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Speaker 1: Welcome to two percent. I'm your host, Michael Laser. Today

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Speaker 1: we are talking to a man who has lived rent

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Speaker 1: free in my head for the past five years. His

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Speaker 1: thinking has improved my life more than anyone else. The

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Speaker 1: guy made me throw out my fitness tracker and stop

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Speaker 1: caring about what it told me. He also made me

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Speaker 1: realize that meeting a certain salary ultimately was not going

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Speaker 1: to make me that much happier. He also reframed my

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Speaker 1: relationship to news and social media and helped me use

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Speaker 1: it in a way that improved my life rather than

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Speaker 1: made me more neurotic. He even helped me understand why

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Speaker 1: it was that my students who got b's, B plus's

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Speaker 1: as did so much better in a long run than

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Speaker 1: my students who got a's. And finally, he helped me

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Speaker 1: understand why it is that the NBA when I was

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Speaker 1: a kid is so much better than the NBA today. Now,

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Speaker 1: if you have read my book Scarcity Brain, you're going

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Speaker 1: to be familiar with today's guest.

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Speaker 2: We're talking to Tea to Win.

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Speaker 1: He's a philosopher at the University of Utah, and he

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Speaker 1: has got a new book that I highly highly recommend

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Speaker 1: everyone read. It's called the score how to stop playing

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Speaker 1: somebody Else's game. In fact, in my book Scarcity Brain,

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Speaker 1: I traveled all the way up to Salt Lake City,

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Speaker 1: Utah to sit down with him, and I devoted an

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Speaker 1: entire chapter of that book to his work.

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Speaker 2: That's how important I think it is.

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Speaker 1: So we got a sweeping episode coming at you, but

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Speaker 1: it has a ton of utility. It'll help you understand

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Speaker 1: what it means to live a good life and weighs

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Speaker 1: in your life that you being steered in directions you

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Speaker 1: may not want to go in, and what to do

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Speaker 1: about it.

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Speaker 3: So let's get into the episode.

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Speaker 2: Thanks for coming on the show.

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Speaker 4: Thanks am good to see you again.

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Speaker 2: Yeah, it's good to see you too.

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Speaker 1: Last time we met, you introduced me to the greatest

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Speaker 1: I believe it was a raisin Croissan I've ever had

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Speaker 1: in my life, and I constantly still think about it.

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Speaker 1: I'm speaking of speaking of rich, fatty foods. Here's actually

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Speaker 1: where I want to start. I want to start with

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Speaker 1: weight loss because I think at everyone at some point

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Speaker 1: in their life has tried to lose a bound or two.

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Speaker 1: So you used weight loss and your own weight loss

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Speaker 1: journey in the book to get into this larger argument

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Speaker 1: you make. So walk us through weight loss and what

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Speaker 1: happened to you.

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Speaker 5: The weight loss story is kind of like entangled with

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Speaker 5: this whole like physical story, right, Like I grew up

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Speaker 5: as a video gamer and reading NERD, hated my body,

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Speaker 5: uninterested in movement, and I kind of just like I think,

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Speaker 5: I just drank relentless amounts of juice all the time.

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Speaker 5: And at some point, like I had gotten big enough

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Speaker 5: that like it, my knees hurt and it like exhausted

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Speaker 5: me to walk from my car to my car to

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Speaker 5: my department, which I didn't like. And so I started

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Speaker 5: trying to lose weight. And the first thing a few

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Speaker 5: things I did were really simple and straightforward. I cut

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Speaker 5: out a few things. I basically stopped drinking orange juice,

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Speaker 5: and my body like I drank too much orange juice,

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Speaker 5: Like my body, my stomach just felt better. I'd made

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Speaker 5: a few tweaks, and I think a lot of people

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Speaker 5: will recognize these tweaks.

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Speaker 4: So this is like back before the.

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Speaker 5: Current awareness of like whatever protein primal diets. This was

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Speaker 5: like twenty something years ago, and I just shifted away from.

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Speaker 4: Like noodles with cheese every.

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Speaker 5: Single meal and started making like stews with meat and

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Speaker 5: like with like rich rib tuber stew, and I just

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Speaker 5: started feeling good. I lost a little bit more weight,

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Speaker 5: I started exercising more, and then my weight loss stopped,

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Speaker 5: and I like, I really got focused on that, and

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Speaker 5: I started being like, Okay, I got a track stuff.

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Speaker 5: So I got a tracker. I started entering a lot

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Speaker 5: of information in and each time my would drop a

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Speaker 5: little more and it would stall and I would have

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Speaker 5: to do something more dramatic. And so at some point

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Speaker 5: I had a weight tracker, and this is in the

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Speaker 5: early days of these things. So I was entering all

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Speaker 5: of my nutritional information into it, which was exhausting. And

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Speaker 5: then I started realizing, so if you have a really

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Speaker 5: old schoold primitive weight tracker, like I had a nutritional tracker,

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Speaker 5: it's really hard if you cook your own stew to

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Speaker 5: get information. If you want exactly the right information, you

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Speaker 5: have to like kind of painstakely enter.

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Speaker 4: Each ingredient and gets really exhausting.

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Speaker 2: It's a lot of math.

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Speaker 4: It's a lot of math.

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Speaker 5: But if you buy prepackaged food, then all the nutritional

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Speaker 5: information is right there. And so this is I think

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Speaker 5: this is the part where it gets really perverse. So

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Speaker 5: in order to continue my nutrition optimization journey, I stopped cooking.

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Speaker 5: I had been cooking stews using like grass fed meat

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Speaker 5: and like tubers and vegetables from the farmer's market, and

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Speaker 5: then I switched over to like prepackaged Annie's mac and

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Speaker 5: crap like that again, just because it was easier to enter.

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Speaker 5: And this is the point, like I was there for

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Speaker 5: just a few months, and I was miserable. I was

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Speaker 5: miserable because I was doing all this entry work, and

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Speaker 5: also I think.

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Speaker 4: Whatever was going on with me.

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Speaker 5: Having rich vegetable stews was making me feel amazing, and

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Speaker 5: eating this other prepackaged stuff was making me feel bad.

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Speaker 5: And I like kind of got myself for a few

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Speaker 5: months at least to ignore both the kind of larger

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Speaker 5: lifestyrow and the kind of bad, empty, hollow feeling in

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Speaker 5: my body as I kept wanting to track nutritional information

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Speaker 5: and kept pushing my weight down. And then eventually I

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Speaker 5: was like, this is crap, and I stopped.

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Speaker 1: And I think I think to quickly like kind of

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Speaker 1: pull back and explain to listeners what happened.

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Speaker 2: It's like, you realize you need to lose weight.

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Speaker 1: You find this thing, these st use that help that

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Speaker 1: the number goes down, you feel amazing, like, this is

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Speaker 1: what we want out of health. I want to feel

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Speaker 1: more energetic. I don't want to get winded as I

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Speaker 1: walk to my car. This is a good thing. Then

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Speaker 1: the way the number stops going down, so you go, well,

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Speaker 1: the numbers stop going down, so what can I do?

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Speaker 1: And this leads you into like, well if I just

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Speaker 1: count my calories, But now the stew becomes this huge

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Speaker 1: pain in the ass to actually do that, So you go, well,

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Speaker 1: it would be easier to just do these other foods

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Speaker 1: than not just healthy, And by focusing on that number,

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Speaker 1: all of a sudden, you start eating and doing these

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Speaker 1: things that don't actually reinforce this larger goal of health

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Speaker 1: that you're after.

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Speaker 4: So there are two things that are going on here.

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Speaker 5: One is that the demand for data entry and the

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Speaker 5: demand to track nutrition like kind of pushed me in

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Speaker 5: a particular course. And I think that's one level. And

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Speaker 5: there's another level, which is that I was using.

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Speaker 4: The idea of weight loss itself as a proxy for health. Yeah,

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Speaker 4: I remember I was talking to this once in.

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Speaker 5: A classroom about this this problem of like how excess

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Speaker 5: quantification kind of sucks our attention over to things that

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Speaker 5: are easily counted. And one of my students was like, yeah,

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Speaker 5: but what about what if you're trying to do What

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Speaker 5: if what you're trying to do is already easily quantifiable,

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Speaker 5: Like I'm trying to get healthier, and like weight loss,

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Speaker 5: that's just a number, that's just quantifiable. And I was like,

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Speaker 5: at what point did the entirety of being healthy come

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Speaker 5: down to weight loss? Like where did we get that transition?

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Speaker 5: And I think like he kind of reacted, and I

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Speaker 5: saw my whole class like just kind of jump at

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Speaker 5: the same time.

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Speaker 4: And I think it's like, in some sense.

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Speaker 5: It should be easy the thought that having lower weight

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Speaker 5: is not the same as being healthy. That should be

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Speaker 5: a simple you don't need like a professor in.

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Speaker 4: A philosophy class to say that.

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Speaker 5: And yet it's so easy to get sucked in that

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Speaker 5: even though you can say that to yourself, you forget

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Speaker 5: and you become obsessed because.

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Speaker 4: There's this easily trackable proxy.

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Speaker 1: Yeah, so this is this idea of value capture. How

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Speaker 1: do you explain that to people tightly who don't are

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Speaker 1: not familiar.

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Speaker 5: So this is the name I needed to come up with.

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Speaker 5: I needed to come up with for this stuff. So

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Speaker 5: I came up with the name value capture, and value

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Speaker 5: capture is any case where your values are rich and

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Speaker 5: subtle or progressing in that direction, and then you get

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Speaker 5: parked in some environment, either an institution or a bureaucracy,

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Speaker 5: or just with an app or tracker, and it gives

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Speaker 5: you some simplified version of your values, typically a quantified metric,

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Speaker 5: and then the quantification takes over.

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Speaker 4: It becomes your focus.

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Speaker 5: So like getting on Twitter to communicate with people and

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Speaker 5: then getting obsessed with your likes and follows, or I

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Speaker 5: think like one of the first examples I started noticing

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Speaker 5: was people getting really obsessed with their fitbit, And I

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Speaker 5: think you have to be clear that obsession is different

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Speaker 5: from just finding it.

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Speaker 4: Useful, right Like, I think a lot of people start

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Speaker 4: with this thing. They're like, oh, I don't move enough.

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Speaker 4: This helps me move a little bit.

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Speaker 5: And at some point I had a friend who is

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Speaker 5: starting to get into rock climbing and loved it. I'm

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Speaker 5: a climber, I love climbing passionately. And then he stopped

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Speaker 5: because when he climbed his step count went down. I

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Speaker 5: think it crystallizes for me what's going on because part

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Speaker 5: of what's important is there all these goods to rock climbing.

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Speaker 5: I mean, obviously the person loved it and made them happier.

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Speaker 5: There's all this multi dimensionality of joint movement. There's all

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Speaker 5: this learning of precision and skill, but that isn't easily

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Speaker 5: trackable by a mechanical.

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Speaker 4: Pre made device.

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Speaker 5: And so if you will let yourself get oriented towards

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Speaker 5: the pervasive ready quantifications, you kind of your attention gets

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Speaker 5: dragged away from the kinds of things that are rich

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Speaker 5: and complicated and interesting but don't track easily with a

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Speaker 5: mechanic device, yeah, and towards the kind of things that

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Speaker 5: are easily trackable at scale. And this is the dynamic

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Speaker 5: that I got the most interested. What happens the problem

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Speaker 5: of value capture for me, so I started calling it

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Speaker 5: value outsourcing. Like what you're doing is instead of picking

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Speaker 5: what you find valuable, instead of coming up with your

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Speaker 5: version of what's important to you about your health or

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Speaker 5: your fitness, you outsource it, and you outsource it to

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Speaker 5: a distant institution. And a lot of the times, like

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Speaker 5: a lot of outsourcing, what ends up being at the

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Speaker 5: center of the outsourcing. It's not always just some like

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Speaker 5: evil villain being like, I'm going to force you to

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Speaker 5: like what I want. It's what you're outsourcing yourself too.

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Speaker 5: Is a bureaucratic process that aims you at the kinds

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Speaker 5: of things that bureaucracies are good at aiming at, which

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Speaker 5: is easily, very visible, very legible countables.

