job, and one of my hats was education learning outcomes liaison for the philosophy department. Now, I would have to report learning outcomes to the Utah State Legislature, and it was just hell. Then what made it hell was I had to write it into clear legible metrics that everyone could follow. Then after that hell, I would go home and with my spouse or fan, we would open up a board game and subject ourselves to a clear, legible scoring system. Then I was just like, What's going on? I think the answer. Maybe the real answer will take a lot of time, but to quickly foreshadow the answer, the dumbest, fastest version of the answer is, you can’t house-rule GPA, and you can’t house-rule your subscriber account. But you can house rule your dungeon and dragon game. You can house-rule your poker game. Or more deeply, you can choose which one you're playing.

That actually the important thing is about the relationship between the clarity of scoring systems and the scale at which they're enforced. Games turn out to be these little bubbles of play that we can move between lightly. You can just change them according to your taste, and metrics or something else. Metrics are a case where the clarity of scoring systems gets fused to a very functional and comprehensible demand. For absolute stability at scale. That becomes the important thing. I think if you want a fast version of it, the biggest thing that's become clear to me since we last talked is the incredible importance of the notion of scale and especially of the price of communicating at scale. The big weird answer turns out to be that games can be for a small number of people. You can make some weird *** role-playing game that only ten people like, and that's fine. But what makes metrics powerful is the demand that they be absolutely accessible and usable across millions of different people, and there's a heavy, heavy price to pay for that. That, I think is become the obsessive center of what I've been thinking about since last we talked.

David Gardner: You've turned it in part into a book. Maybe toward the end, I'll ask you if you have any new thoughts since the book, which you probably do, but for most of us, the thoughts that you provide, for me, certainly in this book, are really provocative, really relevant. Even if we don’t want to talk about the gamification of anything, let’s go back to your example of grade point average, because for a lot of people, this is a great thing in Thi Nguyen’s thinking. When you think about grade point average, for a lot of us, well, it's a way at scale to measure across a university, let's say, the University of Utah, who's doing well and who's not? Who's the best? Who's the worst? As soon as you start doing that, and you make that how we're scoring things, you make that metric the metric because you need it. You're a big state university. Then you start having people game the metric. You have people who take intentionally easy classes because that will give them the best GPA. They potentially lose a love of learning or rob themselves of what they could have been as they pursue the big institutional metric. I know at one point in the book Thi, maybe you could talk about this, you tried to become the ungrader, you share a little bit more on these topics.

Thi Nguyen: GPA is a great one. Another great one that I've been thinking a lot about is so GPA is the one that students are most aware of. At the administrative level for faculty and everyone above, the one that people are really obsessed with is graduation rate and graduation speed. This has become a stand-in in a lot of circles for student success. What student success is is graduating people as quickly as possible. Trying to articulate what was up with this for me, and then I realized here's an interesting thing. Let's say I meet a student and they're struggling and they're miserable and they hate their major, and I talk to them for a while, and I help them identify a better major, and it's better fit for them, and they're happy and they're excited. It takes them another year to get through. I have failed by the student graduation rate metric. The other major metric we have is salary after graduation. If I have a student and they take an ethics class for me, and they become convinced that the goal in life is not to take the job that makes you the most money, but to do something good for the world or that you care about, their salary is likely to go down. Once again, by the other standard metric in my university, I have failed. I got really interested in this.

Actually, there's a backstory you might be interested. I deeply changed my mind about what this whole topic was about over the course of writing the book. When I started writing this book, I thought this was a user interface story. I was really excited by this book that you may know, Natasha Dow Shcull, she's an anthropologist at NYU. She's this incredible book called Addiction by Design. If you don't know you should have her on your show.

David Gardner: Thank you.

Thi Nguyen: She studies the development of the video game poker industry and the development of the user interfaces that promote addiction. Then she tracked how the people that made video poker hyper addictive by looking for particular timings of light and sound got hired by Facebook, by Twitter, by people that make free-to-play games. When I started writing the book, I was like this is the story. The story of Twitter is the story of addictive user interfaces that hack our neural system and get us addicted to our own serotonin. It's a 20-year-old technological story of interface design. Then I started doing background research. I started reading a lot of the things that ended up being really influential in the book. I started thinking, this can't be it 'cause we see these effects far before modern graphical interface design. The book Engines of Anxiety, which is an incredible book by Wendy Espeland and Michael Sauder, is about how the US News and World Report law school rankings completely reshaped legal culture and realigned it along a very simple set of evaluative criteria.

David Gardner: Can you give us more on that? Because I love this point in your book. I never applied to law school. This was I get it, but I didn't really know it, but can you dig in and just lay that one out for my listener?