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Speaker 1: Yeah, makes it easier. All right, I want to do

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Speaker 1: what I want to do, so people really kind of

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Speaker 1: understand this is I want to just like rapid fire

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Speaker 1: through a bunch of examples.

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Speaker 2: Are you ready for this?

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Speaker 4: I am so. I am. I have an espresso, I

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Speaker 4: am so ready.

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Speaker 1: All right, take a sip, and we will start with grades.

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Speaker 5: Grades, I think are one of the clearest examples to

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Speaker 5: me of one of the central dynamics in value capture.

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Speaker 4: So I see.

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Speaker 5: I mean, I teach I see this all the time.

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Speaker 5: I see students who don't know how to feel out

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Speaker 5: what's interesting to them and only know how to respond

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Speaker 5: in the direction of grades. And I was trying to

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Speaker 5: understand what was going on, why students were so great obsessed,

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Speaker 5: And I found this text that helped me understand so

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Speaker 5: much of what was going on. It's a Theodore Reporter's

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Speaker 5: trust in numbers, So theater reporter is a historian. He

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Speaker 5: is he studies quantification culture, and he would really interested

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Speaker 5: in the question of why politicians and bureaucrats often reach

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Speaker 5: compulsively for metrics and quantification to justify what they're doing

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Speaker 5: even when.

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Speaker 4: They're clearly bad.

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Speaker 5: And what he he ends up saying that it's not

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Speaker 5: the quantification and quality. He says, there are two kinds.

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Speaker 5: There are two ways of knowing about the world, qualitative

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Speaker 5: and quantitative. And it's not that there that one is better.

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Speaker 5: It's that they're tools for different tasks, and the problem

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Speaker 5: is compulsively reaching for one tool even when it's inappropriate.

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Speaker 5: So he says, the qualitative information justifying things in terms

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Speaker 5: of words, is good at being sensitive, subtle, open ended, dynamic,

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Speaker 5: at responding to all kinds of new information, but eving

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Speaker 5: multi dimensional. But it travels badly between contexts because it

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Speaker 5: requires a lot of shared background knowledge.

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Speaker 4: To understand right.

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Speaker 2: It takes more time and thought.

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Speaker 5: It takes more time and thought, and it takes a

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Speaker 5: lot of times expertise. I think this is the crucial thing.

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Speaker 5: So when I write to my students about what's going

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Speaker 5: on in.

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Speaker 4: Their essays, I write paragraphs about their.

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Speaker 5: Rigor their originality. I use a lot of philosophical terminology.

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Speaker 5: I talk about their ability to do various kinds of

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Speaker 5: critical reasoning. That stuff won't be comprehensible to say a

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Speaker 5: dean of the business school, and it won't aggregate, and

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Speaker 5: it won't aggregate precisely because in some sense, the important

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Speaker 5: thing is that when I'm writing to my students, and

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Speaker 5: when each different professor is writing to their students, they

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Speaker 5: can respond differently to students different abilities and interests. I

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Speaker 5: might write, if one of my students really cares about

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Speaker 5: writing quality and wants to be a writer, I can

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Speaker 5: focus on that a lot, But I won't do that

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Speaker 5: for other students, So it doesn't travel well, that's the

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Speaker 5: way he puts. It requires a lot of shared background knowledge.

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Speaker 5: So to get around this, we have this tool we've

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Speaker 5: made up in institutional context, that is institutional quantifications. And

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Speaker 5: what we do there is we identify some contact invariant kernel,

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Speaker 5: some chunk that everyone understands and everyone counts in the

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Speaker 5: same way, and we hold it fixed and we all

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Speaker 5: collect into that same bucket.

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Speaker 4: So this is like GPA.

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Speaker 5: Right, we all agree about approximately what an A, B

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Speaker 5: and C means we all agree about the numerical equivalents,

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Speaker 5: and this means that when I give my student an

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Speaker 5: A B, that information is instantly transferable to someone in

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Speaker 5: a totally different context. And because we all agree, it

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Speaker 5: can aggregate instantly, and this enables GPAs.

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Speaker 4: Right. Yeah, So one way to put it is that.

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Speaker 5: The reason that grades letter grades are so important socially

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Speaker 5: is that we've engineered them to be comprehensible to everybody,

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Speaker 5: and we've engineered them to be comprehensible by removing nuance

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Speaker 5: and context.

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Speaker 4: So it's not an accident. I think this is the thing.

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Speaker 5: This is This is the point I think where Porter

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Speaker 5: like this explanation like ripped my mind apart, and like

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Speaker 5: I felt like I matrix style saw the bones of

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Speaker 5: the universe I was in, which is that you know,

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Speaker 5: metrics are powerful and they're kind of inhumane and simplified,

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Speaker 5: and that's no accident. They're powerful because they've been engineered

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Speaker 5: to be informationally portable, and that the thing that makes

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Speaker 5: them portable is this context stripping, nuanced stripping, sensitivity stripping.

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Speaker 4: Yeah.

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Speaker 1: So when I was a professor, what was the big

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Speaker 1: thing I wanted my students to leave that course with

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Speaker 1: it was new ways of I was in the journalism apartment.

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Speaker 1: It was improving their writing. It was ways of thinking

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Speaker 1: about research, about talking to people, about sourcing. It was

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Speaker 1: all these things that were in theory going to help

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Speaker 1: them if they went into the world of journalism and

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Speaker 1: the world in general. So this is our This is

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Speaker 1: like the big, messy goal of the course. Right, it's

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Speaker 1: very hard to like measure that. But what did my

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Speaker 1: students really care about? It was the grade, right, and

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Speaker 1: that did those two things what was interesting didn't always align.

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Speaker 1: So I found that my best students were often B

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Speaker 1: plus A minus because I might give them an assignment

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Speaker 1: and they would in a really weird, creative way, but

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Speaker 1: they were taking a swing, and so I'd have to say,

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Speaker 1: all right, well, I really appreciate what you did here.

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Speaker 1: Here are all these edits, like great work, but like

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Speaker 1: B plus A minus. Meanwhile, the students who would consistently

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Speaker 1: get the a's were a little bit more robotic. I

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Speaker 1: was like, we're not taking the swing. We're doing things.

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Speaker 2: Exactly as prescribed because I need that A.

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Speaker 1: But it's those kids that would take the swings, that

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Speaker 1: were creative, that would think about things differently. Those were

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Speaker 1: the kids that would eventually go on and get those

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Speaker 1: big jobs in newsrooms.

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Speaker 4: Yeah.

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Speaker 5: I think an even clear example for me is learning outcomes.

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Speaker 5: So one of the things that got me into this

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Speaker 5: was in my first job, I was the learning outcomes liaison.

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Speaker 5: And what learning outcomes are are quantified measures of how

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Speaker 5: you have successfully taught your students. But importantly they're used

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Speaker 5: for institutional transparency. So what this means is like, the

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Speaker 5: Utah State legislature doesn't know which departments are full of

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Speaker 5: BS or not, and everyone's worried that philosophy is full

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Speaker 5: of BS, and so they want some kind of outcome

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Speaker 5: that they can check on. So if I say, like, look,

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Speaker 5: I'm going to teach my students to be more reflective

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Speaker 5: and more thoughtful, and they're like, and I'm like, I succeeded,

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Speaker 5: and they're like, how prove that to us, It's hard

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Speaker 5: for me to do so because that requires an exercise

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Speaker 5: of judgment. So what learning outcomes tend to focus on

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Speaker 5: is the kind of things that we can access mechanically,

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Speaker 5: So they tend to folks these days, they focus on

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Speaker 5: graduation rate, graduation speed, student evaluation scores, salary after a graduation.

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Speaker 4: But I just want here, let me point this out.

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Speaker 4: I think this is this is this is a great case.

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Speaker 5: So if I have a student who's in my class

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Speaker 5: and they were dead set on a career in like

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Speaker 5: some kind of business optimize for money, destroy the world,

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Speaker 5: do whatever, and I teach them a bunch of material

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Speaker 5: that shakes them up and makes them realize, oh my god,

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Speaker 5: relentlessly optimizing for money destroys the environment and also screws

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Speaker 5: over other people. And they also start to realize even

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Speaker 5: unhappy all the time, and they want to do something else,

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Speaker 5: So they take an extra year to figure out what

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Speaker 5: they actually want to do, and they look for an

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Speaker 5: ethical job. I have failed by learning outcomes. Yeah, though

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Speaker 5: learning outcomes we have because they took an extra year

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Speaker 5: and they took a lower paying job because they were

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Speaker 5: concerned about which jobs were ethical or not. But again,

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Speaker 5: you can easily see part of what's going on here

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Speaker 5: because there's not an easy way for that institution to

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Speaker 5: track whether or not students are more ethical. Right, there's

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Speaker 5: not a mechanical ethical assessment score, but there is a

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Speaker 5: mechanical graduation rate score. So there's a certain directionality to

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Speaker 5: what bureaucracies can function, can target.

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Speaker 4: And part of the problem with value capture is.

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Speaker 5: That you internalize into your own soul that kind of

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Speaker 5: bureaucratic thinness.

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Speaker 1: Yeah, and I think salaries are another great example. It's

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Speaker 1: like people get so focused on their salary and making

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Speaker 1: that number rise. But then the question is, well, why

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Speaker 1: do you want more money? It's well, probably one, maybe

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Speaker 1: it'll make me happier. I want more freedom, I want

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Speaker 1: more time, I want less stress in my life. And

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Speaker 1: to a certain extent, like a salary will do that

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Speaker 1: if you're a below a certain income oftentimes, but just

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Speaker 1: kind of chasing the number for the second the number, Well,

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Speaker 1: now the person's working more. Now they have more stress,

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Speaker 1: Now they have less freedoms because they have more job tasking,

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Speaker 1: all these things, and so it starts to it can't

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Speaker 1: really capture what that big goal is.

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Speaker 5: Yep, maybe you'll find this interesting. I think I remember

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Speaker 5: what we talked about last time. So when I started

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Speaker 5: this journey trying to think about this stuff, especially about

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Speaker 5: one of the places I started with my relationship with Twitter, Yeah,

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Speaker 5: which again I originally connected to some cool people.

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Speaker 4: Then I went like viral, like twice, and then it

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Speaker 4: was over.

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Speaker 5: I was like two focused For a while, I originally

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Speaker 5: thought this was a story about addictive apps and app design.

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Speaker 5: And there's this really lovely book that is what everyone

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Speaker 5: should read from Natasha dau Shull called Addiction by Design,

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Speaker 5: and it's about how the vaguus gambling industry optimized video

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Speaker 5: poker to addict us to our serotonin spikes, and then

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Speaker 5: that got exported to like Facebook and Twitter and World

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Speaker 5: of Warcraft and there's this very specific user interface design

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Speaker 5: that hacks your brain. That's what I thought it was about.

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Speaker 5: There's an addiction via user interface design, and that's a

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Speaker 5: twenty year old story. And the more research I did,

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Speaker 5: the more I thought that's the wrong story. That's like

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Speaker 5: one percent of the story, because so much of what's

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Speaker 5: going on involves no carefully gamified user interface apps. A

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Speaker 5: lot of what's going on is educational institutions being warped

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Speaker 5: by the US News and World Report university ranking. Right,

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Speaker 5: there's no app there, right, there's just a ranking published

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Speaker 5: in some magazine. And similarly, I think what's actually going on,

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Speaker 5: and I think Salary is such a clear vision of this,

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Speaker 5: is that what we're orienting towards is the kinds of

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Speaker 5: things that require no context to count, and that that

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Speaker 5: is an orientation towards quantification, that it's part of this

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Speaker 5: bureaucratic landscape, and that the story is actually about a

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Speaker 5: thousand years old. It's about a thousand years of a

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Speaker 5: slow and steady progress away from sensitive, high context judgment

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Speaker 5: towards highly accessible, simplified targets. Yeah, and I just want

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Speaker 5: to say it's not I'm not saying that metrics are

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Speaker 5: always bad, because the thing that makes them good is

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Speaker 5: exactly this thing, the thing the idea that porter has,

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Speaker 5: this engineered portability. It's not that metrics are bad, it's

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Speaker 5: that they have a very powerful function for which there

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Speaker 5: is a very powerful design price. The function is portability.

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Speaker 5: The cost is low sensitivity.

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Speaker 1: Yeah, we start to measure it and then we get

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Speaker 1: obsessed with that making that measurement go a certain way,

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Speaker 1: but we lose sight of the reason we're doing the

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Speaker 1: thing in the first place.

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Speaker 2: One example I love that you.

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Speaker 1: Use, and I think we talked about this last time

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Speaker 1: we met is wine and Robert B.

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Speaker 2: Parker walk us through the wine thing.

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Speaker 5: So what happened was wines go really well with food.

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Speaker 5: This is part of the magic wine, right. If you

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Speaker 5: have wine with food. It reacts the wine changes the

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Speaker 5: states to the food changes. There's often some interaction. And

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Speaker 5: some folks, Robert Parker most famously, wanted to make a

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Speaker 5: more objective wine scoring system, and so they needed to

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Speaker 5: be able to test wines against each other and rank

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Speaker 5: them against each other and give them some kind of score.

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Speaker 5: But the problem is if you have wine with food,

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Speaker 5: that's too variable, right, Like if I have one wine

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Speaker 5: with chicken, and I have another wine with sushi, and

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Speaker 5: I have another wine just with some chips, like, maybe

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Speaker 5: those things are interfering with each other. So to render

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Speaker 5: objective judgments, they created a wine scoring environment, a judging environment,

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Speaker 5: in which they removed food, which was a highly variable,

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Speaker 5: highly contact specific factor, and they judged wines against.

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Speaker 4: Each other without food. Food. But this.

441
00:22:58,640 --> 00:23:01,000
Speaker 5: Points us in the direction of a different kind of wine.

442
00:23:01,040 --> 00:23:03,040
Speaker 5: So this is what gives us what are now called

443
00:23:03,080 --> 00:23:06,199
Speaker 5: fruit bombs. Right, So a lot of modern wines have

444
00:23:06,280 --> 00:23:09,919
Speaker 5: big flavors, explode on the palette, are really loud, but

445
00:23:10,000 --> 00:23:12,959
Speaker 5: they don't interact well with food. They don't do anything interesting,

446
00:23:13,000 --> 00:23:16,560
Speaker 5: they don't do anything dynamic. They don't like have this live, vibrating,

447
00:23:16,640 --> 00:23:20,960
Speaker 5: resonant changing weird thing that was what so many people

448
00:23:20,960 --> 00:23:24,080
Speaker 5: loved about wine in the first place. So the story

449
00:23:24,119 --> 00:23:27,760
Speaker 5: of wine culture is that the scoring system in the

450
00:23:27,840 --> 00:23:34,480
Speaker 5: quest for objectivity cut out highly variable, context specific interactions

451
00:23:34,880 --> 00:23:37,040
Speaker 5: to create something that looked like objective judgment.

452
00:23:37,560 --> 00:23:39,080
Speaker 4: And they did create.

453
00:23:40,240 --> 00:23:44,480
Speaker 5: A more objective judgment of equality that cut out a

454
00:23:44,520 --> 00:23:46,560
Speaker 5: lot of what we originally cared about in the first place.

455
00:23:47,040 --> 00:23:49,600
Speaker 4: Right, So a lot of the new wines are bad

456
00:23:49,640 --> 00:23:50,040
Speaker 4: with food.

457
00:23:50,400 --> 00:23:53,119
Speaker 1: Yeah, they taste, So they have people taste all these

458
00:23:53,160 --> 00:23:55,960
Speaker 1: wines without food, and then people give them a number.

459
00:23:56,119 --> 00:23:58,479
Speaker 1: And the magazine was Wine Advocate. Is that correct?

460
00:23:58,720 --> 00:23:58,960
Speaker 4: Yeah?

461
00:23:59,040 --> 00:24:01,600
Speaker 1: So then Wine Advocate, you know, publishes this wine got

462
00:24:01,600 --> 00:24:04,919
Speaker 1: a ninety one. This one got a ninety five, but

463
00:24:05,000 --> 00:24:08,600
Speaker 1: it gets that score without the important factor of food.

464
00:24:08,600 --> 00:24:10,919
Speaker 1: And what I thought is most interesting about this is

465
00:24:10,920 --> 00:24:15,200
Speaker 1: what happens next is wine makers go, oh, well, these

466
00:24:15,640 --> 00:24:18,640
Speaker 1: bottles that are getting a ninety five plus, like they're

467
00:24:18,720 --> 00:24:21,600
Speaker 1: selling at whatever three, four or five times the rate.

468
00:24:21,680 --> 00:24:23,920
Speaker 1: Like the way you make money in the wine industry

469
00:24:23,960 --> 00:24:26,359
Speaker 1: now becomes you got to get a bottle that scores

470
00:24:26,359 --> 00:24:29,240
Speaker 1: a ninety five and that might be different of how

471
00:24:29,280 --> 00:24:31,760
Speaker 1: you made wine before. That made it interesting and so

472
00:24:31,840 --> 00:24:34,320
Speaker 1: this like shifts the entire industry to being like, we

473
00:24:34,400 --> 00:24:37,439
Speaker 1: need to get a ninety five bottle, and that just

474
00:24:37,560 --> 00:24:40,520
Speaker 1: fundamentally changes the industry forever and how winds taste and

475
00:24:40,520 --> 00:24:44,000
Speaker 1: to your point, removes all that important context of like

476
00:24:44,040 --> 00:24:47,720
Speaker 1: you drink it with food, we're looking at us.

477
00:24:47,760 --> 00:24:51,480
Speaker 5: In these are cases where the context of actual use

478
00:24:51,680 --> 00:24:54,320
Speaker 5: is different from the context of judgment. And if you're

479
00:24:54,440 --> 00:24:58,280
Speaker 5: hyper optimizing, let me give you Okay, I thought of another.

480
00:24:58,840 --> 00:24:59,879
Speaker 4: I think I don't think.

481
00:24:59,720 --> 00:25:01,520
Speaker 5: I tell do about this one because I thought about this.

482
00:25:01,720 --> 00:25:07,119
Speaker 5: I figured this out after we talk. Maybe here's another example.

483
00:25:07,920 --> 00:25:11,280
Speaker 5: I started noticing when I started buying a lot of

484
00:25:11,320 --> 00:25:14,800
Speaker 5: clothes online that were well reviewed, that a lot of

485
00:25:14,800 --> 00:25:17,280
Speaker 5: the clothes I would get would show up and were

486
00:25:17,320 --> 00:25:21,400
Speaker 5: super soft and comfortable and would fall apart in two months.

487
00:25:21,160 --> 00:25:21,720
Speaker 2: I've been there.

488
00:25:22,040 --> 00:25:26,639
Speaker 5: The reason is because I think, here's my guess, that

489
00:25:27,160 --> 00:25:31,480
Speaker 5: people review clothes after they put them on immediately. Nine

490
00:25:31,920 --> 00:25:35,280
Speaker 5: percent of online clothing reviews are I got it, I

491
00:25:35,320 --> 00:25:36,600
Speaker 5: take it out of the package I put on. Oh,

492
00:25:36,680 --> 00:25:40,159
Speaker 5: it feels so soft, it's so good, five star reviews.

493
00:25:40,840 --> 00:25:45,159
Speaker 5: Almost nobody comes back after two years to review a

494
00:25:45,160 --> 00:25:50,440
Speaker 5: piece of clothing, and so online marketers to figure it

495
00:25:50,440 --> 00:25:52,359
Speaker 5: out that what does well is high star reviews, and

496
00:25:52,400 --> 00:25:54,359
Speaker 5: the way you optimize for that is you make clothes

497
00:25:54,400 --> 00:25:54,920
Speaker 5: super soft.

498
00:25:55,000 --> 00:25:56,880
Speaker 4: And the way you do that is actually you like.

499
00:25:56,880 --> 00:25:58,720
Speaker 5: Acid to wash the hell out of them at the factory,

500
00:25:59,040 --> 00:26:02,040
Speaker 5: and so they come with the softness of the most

501
00:26:02,040 --> 00:26:03,920
Speaker 5: delicious piece of clothing you've had for four you and

502
00:26:04,000 --> 00:26:06,640
Speaker 5: then they fall apart in a small amount of time.

503
00:26:06,960 --> 00:26:10,439
Speaker 5: It's actually super weirdly similar to the thing I was

504
00:26:10,560 --> 00:26:19,440
Speaker 5: missing about Twitter, where, among other things, social media captures

505
00:26:20,400 --> 00:26:23,840
Speaker 5: likes at the moment of seeing No one thinks about

506
00:26:23,840 --> 00:26:26,199
Speaker 5: a tweet for two months and then comes back to

507
00:26:26,240 --> 00:26:27,160
Speaker 5: it and finds it.

508
00:26:27,160 --> 00:26:29,960
Speaker 1: It's like, right finds the person's profile, goes like fifty

509
00:26:30,000 --> 00:26:32,040
Speaker 1: tweets down and goes, I need to like that right

510
00:26:32,080 --> 00:26:33,040
Speaker 1: now two months later.

511
00:26:34,320 --> 00:26:40,200
Speaker 5: Yeah, the context of capture is immediate, and so that

512
00:26:40,200 --> 00:26:42,639
Speaker 5: that's another way in which the scoring deviates from what

513
00:26:42,680 --> 00:26:45,440
Speaker 5: we actually find important. I mean, I guess the general

514
00:26:45,520 --> 00:26:48,919
Speaker 5: lesson through a lot of this is that it's not

515
00:26:49,080 --> 00:26:54,920
Speaker 5: that quantifications are bad, but it is that they will

516
00:26:54,960 --> 00:26:58,800
Speaker 5: often miss in systematic way. It's what we actually care

517
00:26:58,840 --> 00:27:04,479
Speaker 5: about because of the specific constraints on how we capture

518
00:27:04,480 --> 00:27:08,120
Speaker 5: the information and what kinds of information we can aim

519
00:27:08,160 --> 00:27:09,479
Speaker 5: at capturing at scale.

520
00:27:09,640 --> 00:27:11,560
Speaker 1: Yeah, we're going to take a quick break and then

521
00:27:11,560 --> 00:27:13,280
Speaker 1: when we come back, we are going to answer the

522
00:27:13,359 --> 00:27:26,640
Speaker 1: big question. Why are we so obsessed with numbers? So

523
00:27:26,680 --> 00:27:29,760
Speaker 1: to pull back your book is called the score, and

524
00:27:29,840 --> 00:27:34,240
Speaker 1: score is often a number. Why do quantifications capture us

525
00:27:34,440 --> 00:27:35,359
Speaker 1: in the first place?

526
00:27:36,119 --> 00:27:37,360
Speaker 2: What is it about them?

527
00:27:37,920 --> 00:27:41,359
Speaker 4: I think? So this was a huge question for me.

528
00:27:42,520 --> 00:27:45,160
Speaker 4: It's just like, look, it's just it's so weird. It's

529
00:27:45,200 --> 00:27:45,480
Speaker 4: just this.

530
00:27:45,720 --> 00:27:47,560
Speaker 5: You put something in a number and somethen we start

531
00:27:47,640 --> 00:27:53,480
Speaker 5: caring about it. One answer is that. So the way

532
00:27:53,520 --> 00:27:56,520
Speaker 5: that a lot of philosophers of technology put it is

533
00:27:56,520 --> 00:27:58,280
Speaker 5: that when you have a technology, you should think about

534
00:27:58,320 --> 00:28:00,560
Speaker 5: what it affords. Its affordance is this? That means what

535
00:28:00,680 --> 00:28:04,280
Speaker 5: it makes easy and what it makes difficult. Right, here's

536
00:28:04,320 --> 00:28:06,480
Speaker 5: one of the closs I don't know if this will

537
00:28:06,480 --> 00:28:08,760
Speaker 5: be meaningful, But a factory, what does a factory afford?

538
00:28:09,200 --> 00:28:12,040
Speaker 5: Factories afford making lots of things cheaply? What do they

539
00:28:12,080 --> 00:28:16,080
Speaker 5: not afford making things are custom tailored to a particular interest?