Thi Nguyen: Wendy Espeland and Michael Sauder are sociologists, and they track what happens when the US News and World Report starts issuing university rankings. Before the US News and World Report, there was no singular university ranking. Universities would state their missions, and different people had different senses of what universities were good, but there was no single ranking system. The US News and World Report did that, and I think it's really important right at the outset to say that I think they did it for very good reasons. They did it for accessibility reasons, and a lot of the times, the stories I'm going to tell today are not stories where at the end of the story, you find something like mustache twirling villain who wants to rule the world. Would you actually find often very good-hearted people who have very good causes? I think they're thinking about people like me. Some people I knew in college were from wealthy families who were connected and knew all the inside scoops about which schools were actually good and which weren't.

I'm a Vietnamese immigrant's kid. My parents weren't connected to anything. I had no information. And the US News and World Report was trying to get information that was held often in very closed societies about which schools were actually good and which weren't out to everyone. But to do that, they had to do a radical simplification. So one of the things that Espeland and Sauder note is that before US News and World Report, law schools used to have deeply different missions and different values. So some law schools cared about, say, research. Others cared about getting the people high-paying jobs. Some cared about social justice missions or community outreach. But a lot of these things aren't measured by the US News and World Report. So the US News and World Report tracks a fairly small number of features. So it changes every once in a while, but a lot of it's a status ranking, and then the rest, the part that's not a status ranking, where you just survey people for status, is measured like incoming class GPA, incoming class LSAT score, outgoing class employment rate at the nine-month mark.

So what happens is the coming of the US News and World Report flattens the value landscape of law schools. So suddenly, you don't have as many law schools pursuing community outreach missions or social justice missions or helping people become legal scholars, because those missions don't align with what the US News and World Report is measuring. So everyone is forced to because the US News and World Report becomes so powerful for people to target exactly what those rankings measure. So it flattens the value landscape, but it takes what was once a pluralistic value landscape, and it smooshes it. A

nd then I think the other thing that happens, and this is the most interesting part of what they chart for me. What they say is that before the rankings, individual students used to go through a deep soul-searching around the point of picking which law school to go to. Because law schools represented different value systems, students would have to decide whether what they cared about was a high-paying job or becoming an activist or becoming a researcher. When the US News and World Report came out, they stopped doing that. Students stopped asking themselves what their values were. What Espeland and Sauder Report, and this is from their empirical research, is that students at this time start just assuming that their goal is to get into the best school, and where best is just set by the US News and World Report.

So what I ended up doing in my work is trying to look at this and explain philosophically what the harms are. And I think the best explanation I have is that the harm here is that you're outsourcing your values. You are not going through a process of value deliberation. You're letting an external force, often which has very, very distant values and is often tracking things precisely because they're easy to measure at an institutional scale, right? You're letting that set your own values, about your education, about what you care about.

Anyway, to get back to the previous question, I think the thing that was really interesting for me about this was I realized the US News and World Report is not an addictive graphical interface. There's no video gaminess about it. It's just a ranking badly graphically designed in a magazine. It's just static, and yet most of the effect comes from that. When I dove into history, you see the same effects, like in 1920, about the cost-benefit analyses, suddenly seizing the attention of Congress completely. So I ended up thinking, there's definitely some addictive app stuff. But the most important feature here is about the power of numbers themselves, the power of rankings in institutions to command people's attention and to defeat our sensitivity, because I think the effect I kept seeing was when people who knew deep in their hearts that there was something more important, that there was something the rankings weren't tracking.

When they were set in a setting where some metric became the standard communication device across an institution, people's attention tends to be so drawn in and so seduced and so commanded by this clear metric that they burn out a sensitivity to, I mean, it should be obvious the graduation rate is not the sole measure of a good education. And yet we see administrator after administrator aligning themselves on the metric. So I got really interested in why metrics were so powerful. I guess another question for me was, I mean, when you talk about this stuff, a lot of people will say, like, Oh, the problem is, those are bad metrics. We just should find better metrics. Something in me was like, Yeah, is it just that some metrics are bad, or is there something about metrics by their nature that makes them unable to capture a lot of what's richly valuable about human life? I think I found explanations and arguments that clearly showed me why metrics are intrinsically going to miss huge chunks of human life.

David Gardner: So metrics, which, for our purpose and your book, really is a jargon term, is very specifically, generally being highly negatively connotated. It is like, this is grade point average. This is the law school rankings. These are metrics, and metrics have to succeed at scale. We put them in place, you say, because we have to have scale. And that's in contrast, in some ways, to games to get back briefly to games and scoring systems, where, for an hour and a half, we all agree to play a deck-building, tableau-driven game in which we're going to get points for the cards and how we've lined them up by rows and columns. Then after 90 minutes, it doesn't matter anymore, but we had a great time.