540
00:28:16,200 --> 00:28:16,440
Speaker 4: Right?

541
00:28:17,280 --> 00:28:20,720
Speaker 5: But another thing I want to say is that quantifications

542
00:28:20,760 --> 00:28:26,320
Speaker 5: afford comparison. Right, So if I say I'm happy in

543
00:28:26,320 --> 00:28:30,440
Speaker 5: my job, it's really interesting, it's really stressful. And then

544
00:28:30,480 --> 00:28:33,399
Speaker 5: you say I'm happy in my job it's really chill,

545
00:28:33,640 --> 00:28:35,120
Speaker 5: and I can be really relaxed.

546
00:28:35,240 --> 00:28:37,480
Speaker 4: How do we compare those two? That's really difficult.

547
00:28:37,720 --> 00:28:40,800
Speaker 5: If, on the other hand, I say I make one

548
00:28:40,880 --> 00:28:42,720
Speaker 5: hundred thousand dollars a year and you say I make

549
00:28:42,760 --> 00:28:45,920
Speaker 5: seventy thousand dollars a year, there's an instant and immediate comparison.

550
00:28:45,960 --> 00:28:48,080
Speaker 5: We don't even have to work for it, right, So

551
00:28:48,200 --> 00:28:52,960
Speaker 5: one thing is it makes comparison seamless. That and insofar

552
00:28:53,000 --> 00:28:55,280
Speaker 5: as we like to compare each other, that's one thing.

553
00:28:55,760 --> 00:29:00,400
Speaker 5: But I think the deep story is porter story that

554
00:29:00,440 --> 00:29:06,000
Speaker 5: what quantifications do is they enable us to be completely

555
00:29:06,040 --> 00:29:08,719
Speaker 5: comprehensible to each other. Instead of having to justify myself

556
00:29:08,760 --> 00:29:11,560
Speaker 5: in some weird way, I can justify myself in a

557
00:29:11,560 --> 00:29:15,520
Speaker 5: way that everybody understands instantly.

558
00:29:15,120 --> 00:29:16,800
Speaker 1: And can generally agree upon.

559
00:29:17,760 --> 00:29:20,120
Speaker 5: Yeah, and can generally agree upon. I mean, here's one

560
00:29:20,120 --> 00:29:21,840
Speaker 5: way to notice it's not just a number. I'll tell

561
00:29:21,880 --> 00:29:25,520
Speaker 5: you why, it's not just any Yeah. I can create

562
00:29:25,560 --> 00:29:30,760
Speaker 5: a private journal and write how many experiences of total

563
00:29:30,800 --> 00:29:33,520
Speaker 5: transcendence I had in my outdoor exercise, and I can

564
00:29:33,560 --> 00:29:35,680
Speaker 5: take that number up, but it's not going to be

565
00:29:35,720 --> 00:29:39,400
Speaker 5: meaningful to anyone else. Right on the other hand, if

566
00:29:39,400 --> 00:29:43,719
Speaker 5: I'm like, what's my mileage or what's my weight loss

567
00:29:43,920 --> 00:29:47,000
Speaker 5: or what's my calories burned, these are things that are

568
00:29:47,000 --> 00:29:49,800
Speaker 5: meaningful to other people because they're aimed at targets that

569
00:29:49,880 --> 00:29:53,400
Speaker 5: are cross that are cross contextual. So the thing I

570
00:29:53,440 --> 00:29:58,200
Speaker 5: think that's really doing the work here is not merely

571
00:29:58,240 --> 00:30:01,320
Speaker 5: that there's a number, but that number is based on

572
00:30:01,400 --> 00:30:04,719
Speaker 5: an infrastructure of counting things that we all recognize. So

573
00:30:04,720 --> 00:30:07,960
Speaker 5: it's I think it's more about this kind of constructed, portable,

574
00:30:08,480 --> 00:30:11,440
Speaker 5: intercomprehensibility that ties us to the kinds of things that

575
00:30:11,520 --> 00:30:15,280
Speaker 5: everyone can recognize, rather than just a pure.

576
00:30:15,480 --> 00:30:16,840
Speaker 2: That that does.

577
00:30:17,040 --> 00:30:20,920
Speaker 1: I think there's also we talked about how a measurement

578
00:30:21,080 --> 00:30:24,680
Speaker 1: can give us a sense of certainty and like life

579
00:30:24,720 --> 00:30:28,160
Speaker 1: is really complex, chaotic, how do you know you did

580
00:30:28,160 --> 00:30:30,640
Speaker 1: the right thing the wrong thing? But if you can

581
00:30:30,680 --> 00:30:34,720
Speaker 1: see the number go from two to four, you go, well,

582
00:30:34,720 --> 00:30:37,600
Speaker 1: that was an increase, Okay, I feel okay, I think

583
00:30:37,640 --> 00:30:41,760
Speaker 1: your I think your friends, your climber friend step count

584
00:30:41,920 --> 00:30:45,959
Speaker 1: is a great example with rock climbing as a workout.

585
00:30:46,320 --> 00:30:49,120
Speaker 1: How do you track that? It's hard, right, there's so

586
00:30:49,160 --> 00:30:52,440
Speaker 1: many different variables. You're doing all these different movements. How

587
00:30:52,480 --> 00:30:55,240
Speaker 1: do you really know if you got that much stronger immediately?

588
00:30:55,280 --> 00:30:57,200
Speaker 1: Like you could track that, you know over time. Alive

589
00:30:57,240 --> 00:30:59,640
Speaker 1: was able to do this a month later. But with

590
00:30:59,680 --> 00:31:03,040
Speaker 1: stuff just did you hit ten thousand or not? Oh

591
00:31:03,080 --> 00:31:05,000
Speaker 1: you didn't hit it? You failed today?

592
00:31:05,840 --> 00:31:06,320
Speaker 2: You hit it?

593
00:31:06,760 --> 00:31:09,520
Speaker 1: Congratulations, you're okay, I'm good, I'm healthy today.

594
00:31:10,400 --> 00:31:10,600
Speaker 4: Yeah.

595
00:31:10,600 --> 00:31:12,640
Speaker 5: I think a lot of these things are I want

596
00:31:12,640 --> 00:31:14,120
Speaker 5: to call Okay, this is the dumbest room. I want

597
00:31:14,120 --> 00:31:17,360
Speaker 5: to call them like binarization devices or clarity devices.

598
00:31:17,440 --> 00:31:17,720
Speaker 4: Yeah.

599
00:31:17,760 --> 00:31:19,880
Speaker 5: Like, and you can even see these in games too.

600
00:31:19,920 --> 00:31:22,800
Speaker 5: So here's here's the dumbest Maybe you'll find this interesting.

601
00:31:22,800 --> 00:31:25,120
Speaker 5: This is my favorite dumb thought from writing this book

602
00:31:25,240 --> 00:31:26,360
Speaker 5: that I don't think anyone else cares.

603
00:31:26,400 --> 00:31:26,880
Speaker 2: Are awesome.

604
00:31:27,160 --> 00:31:30,320
Speaker 5: So if you have a bunch of people who are

605
00:31:30,400 --> 00:31:33,560
Speaker 5: very athletic, and you have them interact in some way,

606
00:31:33,600 --> 00:31:34,040
Speaker 5: and you're like.

607
00:31:34,000 --> 00:31:35,880
Speaker 4: Okay, pick the best athlete.

608
00:31:36,640 --> 00:31:39,600
Speaker 5: Even though we're narrowing down just athleticism, that is such

609
00:31:39,600 --> 00:31:42,160
Speaker 5: a complex judgment. You're talking about skill, you're talking about grace,

610
00:31:42,320 --> 00:31:45,160
Speaker 5: you're talking about and even if you do a particular skill,

611
00:31:45,280 --> 00:31:50,920
Speaker 5: like who's better at like fast maneuvering? Like even then

612
00:31:51,000 --> 00:31:53,840
Speaker 5: like it's really like you might we might all look

613
00:31:53,880 --> 00:31:56,200
Speaker 5: at a bunch of people like moving around each other

614
00:31:56,320 --> 00:31:59,960
Speaker 5: trying to and we can't make a clear judgment who

615
00:32:00,080 --> 00:32:02,520
Speaker 5: want And then we put in a basketball net and

616
00:32:02,560 --> 00:32:05,040
Speaker 5: we say, okay, get the ball through the hoop. That

617
00:32:05,160 --> 00:32:10,440
Speaker 5: just instantly clarifies things. Right, that's a that's a legibility device,

618
00:32:10,440 --> 00:32:13,600
Speaker 5: avinorization device. Suddenly all of this stuff is aimed at

619
00:32:13,600 --> 00:32:17,240
Speaker 5: a crux that everyone can read, right.

620
00:32:17,360 --> 00:32:17,959
Speaker 4: Yeah.

621
00:32:18,000 --> 00:32:20,320
Speaker 5: And so one of the reasons I think we find

622
00:32:20,480 --> 00:32:24,400
Speaker 5: sports so attractive is that there are these artificial environments

623
00:32:24,480 --> 00:32:29,000
Speaker 5: where we can set these binarization devices, right, and then

624
00:32:29,080 --> 00:32:31,520
Speaker 5: everyone can look up and suddenly it's clear we don't

625
00:32:31,520 --> 00:32:34,800
Speaker 5: have to dispute anymore about who was the greatest.

626
00:32:34,800 --> 00:32:38,560
Speaker 4: We can just look and count. Yeah.

627
00:32:38,640 --> 00:32:42,720
Speaker 5: But in sports, Uh, in sports, we're not transforming anything real.

628
00:32:43,640 --> 00:32:47,960
Speaker 5: When on Twitter we're transforming communication or politics or healthy

629
00:32:48,000 --> 00:32:53,040
Speaker 5: society into this minorization that doesn't capture everything.

630
00:32:53,240 --> 00:32:57,920
Speaker 1: Yeah, this gets this gets into your idea of games

631
00:32:57,960 --> 00:33:01,280
Speaker 1: and what the point kind of a game is. And

632
00:33:01,280 --> 00:33:03,560
Speaker 1: it's like you've kind of had these collision of these

633
00:33:03,560 --> 00:33:06,400
Speaker 1: two ideas. So walk us through what a game is

634
00:33:06,440 --> 00:33:09,160
Speaker 1: and then kind of get into that idea of games

635
00:33:09,200 --> 00:33:12,800
Speaker 1: that are sort of siloed in these sort of artificial things,

636
00:33:12,880 --> 00:33:14,960
Speaker 1: versus when we take the same idea of a game

637
00:33:15,000 --> 00:33:18,760
Speaker 1: and we place it on these societal big questions in

638
00:33:18,800 --> 00:33:19,280
Speaker 1: our lives.

639
00:33:20,160 --> 00:33:20,360
Speaker 2: Yeah.

640
00:33:20,920 --> 00:33:24,000
Speaker 5: Yeah, So I started writing this book, So I did.

641
00:33:24,560 --> 00:33:27,000
Speaker 5: I had a long journey down one of the weirdest

642
00:33:27,000 --> 00:33:29,360
Speaker 5: paths in philosophy. I like dedicated myself to like the

643
00:33:29,360 --> 00:33:32,160
Speaker 5: philosophy of games for five years, which everyone thinks is

644
00:33:32,360 --> 00:33:34,920
Speaker 5: weird and dumb because you don't get into highly ranked

645
00:33:34,920 --> 00:33:35,840
Speaker 5: philosophy journals.

646
00:33:35,960 --> 00:33:38,720
Speaker 1: Right published like a hidden This was like a hidden

647
00:33:38,760 --> 00:33:39,520
Speaker 1: thing you were doing.

648
00:33:39,600 --> 00:33:39,800
Speaker 3: Right.

649
00:33:39,840 --> 00:33:42,240
Speaker 1: This was like I don't tell anyone about this, I just.

650
00:33:42,600 --> 00:33:43,960
Speaker 2: Talking about it.

651
00:33:43,960 --> 00:33:45,680
Speaker 5: It was the thing I thought was the most interesting,

652
00:33:45,720 --> 00:33:48,400
Speaker 5: but people didn't think it was really anyway. And then

653
00:33:49,120 --> 00:33:53,080
Speaker 5: I start I wrote this book about how games and

654
00:33:53,120 --> 00:33:57,320
Speaker 5: scoring systems are these beautiful devices for crystallizing action. And

655
00:33:57,360 --> 00:33:59,720
Speaker 5: then I started worrying about metrics, and I wrote this

656
00:33:59,760 --> 00:34:02,760
Speaker 5: book about how scoring systems in metrics drained.

657
00:34:02,520 --> 00:34:03,400
Speaker 4: The life out of everything.

658
00:34:03,440 --> 00:34:07,719
Speaker 5: And then I realized my two major views completely contradicted

659
00:34:07,760 --> 00:34:11,520
Speaker 5: each other, and that if my games view was right,

660
00:34:11,560 --> 00:34:14,439
Speaker 5: then gamification should be awesome, and if my metrics view

661
00:34:14,520 --> 00:34:17,800
Speaker 5: was right, then games should be terrible. And I couldn't

662
00:34:17,840 --> 00:34:21,759
Speaker 5: figure out why scoring systems hit so different, why they

663
00:34:21,760 --> 00:34:25,120
Speaker 5: were so great in games and so horrible in our institutions.

664
00:34:25,120 --> 00:34:27,400
Speaker 5: And so this is the thing I was trying to

665
00:34:27,400 --> 00:34:32,520
Speaker 5: figure out. Games for me are just this super interesting

666
00:34:32,640 --> 00:34:36,080
Speaker 5: thing because what we do in a game is we

667
00:34:36,760 --> 00:34:41,279
Speaker 5: take on alternate desires. This is I think the most was.

668
00:34:41,600 --> 00:34:42,960
Speaker 5: I spent a lot of time trying to figure out

669
00:34:43,040 --> 00:34:45,920
Speaker 5: what the heart of the game was. And there are

670
00:34:45,920 --> 00:34:49,160
Speaker 5: two things that I think really helped explain it to me.

671
00:34:50,000 --> 00:34:54,000
Speaker 5: One was Ryder Kinnintia, my favorite board game designer. He

672
00:34:54,040 --> 00:34:56,080
Speaker 5: has a game design Lecturer where he says, the most

673
00:34:56,080 --> 00:34:59,240
Speaker 5: important tool in my game design toolbox is the scoring

674
00:34:59,280 --> 00:35:01,960
Speaker 5: system because it sets the player's desires in the game.

675
00:35:02,000 --> 00:35:02,960
Speaker 4: It tells them what to want.

676
00:35:03,400 --> 00:35:05,960
Speaker 5: It tells them whether they're hand to make baskets or

677
00:35:05,960 --> 00:35:08,040
Speaker 5: collect sheep or get to the top of mountains. It

678
00:35:08,080 --> 00:35:10,040
Speaker 5: tells them whether they're acting on their own or with

679
00:35:10,120 --> 00:35:12,600
Speaker 5: a team together or half of you are on one

680
00:35:12,600 --> 00:35:13,480
Speaker 5: team that gets happed.

681
00:35:13,360 --> 00:35:14,680
Speaker 4: Like it sets your desires.

682
00:35:15,600 --> 00:35:19,360
Speaker 5: The other major account is from the philosopher Bernard Suits,

683
00:35:19,360 --> 00:35:21,480
Speaker 5: who in the Book of the Grasshopper defines a game

684
00:35:21,520 --> 00:35:22,840
Speaker 5: in the following way.

685
00:35:22,920 --> 00:35:23,840
Speaker 4: He says a game.

686
00:35:24,360 --> 00:35:28,279
Speaker 5: To play a game is to voluntarily take on unnecessary

687
00:35:28,320 --> 00:35:32,759
Speaker 5: obstacles to create the process of struggling to overcome them.

688
00:35:32,880 --> 00:35:34,279
Speaker 1: You have to create a pain in the ass, an

689
00:35:34,320 --> 00:35:37,120
Speaker 1: artificial pain in the ass, and that's what makes it interesting.

690
00:35:37,239 --> 00:35:39,600
Speaker 1: It's like the marathon. At the end of the day,

691
00:35:39,640 --> 00:35:42,359
Speaker 1: you cross this finish line. But if you were to

692
00:35:42,480 --> 00:35:45,800
Speaker 1: just skip out the twenty six miles of running altogether

693
00:35:45,840 --> 00:35:47,520
Speaker 1: and you just took a tab to the finish line,

694
00:35:47,520 --> 00:35:50,439
Speaker 1: it's like, well, that's stupid, that wouldn't be fulfilling. It's

695
00:35:50,480 --> 00:35:53,640
Speaker 1: the act of the hell of running the twenty six

696
00:35:53,680 --> 00:35:55,640
Speaker 1: miles and then crossing the finish line.

697
00:35:55,680 --> 00:35:56,880
Speaker 2: That's what makes it a marathon.

698
00:35:57,239 --> 00:35:59,640
Speaker 5: Yeah, so the way that Suits puts it, I think

699
00:35:59,680 --> 00:36:02,880
Speaker 5: the second way he puts it, sorry, I think philosopheric

700
00:36:02,960 --> 00:36:05,040
Speaker 5: it's a're sexy. So the sexiest way he puts it

701
00:36:05,120 --> 00:36:11,480
Speaker 5: is that in games, the goals are partially constituted by

702
00:36:11,480 --> 00:36:14,560
Speaker 5: the obstacles. So if you're just trying to do something

703
00:36:14,680 --> 00:36:17,200
Speaker 5: in non game life, practically, you just do it the

704
00:36:17,200 --> 00:36:19,440
Speaker 5: most efficient way you can. It doesn't matter how you

705
00:36:19,520 --> 00:36:21,560
Speaker 5: do it right. If if I just want to be

706
00:36:21,640 --> 00:36:26,560
Speaker 5: at this spot right because it has some stuff I want,

707
00:36:26,640 --> 00:36:30,080
Speaker 5: just get there the fastest way you can. But crossing

708
00:36:30,120 --> 00:36:33,480
Speaker 5: the finish line of a marathon is a goal, but

709
00:36:33,640 --> 00:36:37,600
Speaker 5: that goal is constituted by obedience to constraints. So if

710
00:36:37,640 --> 00:36:39,920
Speaker 5: I took a cab, it doesn't count as crossing the

711
00:36:39,920 --> 00:36:42,200
Speaker 5: finish line. If I use a step ladder on the

712
00:36:42,200 --> 00:36:45,120
Speaker 5: basketball court, it doesn't count as making a basket. What

713
00:36:45,200 --> 00:36:47,799
Speaker 5: making a basket is is getting involved with a net

714
00:36:47,840 --> 00:36:50,400
Speaker 5: while following all these constraints and rules. And what this

715
00:36:50,520 --> 00:36:54,440
Speaker 5: teaches us, I think, is that the struggle has to

716
00:36:54,480 --> 00:36:57,439
Speaker 5: be essential, to the point that the difference for suit

717
00:36:57,560 --> 00:37:01,120
Speaker 5: between ordinary life practical life in games is In an

718
00:37:01,200 --> 00:37:03,719
Speaker 5: ordinary life, we often just want stuff and we'll do

719
00:37:03,800 --> 00:37:05,920
Speaker 5: any we'll try to get it as efficiently as possible.

720
00:37:06,400 --> 00:37:11,440
Speaker 5: And games are inefficiencies on purpose. Yeah, we force ourselves

721
00:37:11,480 --> 00:37:16,880
Speaker 5: into into efficiencies. Why would we do that only if

722
00:37:17,719 --> 00:37:20,920
Speaker 5: much or all of the value came from the process

723
00:37:20,960 --> 00:37:23,120
Speaker 5: of struggling rather than the outcome.

724
00:37:23,560 --> 00:37:24,920
Speaker 1: We're going to take a quick break and then when

725
00:37:24,920 --> 00:37:27,040
Speaker 1: we come back, we're going to talk about why games

726
00:37:27,080 --> 00:37:39,120
Speaker 1: and gamification capture us in daily life. So talk to

727
00:37:39,239 --> 00:37:43,759
Speaker 1: us about how in the game world, like you're playing monopoly,

728
00:37:43,920 --> 00:37:45,600
Speaker 1: the point is it's a parent right, It's just this

729
00:37:45,640 --> 00:37:47,280
Speaker 1: little fake thing you do with your friends.

730
00:37:48,480 --> 00:37:49,080
Speaker 2: You rob them.

731
00:37:49,120 --> 00:37:51,600
Speaker 1: Let's say you screw them over on a move. They

732
00:37:51,600 --> 00:37:53,719
Speaker 1: don't actually care. They're like, that's the point of it.

733
00:37:53,800 --> 00:37:55,960
Speaker 1: They don't hate you for doing that. But when we

734
00:37:56,000 --> 00:37:59,759
Speaker 1: apply the sort of same structures to daily life, how

735
00:37:59,840 --> 00:38:00,719
Speaker 1: can not backfire?

736
00:38:01,520 --> 00:38:02,120
Speaker 4: Yeah?

737
00:38:02,400 --> 00:38:07,200
Speaker 5: So with games, I think an important thing to understand

738
00:38:07,239 --> 00:38:11,040
Speaker 5: about games is that what we're doing is not what

739
00:38:11,080 --> 00:38:13,799
Speaker 5: we're doing, or the point is not the point. So

740
00:38:15,000 --> 00:38:17,280
Speaker 5: one way to put it, I think is that in games,

741
00:38:17,880 --> 00:38:20,319
Speaker 5: the goal and the purpose come apart. The goal is

742
00:38:20,320 --> 00:38:21,719
Speaker 5: what you're trying to pursue in the game, and the

743
00:38:21,719 --> 00:38:25,360
Speaker 5: purpose is the larger reason you're doing it. So the

744
00:38:25,400 --> 00:38:28,640
Speaker 5: goal of charades is to win by communicating the purpose

745
00:38:28,680 --> 00:38:30,480
Speaker 5: is to have fun, and you can tell that that's

746
00:38:30,520 --> 00:38:32,680
Speaker 5: actually the purpose because if you lose and had a

747
00:38:32,719 --> 00:38:34,920
Speaker 5: great time, you succeeded.

748
00:38:35,000 --> 00:38:35,600
Speaker 4: Yeah, right.

749
00:38:35,840 --> 00:38:38,360
Speaker 5: Similarly, for me rock climbing, the point of rock climbing

750
00:38:38,640 --> 00:38:41,680
Speaker 5: is to relax myself and enter a meditative state and

751
00:38:41,760 --> 00:38:44,360
Speaker 5: kind of clear my brain. And what's important is to

752
00:38:44,480 --> 00:38:46,279
Speaker 5: do that, I have to go to the climbing gym

753
00:38:46,400 --> 00:38:49,600
Speaker 5: or go to the crag and try just focus intensely

754
00:38:49,760 --> 00:38:53,160
Speaker 5: on getting to the top. But even if I completely

755
00:38:53,200 --> 00:38:55,880
Speaker 5: fail at getting to the top, when I leave, my

756
00:38:55,960 --> 00:38:57,839
Speaker 5: mind will be clear, my body will feel good.

757
00:38:57,920 --> 00:38:58,719
Speaker 2: You're still good to go.

758
00:38:59,160 --> 00:38:59,880
Speaker 4: You're still good to go.

759
00:39:01,360 --> 00:39:05,120
Speaker 5: So I call this striving play. So striving play is

760
00:39:05,120 --> 00:39:07,960
Speaker 5: something where you're aiming at a goal, but your real

761
00:39:08,000 --> 00:39:11,239
Speaker 5: point is something in the process. And one of the

762
00:39:11,280 --> 00:39:15,759
Speaker 5: things we can do in games is that we can detach.

763
00:39:16,480 --> 00:39:20,800
Speaker 5: Because games are so detached from the rest of the world,

764
00:39:21,120 --> 00:39:23,960
Speaker 5: we can keep pushing around what the rules are. We

765
00:39:24,000 --> 00:39:26,480
Speaker 5: can keep pushing around the scoring system to give us

766
00:39:26,520 --> 00:39:30,600
Speaker 5: the action we want. So many games are so different

767
00:39:30,600 --> 00:39:32,279
Speaker 5: from each other, and you can even see this in one.