Then we play a completely different game, and we constantly choose into new contexts, new scoring systems. We can't choose out of the metrics. Here's a direct quote from your book, and for anybody who's just getting into this material, if I were to say there's a single line takeaway maybe that we can all walk away from this conversation with from Thi's book, it might be this. I'm just capturing what you've already said, and I quote, "I wasn't using a scoring system to achieve my own values. I was letting the scoring system set my values for me." There are so many great examples and stories in your book. I feel like we get to know you as an author, which we don't necessarily expect from a lot of academic writing traditionally, but I think what's so engaging about you, both your writing and, of course, anytime I get to talk to you, is you're just so much fun to listen to and learn from. Could you please briefly bring in cooking and the effect that recipes have relevant to this conversation?

Thi Nguyen: Let me back up for a second, for the quote that you just read. I think one way to put it, I was at dinner with a bunch of academics, and I was talking about this book while I was writing it. This political scientist, God, I forgot his name. I signed him in the book. He said, Oh, yeah, Hobbes talks about this. And I was like, What? I didn't know Hobbes talked about this. So Hobbes is a political philosopher who famously said, "Morality just comes down to political power." Like, whatever the powerful tyrant does, that's morality. And this guy says, Yeah, but you should look at what Hobbes says ultimate power is. So it turns out that Hobbes says, the ultimate power of the tyrant, the strongest power in the world, is not military might and not force of arms. It's power over language, because if you get to define what success and failure mean for people, what good and bad are for people, then you control them from the inside.

One way to think about what metrics are is that there are definitions of what is important, what counts as good, what counts as success. They get pushed out from the center onto everyone else. I think this is exactly what you're talking about. So this is the huge difference between games, is that when I play games intentionally and well, I'm adopting scoring systems, but I'm adopting them for my own purposes. I mean, I think this is such a common thing that it's almost trivial, but you can play a game. And then when you're done, you get to ask yourself, Did I like it? Was that worthwhile? Was that fun? Was that interesting? Was that stimulating? If you say no, if the scoring system does not turn out to support your own values for game playing, then you can reject it. Again, this is not true of everything. This is probably not true for, like, professional sports. This is not true for force games, for games in the environment that many of us encounter them. They support reflective choice over scoring systems. They ask us constantly to ask whether the scoring system is good for us.

Something very different seems to be true of metrics. You asked about recipes. I think recipes are a really good example of, so when I was trying to figure out what was up with metrics, why they seemed to intrinsically miss what was important, I found these two people, Theodore Porter and Lorraine Daston, both of them historians, who had such powerful accounts, each of them individually and together, they're like Matrix-style ripped the mask off of the modern world, and then I suddenly felt I could see everything.

So let's talk about Lorraine Daston, because this is the gateway to talking about recipes. So, Lorraine Daston has a book from a few years ago called Rules. She's trying to explain the different natures of rules. So why are we talking about rules? A scoring system is a rule set that specifies what you're going to measure as success. So, Twitter, for example. Hidden beneath the bones of Twitter, any social media system, if you adopt likes, what it's saying is, here's the rule. What counts as success is how many people click that little like button. A lot of other ways that you can imagine thinking about success. You can think that success was connecting to people or deeply reaching one person or having an interesting conversation. But the rule system, the hidden rule system of Twitter, if you take it on board, says, no, it's just about who clicks the like button at the moment that they saw the thing.

So it's trying to figure out rules, and Lorraine Daston explained the nature of rules to me. So in her book, she says that our conception of rules has changed radically over the last many hundred years. She says, over time, we have actually had very different conceptions of rules. The modern notion of a rule is actually pretty recent. So she says, a lot of the older conceptions of rules are what you might call a rule as a principle. So a principle is a generalized abstraction that admits of exceptions, but you have to get the spirit to know the exceptions. So you can't just follow it blindly. You have to apply the rule with sensitivity and expertise and discernment and judgment to know when it doesn't apply.

So I think my favorite example is, like, in creative writing, I learned the rule, Show, Don't Tell. It's a rule, except you might notice that a lot of artists break it, right? Tolstoy. “All happy families are alike. Every unhappy family is unhappy in its own way.” One of the greatest opening lines in the history of literature breaks the Show, Don't Tell rule. If you point this out to your creative writing teacher, like I did when I was a young student, they would be like, that's not the point. The point is not that you apply this unthinkingly. The point is it's a general guideline. If you really start to understand how fiction works, you'll know when to break it. And if you say, like, give me exactly the rules for one to break it, they can't tell you because the point of a principle is the exceptions are complicated. You have to have some sense of the real thing behind the rule to know when to break the rule. So that's a rule is principle. The new rule, she says, is a mechanical rule. A mechanical rule is one that's written so that anyone can follow it unthinkingly and get the same result.

David Gardner: I know this is rooted in double-entry bookkeeping because I've read your book, and she talks about this. For understandable reasons, for the first time, we needed to separate from human, in human fact. That's a relatively modern conception, and it started with the accountants, Thi.