768
00:39:32,320 --> 00:39:33,759
Speaker 5: So in climbing, there are lots of things you can

769
00:39:33,800 --> 00:39:36,000
Speaker 5: do in climbing. One way to climb is to climb

770
00:39:36,040 --> 00:39:39,879
Speaker 5: as difficult as much the most difficult routes you can

771
00:39:40,000 --> 00:39:41,719
Speaker 5: Another thing you can do is you can try to

772
00:39:41,800 --> 00:39:43,600
Speaker 5: flirt with risk. Another thing you can do is you

773
00:39:43,600 --> 00:39:46,680
Speaker 5: can climb easy routes in beautiful nature and try to

774
00:39:46,719 --> 00:39:50,800
Speaker 5: climb as many gorgeous areas. There are so many different goals,

775
00:39:51,200 --> 00:39:54,080
Speaker 5: and you can push around and choose the goal that's

776
00:39:54,120 --> 00:39:58,400
Speaker 5: the most satisfying to you. Because games are not locked

777
00:39:58,440 --> 00:40:02,600
Speaker 5: into each other. The way that the anthropologist Johann Huzinga,

778
00:40:02,600 --> 00:40:04,759
Speaker 5: who's this super famous games caller, put it is a

779
00:40:04,800 --> 00:40:08,320
Speaker 5: games occur in a magic circle. The meanings in games

780
00:40:08,360 --> 00:40:11,600
Speaker 5: are isolated from the rest of life. Which this means

781
00:40:11,719 --> 00:40:13,680
Speaker 5: is that I mean, one way he put it is

782
00:40:13,680 --> 00:40:16,359
Speaker 5: that when we're playing against each other, we cancel out

783
00:40:16,360 --> 00:40:21,319
Speaker 5: our different relationships. My wife and I are mostly in

784
00:40:21,400 --> 00:40:26,480
Speaker 5: our daily life supportive, right, loving, and then we play

785
00:40:26,520 --> 00:40:28,640
Speaker 5: a game and we just try to kill each other. Yeah,

786
00:40:28,680 --> 00:40:32,680
Speaker 5: and that's okay, right, that's unrelated. And the fact that

787
00:40:32,800 --> 00:40:35,640
Speaker 5: I want or she want is also unrelated.

788
00:40:35,200 --> 00:40:36,080
Speaker 4: To our larger life.

789
00:40:36,120 --> 00:40:38,399
Speaker 5: That's what makes it okay for me to go all

790
00:40:38,480 --> 00:40:42,840
Speaker 5: out against her in a board game because those points

791
00:40:43,160 --> 00:40:48,239
Speaker 5: are detached. So games have this isolation which lets them

792
00:40:48,280 --> 00:40:50,759
Speaker 5: be radically different, like if I want to change my

793
00:40:50,800 --> 00:40:52,239
Speaker 5: game or play a different game, if we want to

794
00:40:52,280 --> 00:40:57,080
Speaker 5: play I think sometimes my kids and I we play

795
00:40:58,000 --> 00:41:00,720
Speaker 5: super Marius mash and sometimes we play in normal way,

796
00:41:00,800 --> 00:41:05,360
Speaker 5: and sometimes we play for the most spectacular death possible.

797
00:41:05,400 --> 00:41:07,840
Speaker 5: Who cares about who wins, right, and you can just

798
00:41:07,880 --> 00:41:10,680
Speaker 5: do that. Metrics are not like that because metrics are

799
00:41:10,719 --> 00:41:13,919
Speaker 5: attached to real world resources and attached to each other.

800
00:41:14,000 --> 00:41:17,560
Speaker 5: The whole point of metrics is that they're interconnected, right.

801
00:41:17,600 --> 00:41:20,319
Speaker 5: The whole point is that everyone counts in them in

802
00:41:20,400 --> 00:41:24,160
Speaker 5: the same way, so you cannot alter them in a

803
00:41:24,160 --> 00:41:25,680
Speaker 5: way that makes it better for you. I mean, the

804
00:41:25,760 --> 00:41:27,719
Speaker 5: dumbest way to put it is that you can house

805
00:41:27,840 --> 00:41:30,479
Speaker 5: rule poker, but you can't house rule GPA. You can't

806
00:41:30,480 --> 00:41:34,439
Speaker 5: house rule like Twitter likes, because the thing that gave

807
00:41:34,480 --> 00:41:37,520
Speaker 5: them the value in the first place was that we

808
00:41:37,520 --> 00:41:38,839
Speaker 5: were all counting in the same way.

809
00:41:39,040 --> 00:41:43,440
Speaker 1: Yeah, and people can approach the same game differently. So

810
00:41:43,480 --> 00:41:46,439
Speaker 1: you have the idea of striving play versus achievement play,

811
00:41:46,440 --> 00:41:48,720
Speaker 1: how would that play out in something like how someone

812
00:41:48,719 --> 00:41:50,200
Speaker 1: approaches something like a marathon.

813
00:41:50,560 --> 00:41:52,960
Speaker 5: Achievement play is when you play because you value winning,

814
00:41:53,239 --> 00:41:57,400
Speaker 5: and striving play is when you play because you value

815
00:41:57,480 --> 00:42:00,279
Speaker 5: the struggle. And what's interesting is to get that ruggle,

816
00:42:00,320 --> 00:42:02,440
Speaker 5: we actually have to try to win, but winning doesn't

817
00:42:02,680 --> 00:42:06,680
Speaker 5: actually matter, right, And so one of the I think

818
00:42:06,719 --> 00:42:10,200
Speaker 5: one of the interesting things is that we can slide

819
00:42:10,280 --> 00:42:16,279
Speaker 5: the reasons we play all around because the point isn't

820
00:42:16,280 --> 00:42:18,080
Speaker 5: the point, because the goal isn't the point, right, So

821
00:42:18,560 --> 00:42:23,279
Speaker 5: I mean, I can I can shift my reasons for

822
00:42:23,400 --> 00:42:30,920
Speaker 5: playing fluidly during the game, right, Like, Sometimes sometimes I

823
00:42:30,960 --> 00:42:33,840
Speaker 5: can be playing to win and then realize that this

824
00:42:34,000 --> 00:42:37,280
Speaker 5: is not enjoyable, and then I can start goofing off.

825
00:42:37,680 --> 00:42:40,200
Speaker 5: Sometimes I can be I mean, one thing I'll often

826
00:42:40,239 --> 00:42:42,680
Speaker 5: do is I'll be goofing off with my kid on

827
00:42:42,719 --> 00:42:45,160
Speaker 5: a video game and then suddenly realize that my kids

828
00:42:45,160 --> 00:42:46,920
Speaker 5: are not getting old enough that they can beat me.

829
00:42:46,960 --> 00:42:48,520
Speaker 4: I'm like, oh wait, this is an interesting challenge.

830
00:42:48,560 --> 00:42:50,600
Speaker 5: I can go all out now, and suddenly we can

831
00:42:50,680 --> 00:42:53,000
Speaker 5: just try super hard, or we can go in between.

832
00:42:53,040 --> 00:42:55,960
Speaker 5: Sometimes some games ask you to be super focused and

833
00:42:56,000 --> 00:42:59,680
Speaker 5: some games don't, and you can shift between them because

834
00:42:59,719 --> 00:43:04,960
Speaker 5: it does matter, right, Like if I, if I, if I,

835
00:43:04,960 --> 00:43:07,400
Speaker 5: if I try something else, If I change my attitude

836
00:43:07,719 --> 00:43:12,120
Speaker 5: to play Super Mario Smash Goofily and I lose to

837
00:43:12,160 --> 00:43:14,560
Speaker 5: my kid, nothing happens.

838
00:43:14,600 --> 00:43:17,120
Speaker 1: It's good, you want it. If it felt goofy, you won.

839
00:43:17,880 --> 00:43:21,120
Speaker 5: Yeah, So it's one way to put it is that

840
00:43:21,920 --> 00:43:26,680
Speaker 5: in in games, we have a lot of control both

841
00:43:26,800 --> 00:43:29,799
Speaker 5: over the goal that we pursue in the game and

842
00:43:29,880 --> 00:43:33,239
Speaker 5: the purpose that we have for playing it. We can

843
00:43:33,360 --> 00:43:38,000
Speaker 5: maneuver both around. But with metrics it doesn't have to

844
00:43:38,000 --> 00:43:40,200
Speaker 5: be this way. You could try to control the metric

845
00:43:40,440 --> 00:43:42,879
Speaker 5: that you that you cared about, and you could try

846
00:43:42,880 --> 00:43:43,800
Speaker 5: to change your purpose.

847
00:43:44,239 --> 00:43:45,359
Speaker 4: But what they invite us to.

848
00:43:45,320 --> 00:43:48,160
Speaker 5: Do is just to take it as given, to give

849
00:43:48,239 --> 00:43:50,520
Speaker 5: up control, just to be like, well, here's the nearest metric,

850
00:43:50,560 --> 00:43:53,760
Speaker 5: here's the nearest keep perromance enticator. Oh I'm I'm on YouTube.

851
00:43:53,760 --> 00:43:56,000
Speaker 5: I guess I have to care about subscribers. And you

852
00:43:56,040 --> 00:43:58,479
Speaker 5: just take the most pervasive metric and you just take

853
00:43:58,520 --> 00:44:01,520
Speaker 5: it as the goal and the purpose and you don't

854
00:44:01,560 --> 00:44:05,839
Speaker 5: maneuver it. So's they don't force this. You could try

855
00:44:05,840 --> 00:44:07,959
Speaker 5: to have a more playful attitude and a more game

856
00:44:08,080 --> 00:44:11,279
Speaker 5: like attitude towards these large external metrics, and that's one

857
00:44:11,280 --> 00:44:14,080
Speaker 5: of the things I hope people try to do. But

858
00:44:15,000 --> 00:44:20,319
Speaker 5: what they afford, right, what these technologies encourage us to

859
00:44:20,360 --> 00:44:25,200
Speaker 5: do is to not figure out what we want on

860
00:44:25,239 --> 00:44:28,439
Speaker 5: our own and just defer to the external because it's

861
00:44:28,480 --> 00:44:31,640
Speaker 5: so pervasive and steady and available.

862
00:44:32,320 --> 00:44:33,120
Speaker 2: Yeah.

863
00:44:33,280 --> 00:44:38,120
Speaker 1: I think with the marathon, the striving versus achieving, it's

864
00:44:38,480 --> 00:44:41,680
Speaker 1: striving would be Okay, I want to improve my fitness.

865
00:44:41,719 --> 00:44:43,279
Speaker 1: I want to have this interesting experience. I want to

866
00:44:43,280 --> 00:44:45,799
Speaker 1: see what my body can do. Whether you get first

867
00:44:45,800 --> 00:44:49,080
Speaker 1: place or last place, you're going to get that from

868
00:44:49,080 --> 00:44:53,279
Speaker 1: a marathon, whereas achievement would be I must hit X

869
00:44:53,360 --> 00:44:57,839
Speaker 1: time and run at why pace all twenty six miles,

870
00:44:57,920 --> 00:45:00,640
Speaker 1: and there can be a clear failure to that. And

871
00:45:00,680 --> 00:45:02,400
Speaker 1: so it's just this different frame of mind, and I

872
00:45:02,400 --> 00:45:05,600
Speaker 1: think that sometimes the achievement can maybe make people a

873
00:45:05,600 --> 00:45:08,040
Speaker 1: little more nuts in cases. I mean, you could get

874
00:45:08,080 --> 00:45:10,759
Speaker 1: this big internal reward because oh I finished in under

875
00:45:10,800 --> 00:45:15,800
Speaker 1: three hours, but it definitely changes the nature of that marathon.

876
00:45:16,160 --> 00:45:18,680
Speaker 5: I think it's actually a little more complicated to that

877
00:45:18,760 --> 00:45:21,120
Speaker 5: because so achievement players what they care about is winning.

878
00:45:21,160 --> 00:45:23,400
Speaker 5: Striving players what they care about is an experience of struggle.