Thi Nguyen: Yeah. You're talking about Mary Poovey, another scholar in the space. One of the things she says is, we used to think something was a fact because it came from a good person who had good judgment. Now what we think a fact is is something that comes from a mechanical process. That anyone can inspect, something that emerges from no person at all. I think in a sense, what's happened is that we as a modern society have been captured by the standard of mechanical repeatability, right? We think that what's real is what anyone can track and that everyone tracks the same way, and what's not real is anything that defies that. That's not true. That's not the real heart of things because there are a lot of things that are important to the world that require intense expertise to notice or see.

Jennifer Lena, the sociologist I love, has a great example about how arts funders often try to give grants for artists based on expert judgment about what looks like good art. But oversight, especially congressional oversight, often thinks that these arts grantors are just nepotistically funding their friends because they can't see what's valuable. So when they look for a standard that anyone can follow, they often reach for things like ticket sales, box office sales, popularity. That's mechanically inspectable, but it doesn't actually track what's valuable. Lorraine Daston thinks that mechanical rules are designed so that anyone can follow them. They're designed to be accessible, right? They're designed to be accessible without particular expertise or education. But there's a cost to that. When you write rules that are designed to be accessible, what you're excluding is any judgment that requires sensitivity or expertise or long familiarity.

She gives this incredible example of the difference between principles and mechanical rules and its recipes. So she says, like, Okay, if you look at recipes, old school recipe books, old school cookbooks look very different from modern cookbooks. So a recipe in an older cookbook will often look like this. Take three handfuls of flour and mix in enough water to make it moderately pliable and gooey, and knead it until it stiffens, and then whack it until it is resilient, stretch it, roll it. Then my favorite one was bake it at good heat until it gives a nice resounding knock sound when hit. Then a new school recipe often looks like: mix three cups of flour and two cups of water, mix at speed eight on a KitchenAid for three minutes, and then form into a loaf and bake at 350 degrees for 45 minutes. The latter looks legitimate to us, and I think for a lot of people, the first one looks weird, old, goofy, unreal.

Actually, if you bake a lot, what you'll understand is the first one's actually really good. Old school recipes actually work really well if you know what you're doing. If you have the expertise, they're actually cueing you to adapt, to listen to sense things, and to sense what's really important. The thing about this knocking cue is it doesn't actually work great the first time. But once you practice a few times with the bread, you'll learn exactly how bread sounds when it hits the right level of loft, and it's actually cuing you in a way that requires some testing and experience, and skill to look for what's really important. This other thing, the modern recipe style, it looks really official to us, but it's been written so that anyone can out background skill or practice. It doesn't actually work perfectly over time. It works pretty good. But if you're a good baker, one of the things you know is humidity changes, temperature changes, different flours are different.

On different days, the same bread will take more time, will want a little higher heat, will want a little bit more kneading. What you need to do is adapt. The interesting thing about the modern style recipe is it writes itself in a very accessible way that anyone can follow and get to the same procedure. But what you lose is any cues that tell you to adapt, to be sensitive, to look for odd little details, to, like, sniff and smell when things smell right. What's interesting here is that the way that Lorien Dastin puts it, is that the modern recipe is written as a set of mechanical rules to follow that anyone can follow in the same way. Its virtue is consistency. What it loses is adaptability to changing circumstances. It loses the cues that tell you to look and listen and be careful. I think what this is, I don't know if it's a metaphor, but it is a version of what's going on with metrics.

When I tell you to fund original art, when I tell you to fund creative art, when I tell you to try to teach to students to encourage critical thinking, these are things that require a fair amount of sensitivity and judgment to apply. Sure. When I tell you to educate for fastest graduation rate or highest salary, or highest scores on student evaluations, these are things that do not require expertise to apply. These are standards that have been mechanized. I think what Destin is really showing us is the heart of the trade-off at the center of modern metrics. What it is is a trade-off between sensitive rules that are hard to follow. Versus clear mechanical rules that are formulated so anyone can follow them, but in order to be so formulated, they have to cut off directions and criteria that have high sensitivity and high experience.

David Gardner: We can't have context, we can't have nuance. In some senses, they're dumbing not just the system down, but obviously a concern of yours, and something that I enjoyed when you went there in the score is they're dumbing us down, too, if all of a sudden we're no longer paying attention to nuance or we weren't aware that things could be more complicated or more interesting.

Thi Nguyen: But I should pause and be clear that I am not anti-metrics. I think in many cases, metrics are put in place precisely because they're accessible, precisely because without them, you have bias and you have corruption. By forcing people to hit a clear target that anyone can check, you do remove a certain window for corruption and bias. At the same time, you remove a window for sensitivity and expertise. I think it's really worth here talking about Theodore Porter. This is the other major player that really helped me understand what was going on. He's the one that talks more explicitly about context. Porter, in this amazing book, Trust in Numbers, Porter is a historian who’s studying the rise of quantification culture. The thing he's really interested in is explaining why so many bureaucrats, politicians, and administrators reach for quantified justifications, even when the quantifications are obviously irrelevant or obviously tracking the wrong thing.