879
00:45:23,560 --> 00:45:25,920
Speaker 5: But for some striving players, the experience of struggle they

880
00:45:25,960 --> 00:45:29,319
Speaker 5: want they only get when they're being hyper competitive. So

881
00:45:29,400 --> 00:45:32,120
Speaker 5: both striving players and achievement players can be super competitive.

882
00:45:32,520 --> 00:45:35,000
Speaker 5: Like some people, the joy and the pleasure they get

883
00:45:35,080 --> 00:45:37,840
Speaker 5: comes from really trying hard to win. I think the

884
00:45:37,920 --> 00:45:41,640
Speaker 5: big difference is the kind of reflective control they have

885
00:45:42,480 --> 00:45:45,200
Speaker 5: over the game they're playing. So if you're an achievement

886
00:45:45,200 --> 00:45:47,080
Speaker 5: player and you're just trying to win, then the value

887
00:45:47,080 --> 00:45:48,600
Speaker 5: of the game for you as winning. You're just going

888
00:45:48,680 --> 00:45:50,920
Speaker 5: to try to win. If you're a striving player and

889
00:45:50,960 --> 00:45:54,120
Speaker 5: you value something else, like I value a thrill, right,

890
00:45:54,760 --> 00:45:57,400
Speaker 5: that means that I can be super competitive in a game.

891
00:45:57,960 --> 00:46:00,759
Speaker 5: And if I step back and I'm like, was that thrilling? No,

892
00:46:01,840 --> 00:46:03,960
Speaker 5: then I can change games. I can go to a

893
00:46:04,000 --> 00:46:07,239
Speaker 5: different game. So here's something simple. I play a lot

894
00:46:07,239 --> 00:46:08,560
Speaker 5: of games to experience meditation.

895
00:46:09,239 --> 00:46:09,680
Speaker 4: This is why.

896
00:46:10,080 --> 00:46:12,759
Speaker 5: And I try some games, I get it for a bit.

897
00:46:12,840 --> 00:46:15,080
Speaker 5: So I hiked for a while for meditation. I realized

898
00:46:15,080 --> 00:46:18,520
Speaker 5: I would get moments of it. And then I tried

899
00:46:18,600 --> 00:46:21,800
Speaker 5: hiking more intensely, like I'm gonna do more mileage.

900
00:46:22,480 --> 00:46:22,800
Speaker 4: Didn't.

901
00:46:22,960 --> 00:46:25,520
Speaker 5: I actually got less meditation. And then I tried fly fishing.

902
00:46:25,680 --> 00:46:28,080
Speaker 5: It turns out that fly fishing is for me like

903
00:46:28,160 --> 00:46:31,680
Speaker 5: a shortcut to pure zendless meditation. And one of the

904
00:46:31,680 --> 00:46:34,600
Speaker 5: interesting things is if I fly fish kind of differently

905
00:46:34,719 --> 00:46:37,440
Speaker 5: and like not really try that hard, I don't get

906
00:46:37,120 --> 00:46:40,880
Speaker 5: that meditation effect. If I really try hard to catch

907
00:46:40,920 --> 00:46:43,280
Speaker 5: a big fish. Then I have to be super focused

908
00:46:43,280 --> 00:46:47,319
Speaker 5: on the river. And when I'm super focused visually on

909
00:46:47,360 --> 00:46:50,880
Speaker 5: the river and on noticing the bugs because you have

910
00:46:50,960 --> 00:46:53,320
Speaker 5: to do that to catch the smart fish and fly fishing,

911
00:46:54,080 --> 00:46:57,560
Speaker 5: then I get the pure hit of just this pure

912
00:46:58,160 --> 00:46:59,920
Speaker 5: meditative trans state.

913
00:47:00,400 --> 00:47:02,120
Speaker 4: And so it does it make sense?

914
00:47:02,960 --> 00:47:07,680
Speaker 5: The thing that striving play gives you is not an

915
00:47:07,800 --> 00:47:11,239
Speaker 5: uncompetitive attitude. It's that you can choose what game and

916
00:47:11,280 --> 00:47:14,560
Speaker 5: the degree of competitiveness, competitiveness and intensity you have in

917
00:47:14,600 --> 00:47:17,319
Speaker 5: the game in order to hit this larger thing, which

918
00:47:17,360 --> 00:47:21,600
Speaker 5: is what you actually care about. For me, actually, it's

919
00:47:21,640 --> 00:47:25,240
Speaker 5: super interesting. When I am too intense about rock climbing,

920
00:47:25,280 --> 00:47:27,359
Speaker 5: I lose the joys I have in it. But when

921
00:47:27,360 --> 00:47:31,040
Speaker 5: I'm super intense about fly fishing, that's when I get

922
00:47:31,800 --> 00:47:38,040
Speaker 5: the gateway to this mental magic state that is just

923
00:47:38,200 --> 00:47:42,360
Speaker 5: pure mental flow joined with a river something magic.

924
00:47:42,560 --> 00:47:42,799
Speaker 4: Yeah.

925
00:47:42,800 --> 00:47:46,040
Speaker 1: Well, I think it's interesting too because a lot of

926
00:47:46,080 --> 00:47:50,080
Speaker 1: these games can have this element of quantification, and if

927
00:47:50,120 --> 00:47:53,960
Speaker 1: you only focus on that, that could lead you a

928
00:47:54,000 --> 00:47:55,120
Speaker 1: stray in a lot of ways. I think you have

929
00:47:55,200 --> 00:47:58,080
Speaker 1: the example of rock climbing. How you just told this out.

930
00:47:58,440 --> 00:48:00,479
Speaker 1: You know, if you approach it a little more chill.

931
00:48:00,520 --> 00:48:02,080
Speaker 1: You get more from that. But for a while you

932
00:48:02,160 --> 00:48:04,439
Speaker 1: were really focused on I need to hit the next

933
00:48:04,560 --> 00:48:07,520
Speaker 1: numbered route because the boulders are scaled, the climbs are scaled,

934
00:48:08,080 --> 00:48:12,440
Speaker 1: and so I think it's building that awareness though of

935
00:48:12,520 --> 00:48:15,200
Speaker 1: in what way do I approach this game to get

936
00:48:15,200 --> 00:48:18,440
Speaker 1: this goal I'm after, whatever it might be. It's like,

937
00:48:18,880 --> 00:48:21,080
Speaker 1: it's kind of messy and it's hard to do. It

938
00:48:21,120 --> 00:48:22,799
Speaker 1: takes a little more work, but once you find that,

939
00:48:22,920 --> 00:48:25,880
Speaker 1: it becomes magic. Whereas if you always just kind of

940
00:48:25,880 --> 00:48:29,880
Speaker 1: offload to here's the marker of my success based on

941
00:48:29,920 --> 00:48:33,320
Speaker 1: this scaling system, that could maybe lead someone astray.

942
00:48:33,719 --> 00:48:35,120
Speaker 4: Yeah, it's super complicated and messy.

943
00:48:35,160 --> 00:48:37,120
Speaker 5: One of the interesting things about rock climbing for me

944
00:48:37,480 --> 00:48:39,600
Speaker 5: was the difficulty scale. Just being super focused on the

945
00:48:39,600 --> 00:48:44,120
Speaker 5: difficulty scale was amazing for me for about five years. Yeah,

946
00:48:44,239 --> 00:48:47,480
Speaker 5: So I think when I was not very physically apt,

947
00:48:48,920 --> 00:48:52,319
Speaker 5: if I didn't try to, if I just kind of

948
00:48:52,360 --> 00:48:56,080
Speaker 5: meandered around and didn't care much about difficulty, I didn't

949
00:48:56,080 --> 00:49:00,880
Speaker 5: have to focus on my body and the goal of

950
00:49:01,719 --> 00:49:06,759
Speaker 5: climbing harder climbs, because it made me focus on my

951
00:49:06,840 --> 00:49:09,880
Speaker 5: body and pay more attention to my body. Actually, unlocked

952
00:49:09,920 --> 00:49:12,480
Speaker 5: a lot of like pleasure and movement and joy, and

953
00:49:12,560 --> 00:49:15,160
Speaker 5: so that scoring system was actually super useful for a good.

954
00:49:15,000 --> 00:49:15,640
Speaker 4: Amount of time.

955
00:49:15,880 --> 00:49:17,640
Speaker 5: And then at some point I just hit like my

956
00:49:17,680 --> 00:49:21,879
Speaker 5: physical peak, like I'm not that athletic, and I now

957
00:49:21,880 --> 00:49:22,359
Speaker 5: am a parent.

958
00:49:22,400 --> 00:49:23,560
Speaker 4: I just don't have that much time.

959
00:49:23,760 --> 00:49:26,719
Speaker 5: And then once I like hit it to blow, the

960
00:49:26,719 --> 00:49:30,239
Speaker 5: difficulty scale wasn't working for me anymore, and I got

961
00:49:30,239 --> 00:49:32,320
Speaker 5: pretty unhappy, and then I had to change. So now

962
00:49:32,560 --> 00:49:35,759
Speaker 5: I actually pursue my own weird private vision of like

963
00:49:36,880 --> 00:49:39,000
Speaker 5: doing climes as elegantly as I can.

964
00:49:38,840 --> 00:49:40,320
Speaker 4: Which is not very portable.

965
00:49:40,600 --> 00:49:43,400
Speaker 5: But also I think the thing I have to admit

966
00:49:43,719 --> 00:49:48,360
Speaker 5: is I couldn't have gotten there without the scoring engaging

967
00:49:48,400 --> 00:49:51,160
Speaker 5: in the scoring system as given for a good amount

968
00:49:51,200 --> 00:49:53,360
Speaker 5: of time. So I think, like what this teaching to

969
00:49:53,360 --> 00:49:55,480
Speaker 5: me is not that like, scoring systems are bad, metrics

970
00:49:55,480 --> 00:49:59,759
Speaker 5: are bad, but that they are sometimes useful things that

971
00:49:59,800 --> 00:50:03,319
Speaker 5: we can manage carefully and can be incredibly powerful when

972
00:50:03,320 --> 00:50:06,399
Speaker 5: we manage them carefully. And then I mean, I think

973
00:50:06,400 --> 00:50:09,560
Speaker 5: there's so many people who am using the fitbit is

974
00:50:09,760 --> 00:50:12,600
Speaker 5: a great motivator and gets them exercising the beginning, and

975
00:50:12,640 --> 00:50:15,879
Speaker 5: then you get people who are like well, I can't rock,

976
00:50:16,600 --> 00:50:17,640
Speaker 5: even though I love it.

977
00:50:18,239 --> 00:50:21,200
Speaker 1: I think that's as you were saying that, I was

978
00:50:21,239 --> 00:50:24,560
Speaker 1: thinking about how people approach their fitness trackers. It's I

979
00:50:24,600 --> 00:50:26,800
Speaker 1: think it's for a person who really doesn't have a

980
00:50:26,840 --> 00:50:30,719
Speaker 1: lot of awareness around their behaviors, throwing that thing on

981
00:50:30,760 --> 00:50:34,160
Speaker 1: your wrist for a few days and you go, oh,

982
00:50:34,440 --> 00:50:37,040
Speaker 1: I only walk three thousand steps. I had no idea,

983
00:50:37,600 --> 00:50:40,920
Speaker 1: And so that can incentivize people that start moving, and

984
00:50:40,960 --> 00:50:44,160
Speaker 1: that does a lot of good things. What I think happens,

985
00:50:44,239 --> 00:50:46,680
Speaker 1: especially as people sort of get along the path in

986
00:50:46,960 --> 00:50:48,840
Speaker 1: you know, building health and fitness, all of a sudden

987
00:50:48,920 --> 00:50:52,800
Speaker 1: that becomes the clear marker of success of whether or

988
00:50:52,840 --> 00:50:56,200
Speaker 1: not I was fit today, and alters their behavior in

989
00:50:56,280 --> 00:50:59,600
Speaker 1: such a way that could maybe even go against these

990
00:50:59,600 --> 00:51:01,560
Speaker 1: bigger roles of building fitness.

991
00:51:01,600 --> 00:51:03,720
Speaker 2: Your friend, the rock climber example.