My new favorite terrible metric, a friend of mine is a student advisor at a university, and he and his student advisors are now being judged on advising quality, where advising quality is measured a number of keystrokes per minute into the student advising system. This seems like, obviously bankrupt, and I guess the question here is it’s so obviously terrible. Why would anyone use this? This is a question that Porter's trying to answer. Like, why are numbers so seductive? His answer is that there are two different systems of reasoning and justification we have, qualitative and quantitative, and he thinks they're good at different things. The claim isn't that quantification is bad. The claim is that these are different tools that have different purposes, different strengths, and different weaknesses, and we should use them together carefully and intentionally. What he says is that qualitative reasoning is reasoning in words, justifying things in paragraphs. Qualitative reasoning is sensitive and open ended and dynamic, but it travels badly between contexts because it requires a high amount of shared background knowledge to understand. He says, In institutions, we get around this. We try to solve this with a technology with a device, quantification, metrics. What we do to create quantifications and institutions is we identify a context invariant kernel. We identify something that everyone understands and counts in the same way.

Once we've identified that kernel, that information can pass easily between people with different contexts, and people in different contexts can all count and collect data into the same bucket, and that can all aggregate instantly. I think my favorite example of this is GPA. Like, when I evaluate my students' papers, I write long multi-paragraph commentary about their originality and sensitivity and about their scholarship and rigor and the quality of their argument, and I can move along 10 or 15 dimensions, and I can use all the rich language that we've developed in philosophy. But those qualitative assessments won't travel. They won't be understood easily by people in different departments, and they won't aggregate. Because each of them is tracking different dimensions. When we create a stable bucket that everyone agrees on, GPA, then we've created something that does travel. We all know approximately what an A, B, and C means, and we all mean approximately the same thing when we enter A, B, and C at someone's grade, and so everyone can interpret those numbers easily, and we can all collect into the same buckets, and they can all aggregate instantly.

What we get, says Porter, when we create this contextually invariant bucket, when we create this kernel that everyone understands is a highly portable information system. We create something that everyone can understand and share instantly. But we create it by stripping out context and nuance from that bucket. We have to be all counting something that we can all track together, and so we can't be triggering it off of high context expert particulars that only a few of us can track. I think the huge insight here is that the power of data is inextricably connected to its price. The power of data is that we can all understand it, all access it, and they can travel instantly. The price is that it focuses us on low context qualities that are stable across different expertises and contexts. This gives me nightmares now, because what it says is that the very reason that metrics are powerful is precisely that they have been intentionally denounced. That is the method by which we've created the power of portable data.

David Gardner: As I think about this, Thi, one of the things that I've certainly learned is that scientific evolution people who are much better studied on that than I, some of whom I've read, point out that what makes humans unique? What makes us quite amazing, really. What caused us to far exceed the apes and the chimpanzees is our ability to coordinate at scale, to organize and to cooperate. If you get more than 60 apes together, they can't work together. They just start fighting. Things that we humans take for granted today, I'll give a few quick examples, clothing, iPhones, stadiums, medicine, airplanes are all largely explained by our ability to cooperate at scale. One of your four horsemen, we don't have time this week to talk through all four of your horsemen of bureaucracy that you highlight in the book, a fun feature throughout the score. But one of them is scale and obviously, you and I, on the one hand, are inveighing against it and just pointing out the dangers of falling in love with scale and missing all of the nuance and what makes life special and memorable and what makes every person unique. Yet, out the other side of our mouths, we have to acknowledge that scale explains why we have clothes on right now and medicine and iPhones.

Thi Nguyen: My claim is never that metrics and data are bad. Let us be clear. I'm an asthmatic. Without modern science and data-based medicine, I would be dead at age of like 10. I think I can probably, off the top of my head, think about 15 times where I would be dead without medical interventions to require large-scale data. In no way am I saying the data and scale-based methods are bad. What I'm saying is that they're a tool that's very good at certain things and not good at other things. They're very good at targeting the kinds of things that everyone can detect or count together.

If you want me to overgeneralize, this is one of the reasons why modern medicine is really good at extending lifespan and really bad at supporting mental health and psychological well-being. Because lifespan is the thing that everyone can count together easily. Psychological well-being is the thing that's highly variable, and highly contextually dependent and very hard to count together at scale. I guess another way to put it is I'm not saying that metrics and data that what they measure is a lie. If your metric measures the number of keystrokes in the student accounting system, that's a real number. When your metric measures how quickly students are graduating, what their salaries are. Those are real numbers. When your data is measuring how an intervention increases average lifespan, those are real numbers. The thing that I'm worried about is that they're another sector of humanity. A huge part of our lives that are hard to count together precisely because they require high sensitivity or high contextual nuance.

Because they're hard to count together, they won't show up easily in our data systems. When there are fights between the easy to publicly count and the subtle, hard to publicly count stuff, in our world, the easy to count stuff wins automatically. I have two examples. One's less controversial. One might get me canceled, whatever. The less controversial one is when you're thinking about saturated fats, it's really easy to track their impact. If saturated fats increase heart attack rate and decrease average lifespan, that's easy to count at scale. If saturated fats also give some of us profound joy, if the taste of brie is one of the deepest treasures of my life, that's pretty hard to count at scale. My worry is that I'm not saying this is where I start sending, like a Thanos-type super villain or something. I'm not saying that lifespan is bad, and decreasing heart attack rate is bad. What I'm saying is, like, it's worrying that the easy to count stuff, which is important, auto wins fights, and that the other stuff drops out of you completely.

Another version of this for me is, this is the more controversial one. But I have been worried that during COVID, during public health discussions, counting lives saved and lives lost is an easy thing to count because death is very visible. Psychological health, child development, community well-being, tradition. I think these are also important, but they're very hard to count. Again, I'm not saying that saving lives is not good. I'm saying that there's a complex calculus, but the way modern justification systems work, the stuff that's not easily countable suddenly count as zero. That seems weird when I mean, I guess one way to put it is a lot of people want to say things like, there's objective stuff, and there's subjective stuff. There's the real stuff and the not-real fake stuff. What I want to say is that's not actually the line that explains data versus non-data. What data tracks is the stuff that's easy to count in unison, and what's on the other side is stuff that requires sensitivity and expertise to track. That's what's dropping out in a data-centric world.

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David Gardner: As I listen to you, Thi, I'm just reminded that I wish this podcast could go three hours sometimes because part of me wonders, what if we had a standard list of, let's say, 20 goals that undergraduate students identify at the start of their education, and maybe it's a standard list of 20 things, and one of them is simply intellectual exploration. You know that for that student, it matters. But for this other one, he just wants to graduate as fast as possible. It's all about the money. If people could express ahead of time, in some standardized way that might become a metric I feel like we could nuance the system and make it smarter and not make you as an academic, have to perform to certain rates that your own students may not even care about. But I need to push all that aside because when I think about something like that, that's more of a beautiful question.

It reminds me of one of my favorite books, A More Beautiful Question by Warren Berger, which is so much about, in some ways, what we're asking. Couldn't this be done better? How do you balance these things? Those questions. But I think just bringing this through and concluding on the book for now I'm thinking about my listener right now, and this person, I hope has been highly engaged. They're a little mystified because they agree with you that a lot is missed when we pay too much attention to metrics, and yet, and you yourself would acknowledge this as I would, as well. Metrics still matter. I'm wondering, for the rest of us, Thi Nguyen what is a score that you think we should be trying to keep that maybe not enough of us are scoring ourselves on. Then what's a metric that you think most of us may not even be aware of, let's say, and we should be shedding?

Thi Nguyen: I refuse to answer this question. But I have principled reasons for doing that [LAUGHTER] This is related to a part of my book that I don't want to spoil for people, but I think you'll know what I'm talking about. I think the entire message of this book is that the scoring systems that matter for you are the ones that align with your values, and so the most important thing is to have intentional, reflective choice about which scores do align with your values and which ones don't. In that case, the most hypocritical thing that I could do is to tell you which scores to listen to. [LAUGHTER] I refuse to answer that question.

David Gardner: I love it. Again, since we're running out of time, I can't ask my follow-up, but we're going to have more fun still ahead. I have one final question, and then you've consented to play Buy, Sell or Hold with me, which we will close with. My one final question is, I adumbrated this earlier, but Thi, have you had any new thoughts since writing and publishing The Score earlier this year? What are you thinking about now that we haven't been able to read about?

Thi Nguyen: I have been thinking a lot about how many of our basic ideas have already been transformed by this demand for mechanical clarity and decontextualization. I've been working on this stuff about how many of our basic ideas like self and art and moral responsibility, have been artificially clarified. That what the actual reality is is much fuzzier. What you're responsible for. The idea that you are responsible for specific things might be this illusion that we've built of the legal system, because the legal system has to punish particular people. But the answer is always who's responsible for that? A million things throughout history. I have been interested in, I don't know, how much we've imported bureaucratic thinking, even to our basic moral concepts.

David Gardner: I love that. So much of philosophy, and I only took one course in my undergraduate studies that was philosophy, but so much of what I've learned from you and what I love in the world is paying attention to the words that we use. Before we move on to Buy, Sell or Hold, one thing I'd just like to reflect on is you use this phrase, and it's going to sound very complex to most of us. You use the phrase permanutical injustice. While that's a complex, jargon-ridden phrase, perhaps, the underlying concept is really worth briefly thinking about. At one point, you talk about the phrase sexual harassment, and that was not a phrase that people used 75 years ago. Therefore, because they didn't have the words for it, especially women, since usually it's been visited upon women, they didn't actually have a legitimate gripe or a way to express what they were seeing or feeling, and it was even at scale, and so it wasn't in some senses until we awakened we had consciousness around this thing and put words to it, reified it, one of my favorite complex words, reification, that it made it possible for us to tackle it. Before we go to Buy, Sell or Hold, I'm thinking again, just about the importance of the language that we use and inventing new terms and reframing concepts, and I know you're alive on fire with this one. Throw me something before we start buy, sell, hold.

Thi Nguyen: That idea comes from Miranda Fricker, and the history of it is that before the term sexual harassment, the term that was in general use was office play, and this is a completely different moral valence from sexual harassment. In Fricker's accounting, many women who experienced such a thing felt, she says, crazy and alone until they came up with a language that made it possible to think those experiences to themselves. I think it is deeply related to the obsian idea that who sets the language, whether the most popular term is office play or sexual harassment, deeply changes our reactions to things and our evaluations of things. That's the worry I have about metrics. It's totally fine to have neutral data in the background. As long as you know that there is only one way of conceiving of things. It's when that stuff gets projected and forced on us, or we unthinkingly uptake it as the automatic definition of what's good. When you just start thinking, what's good in social media is a lot of likes, or you start thinking, what's good in my life is having the most money at the end of the day. That's when you have lost control of your values and let some distant institution reach into you and tweak the settings on what you care about.

David Gardner: The key phrase here, fellow Fools, is value capture, and I do appreciate that the good doctor here himself is not putting forward his own values. He's encouraging you to think about what your values are and awakening you to the possibility that you might be compromising your values or have thrown some away because of metrics that you are being forced, maybe not even in a way you were previously aware of that you were being forced to kowtow to, the book is The Score. How to stop playing somebody else's game. Our author and my guests this week is C. Thi Nguyen. C. Thi, let's go on to close it out with By, seller or hold. I'll be asking you about things happening in our society or culture. You already know this you've played before. These are not actually stocks. But if they were, would you be buying, selling or holding and a sentence or two as to why? Since I have a lot of fun with you, I think I have eight. We should go through this rapid fire. You ready? Buy, sell or hold, ChatGPT?

Thi Nguyen: Oh, my God. No. I've such complicated feelings. I'm going to hold. My feelings are too complicated, except to say that we're at a moment of a radical transformation of what is automated and not and what is outsourced or not. The thing, I think, to think the most about ChatGPT, is simultaneously what it can do for you and then what skills you have that will rot when you no longer exercise them.

David Gardner: Very well said. No. 2, chess, go, poker, diplomacy. Increasingly, whenever humans invent a game, AI eventually masters it. Maybe the question isn't who wins anymore. It's whether that changes what games are actually for. C. Thi Nguyen, buy, sell, or hold playing games against AI.

Thi Nguyen: Against AI. I'll sell. The answer to this is really clear. For me, no marathon runner is threatened by the fact that cars go faster. I think chess and go players should not be threatened by the fact that AI can do it better. That's not what games are about exercise of specific capacities by excluding tools.

David Gardner: Very well said, and I will note for gamers, and they're out there, certainly. Our conversation, this go round around The Score is really about scores and metrics, obviously tied to games. But if you want to hear Thi and me geek out on games, including our Mount Rushmore of favorite games, just go back. Google, C. Thi Nguyen Rule Breaker Investing, and you'll hear a lot more game talk if you feel like you're missing that this time around. Next one, I think I already know the answer to this because we discussed it earlier, but I'm still going to ask it anyway. Buy, sell, or hold, Thomas Hobbs' observation that real power comes from defining success rather than merely exercising force.

Thi Nguyen: Buy, come on. Hobbs' insight here is what underlies military might. It is convincing soldiers to fight in the direction you want. You can just expand that to everyone. The ultimate power is to be able to control people's conception of success.

David Gardner: One other line I have memorized from Hobbes because I studied him, at some point, undergrad, but it's something like this. The condition of man is the condition of war of every man against every man. When I first read it as a Hobbes' student, I didn't really like it. I like it even less today, and I'm sure I'm missing a lot of context behind it. It's a brutalist view of things.

Thi Nguyen: You didn't ask me buy, sell, or hold about that part. I'll sell that part.

David Gardner: Let's move on to Number 4. We're increasingly letting algorithms choose what we watch, what we hear, what we read, even, maybe, who we date. Convenience is maybe putting some points up on the scoreboard. Thi, buy, sell, or hold, algorithmic recommendations.

Thi Nguyen: This is where I have to ask you what buy, sell, or hold means. Do I think it's terrible? Yes, sell. Would I invest in it for my own selfish purposes? I think humanity is lost to convenience, and we're going to sacrifice in general, most of our important qualities for the convenience of ready automation. Sorry.

David Gardner: Number 5, I lightly alluded to it earlier. Buy, sell or hold, feel free to tell a short story if you like. Ungrading.

Thi Nguyen: [LAUGHTER] Oh, God. Hold. Ungrading is the process of stepping back from grading and emphasizing something besides grades and education. I still believe in the dream. I don't think it works in my particular classroom when the rest of the world is still grading, and I'm worried that institutionally we'll never be able to step away from it. Complex feelings. The dream is alive, but the particulars are difficult. Hold.

David Gardner: Thank you. Number 6, for years, we've been told to specialize, but now some of the people who seem to break through are often, I might say, wildly interdisciplinary, comfortable wandering from philosophy to coding, to art, to entrepreneurship. Thi, you have two young kids. I know what do you want to raise them to be? Buy, sell or hold being a generalist.

Thi Nguyen: Hold, for complex reasons, I think the basic fact of the world is the world is too full of expertises, and no one can track everything. Many of the gaps in the world come from gaps between the expertises, and some of the most valuable work is done when people who have one expertise try to learn another and connect a few. The thing that I'm worried about is that sometimes when people believe in this, they stop going deep on everything and basically try to think about the world understanding everything via two-minute TED Talks, and I don't think that works well, either. What we're trying to navigate is the complexity of the world and the need for expertise and the need to connect expertises, and the solution to that is not general shallowness, so hold.

David Gardner: A lot of holding going on. We might do it again here. Let's see. Now, let me first of all, apologize, not once during our hour or so together, have we ever mentioned rock climbing, a passion of yours. You write about it in the book. You've mentioned it on both of our podcasts in the past. I know you love it. But I'm going a slightly different direction here. Pickleball has become America's fastest-growing sport. It's beloved. It's mocked. It's occasionally blamed for neighborhood noise complaints. Buy, sell or hold, C. Thi Nguyen. Pickleball.

Thi Nguyen: Buy. I don't play pickleball, but I believe in it. I think one of the reasons it's mocked is because from what I understand, it is a highly accessible sport that's enjoyable to all, but I suspect from what I can tell, the skill ceiling is higher in tennis. I think our world often fetishizes the thing that professionals are really good at. Some of the best games are games that are optimized for the joy of amateurs or the joy of dabblers. That doesn't sell as many sponsorships, but I think games and institutions are built, so many people can enjoy them at any skill level is a deeply valuable thing that we should cherish more.

David Gardner: I guess the last one for you. Jim Carrey's lead character gradually discovers that his entire life has been an elaborately constructed television show, forcing him to choose between the comforting illusion he's always known and the uncertain freedom of the real world. Buy, sell, or hold the movie The Truman Show.

Thi Nguyen: Buy. I'll tell you, thank you for handing me an opportunity on a silver platter. In the background of this behind Truman Show, behind Matrix, I think is the old image from Plato. That we are staring at illusions on the wall and unwilling to look at reality. The thing I'm worried about is that metrics are the illusion on the wall. The thing I'm worried about is that from a certain perspective, large-scale institutions can only see things that they process through data and that they are unwilling to grasp that there are parts of the world that are subtler than large-scale institutional data collection processes can grasp. I think Truman Show, Matrix, Plato, all of these senses, there is a true weird reality behind a hard shell of easy, palatable illusion. They're getting it part of this.

David Gardner: It just strikes me as a metaphor that you've been talking about through your own work that's really connected. How about a bonus? Because we have a minute left. Buy, sell or hold a word that you use 64 times in The Score. Since it's about 320 pages, my math says, every five pages, you're using this word. You just did it in the last minute or so. Buy, sell or hold and explain to us why you love it. The word weird.

Thi Nguyen: Buy, obviously. Weird is a stand in for me for anything that is not easily digestible or anything that whose value is not highly accessible. I think the whole push of everything I'm worried about is that many important things in the world take a lot of time and sensitivity to track. If you're building metrics that define success in terms of values that everyone can see, and if that becomes dominant, then what we lose is subtle beauty. From the point of view of a world, but demand that everything important be instantly comprehensible, the word for the subtle is weird.

David Gardner: I love it. Certainly, people in Austin, Texas, who have the bumper sticker, keep Austin weird. I think they get it, too. Thi, this has been a delight. Thank you for reminding us that games aren't just entertainment, and scores aren't just for fun, especially when they turn into a matrix. I love your book, The Score, how to stop playing somebody else's game. This was a delight to have you back on Rule Breaker Investing. I'm already looking forward to your next book and our next time together. Fool on, my friend.

Thi Nguyen: Thank you.

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