992
00:51:03,480 --> 00:51:05,960
Speaker 1: Is you know, you could argue, well, if you got

993
00:51:06,040 --> 00:51:07,840
Speaker 1: enough steps and then you did this sort of strength

994
00:51:07,840 --> 00:51:10,799
Speaker 1: thing and this movement thing, like that's holistically a better

995
00:51:10,840 --> 00:51:13,240
Speaker 1: approach for your health than just getting the ten thousand

996
00:51:13,239 --> 00:51:16,640
Speaker 1: steps without all those other things thrown in. I think

997
00:51:16,680 --> 00:51:20,480
Speaker 1: you see this in sleep scores as well. People get

998
00:51:20,520 --> 00:51:23,360
Speaker 1: so fixated on that sleep score. And what cracks me

999
00:51:23,440 --> 00:51:28,880
Speaker 1: up is when the numbers, say, goes down and you

1000
00:51:28,880 --> 00:51:31,440
Speaker 1: almost see people start to panic over the number going down.

1001
00:51:31,480 --> 00:51:33,160
Speaker 1: Oh my god, I had a meeting today. This meeting

1002
00:51:33,200 --> 00:51:36,080
Speaker 1: is going to be a disaster because my sleep score

1003
00:51:36,160 --> 00:51:38,520
Speaker 1: was a sixty instead of an eighty. Whereas if you

1004
00:51:38,520 --> 00:51:41,680
Speaker 1: didn't have that sleep score on you might have woken

1005
00:51:41,760 --> 00:51:43,640
Speaker 1: up and just felt fine, like, all right, I got

1006
00:51:43,640 --> 00:51:44,120
Speaker 1: this meeting.

1007
00:51:44,160 --> 00:51:45,640
Speaker 2: I'm psyched for this meeting.

1008
00:51:46,480 --> 00:51:51,480
Speaker 4: Wait, I have a really devastating factoid.

1009
00:51:52,200 --> 00:51:55,239
Speaker 5: Okay, wait, I have two devastating pactoids for you that

1010
00:51:55,280 --> 00:51:56,320
Speaker 5: didn't make it into the book.

1011
00:51:56,719 --> 00:51:58,320
Speaker 1: We love devastating factoids.

1012
00:51:58,520 --> 00:52:03,440
Speaker 5: Send them the comment about how it's super useful if

1013
00:52:03,440 --> 00:52:07,120
Speaker 5: you have no sensibility, like when I A lot of

1014
00:52:07,120 --> 00:52:10,160
Speaker 5: these scores are very very very rough proxies totally and

1015
00:52:10,239 --> 00:52:13,279
Speaker 5: if you have no sensibility in the area. I also

1016
00:52:13,360 --> 00:52:16,520
Speaker 5: had the same thing with nutrition. Actually, when I started

1017
00:52:16,880 --> 00:52:21,040
Speaker 5: nutrition tracking with no awareness, it was actually awesome.

1018
00:52:21,160 --> 00:52:22,040
Speaker 4: Yes, I had no.

1019
00:52:22,000 --> 00:52:25,040
Speaker 5: Idea, I had no idea how many carbs were in things,

1020
00:52:25,360 --> 00:52:28,720
Speaker 5: and it took me a while to realize I needed

1021
00:52:28,719 --> 00:52:31,520
Speaker 5: that information to get through my thick skull that a

1022
00:52:32,040 --> 00:52:35,759
Speaker 5: massively carbon cheese heavy thing made me sleepy and then

1023
00:52:35,840 --> 00:52:38,560
Speaker 5: tired the whole next day. I just didn't have enough

1024
00:52:38,600 --> 00:52:41,200
Speaker 5: sensitivity to my body to do that. And then at

1025
00:52:41,239 --> 00:52:43,920
Speaker 5: some point, once I learned that sensitivity, I could depart

1026
00:52:43,960 --> 00:52:48,520
Speaker 5: from the score and pursue like a more like delicate

1027
00:52:48,560 --> 00:52:50,640
Speaker 5: sense of what things were doing well in my body

1028
00:52:50,680 --> 00:52:52,880
Speaker 5: that came apart from those simple mentions.

1029
00:52:53,080 --> 00:52:55,800
Speaker 2: That was my experience entirely.

1030
00:52:56,080 --> 00:52:58,920
Speaker 1: The first time I ever measured my food, and I

1031
00:52:59,000 --> 00:53:01,319
Speaker 1: took what I thought was a serving of peanut butter

1032
00:53:01,440 --> 00:53:03,640
Speaker 1: and learned that it was about four So what I

1033
00:53:03,640 --> 00:53:06,840
Speaker 1: thought was about two hundred talories was more like eight hundred.

1034
00:53:06,920 --> 00:53:09,719
Speaker 1: It was like, oh, well, that's a useful piece of

1035
00:53:09,800 --> 00:53:11,200
Speaker 1: information moving forward.

1036
00:53:11,560 --> 00:53:13,640
Speaker 5: What's interesting is that these things can help tune us in,

1037
00:53:14,040 --> 00:53:17,680
Speaker 5: but the worries in the long term they Okay.

1038
00:53:17,840 --> 00:53:21,319
Speaker 4: When I was researching this stuff, the most.

1039
00:53:21,400 --> 00:53:23,840
Speaker 5: Brutal example I found, which is not in the book

1040
00:53:23,840 --> 00:53:28,640
Speaker 5: because my editor thought it was too gross, is pickup

1041
00:53:28,680 --> 00:53:30,440
Speaker 5: artist culture interesting.

1042
00:53:31,440 --> 00:53:33,799
Speaker 4: So pick up artists, for.

1043
00:53:33,800 --> 00:53:36,280
Speaker 5: Those of you who don't know, are people who compete

1044
00:53:36,719 --> 00:53:41,480
Speaker 5: for sexual success and it's literally called scoring, right, Okay, Yeah,

1045
00:53:41,560 --> 00:53:45,000
Speaker 5: And there are a bunch of sociologists and anthropologists that

1046
00:53:45,040 --> 00:53:47,240
Speaker 5: have studied them. And I read a bunch of these studies,

1047
00:53:47,280 --> 00:53:49,840
Speaker 5: and what I found blew my mind because it turns

1048
00:53:49,880 --> 00:53:52,759
Speaker 5: out so pick up artists tend to compete for things.

1049
00:53:52,800 --> 00:53:55,760
Speaker 5: I think you know what they compete for. Phone numbers,

1050
00:53:56,360 --> 00:54:00,040
Speaker 5: number of sexual accident, evening speed for meeting someone to

1051
00:54:00,120 --> 00:54:03,480
Speaker 5: a sexual act with them right, number of sec average

1052
00:54:03,560 --> 00:54:07,120
Speaker 5: number of new hookups per night out in a month,

1053
00:54:07,160 --> 00:54:11,880
Speaker 5: stuff like that. Here's what they don't compete for. This

1054
00:54:11,920 --> 00:54:14,279
Speaker 5: should be obvious, but I think we forget it. They

1055
00:54:14,280 --> 00:54:17,600
Speaker 5: don't compete for quality of relationships. They don't even compete

1056
00:54:17,600 --> 00:54:22,120
Speaker 5: for pleasure. One of there's a sociologist who notes that

1057
00:54:22,160 --> 00:54:25,000
Speaker 5: a mantra throughout the pickup artist culture is you have

1058
00:54:25,040 --> 00:54:27,840
Speaker 5: to give up on happiness or enjoying them. That'll just

1059
00:54:27,880 --> 00:54:32,640
Speaker 5: get in the way of making more numbers. I see you, right,

1060
00:54:34,520 --> 00:54:39,120
Speaker 5: but you can see why. Here's why pleasure isn't accountable.

1061
00:54:40,200 --> 00:54:43,120
Speaker 5: If I say I had more pleasure and you say

1062
00:54:43,120 --> 00:54:45,960
Speaker 5: you had more pleasure, there's no way for us to compare, right,

1063
00:54:46,080 --> 00:54:51,480
Speaker 5: But we can compare who got to the sexual act faster, right,

1064
00:54:51,560 --> 00:54:54,359
Speaker 5: because that's a public, measurable.

1065
00:54:54,320 --> 00:54:57,040
Speaker 1: Public in this case being you and I are on

1066
00:54:57,080 --> 00:55:02,360
Speaker 1: the pickup artist's Reddit thread. You say, hey, thirty hookups

1067
00:55:02,360 --> 00:55:04,600
Speaker 1: in thirty days, and I go, oh, well, I just

1068
00:55:04,600 --> 00:55:07,080
Speaker 1: had twenty eight. You clearly are the better pickup artist

1069
00:55:07,160 --> 00:55:11,160
Speaker 1: if we're only measuring it by that deal done.

1070
00:55:11,760 --> 00:55:16,000
Speaker 5: I mean, I thought when I started reading what pickup

1071
00:55:16,040 --> 00:55:19,400
Speaker 5: Artists the dude turnout that pickup artists were evil and manipulative.

1072
00:55:19,840 --> 00:55:23,120
Speaker 4: But at least we're enjoying themselves. But it's so much

1073
00:55:23,160 --> 00:55:26,640
Speaker 4: worse than that. Yeah, it's that.

1074
00:55:29,680 --> 00:55:34,160
Speaker 5: So many seem to have burned out any sense of

1075
00:55:34,200 --> 00:55:36,359
Speaker 5: pleasure or joy or any of the reasons you might

1076
00:55:36,400 --> 00:55:39,000
Speaker 5: went in a relationship and created this holid out shell

1077
00:55:39,280 --> 00:55:42,520
Speaker 5: of just what's public accountable. And I kind of think

1078
00:55:42,800 --> 00:55:45,240
Speaker 5: that we have all become some kind of pickup artist

1079
00:55:45,719 --> 00:55:47,120
Speaker 5: in some era of our life.

1080
00:55:47,360 --> 00:55:48,799
Speaker 1: We're going to take a quick break, and then when

1081
00:55:48,800 --> 00:55:50,560
Speaker 1: we get back, we're going to talk about how tease

1082
00:55:50,600 --> 00:55:54,400
Speaker 1: thoughts on numbers maybe leading you to get worse healthcare

1083
00:55:54,480 --> 00:55:55,160
Speaker 1: from your doctor.

1084
00:56:04,280 --> 00:56:07,560
Speaker 2: What's the most common accounts.

1085
00:56:07,120 --> 00:56:09,480
Speaker 1: You've heard from people who are familiar with your work, Like,

1086
00:56:09,480 --> 00:56:11,920
Speaker 1: what are the five things you hear people say that

1087
00:56:12,000 --> 00:56:14,960
Speaker 1: You're like, oh, you're the pick up artist of this domain.

1088
00:56:15,760 --> 00:56:19,279
Speaker 5: It's funny, because I mean everyone the ones that you're

1089
00:56:19,280 --> 00:56:23,840
Speaker 5: talking about social media and nutrition are the most common

1090
00:56:23,840 --> 00:56:26,280
Speaker 5: ones I hear. But what I often hear are really

1091
00:56:26,320 --> 00:56:29,880
Speaker 5: technical in arcane stories about someone who went The problem

1092
00:56:29,920 --> 00:56:31,680
Speaker 5: is that a lot of the metrics are very specific.

1093
00:56:31,719 --> 00:56:33,560
Speaker 5: So what I hear often is, oh, I went into

1094
00:56:33,640 --> 00:56:36,240
Speaker 5: education policy because I cared about people, and then I realized,

1095
00:56:36,320 --> 00:56:38,600
Speaker 5: for the last ten years, I've been chasing this outcome

1096
00:56:38,880 --> 00:56:44,040
Speaker 5: that just has become completely disconnected from the thing we

1097
00:56:44,480 --> 00:56:45,040
Speaker 5: care about.

1098
00:56:45,200 --> 00:56:49,240
Speaker 4: Yeah, I hear this. It's funny.

1099
00:56:49,400 --> 00:56:51,680
Speaker 5: Every time I talk to somebody and I tell them

1100
00:56:51,719 --> 00:56:55,040
Speaker 5: about this, they're like, oh my god, we have the

1101
00:56:55,080 --> 00:57:01,560
Speaker 5: worst one in our profession. The what doctors complain tell

1102
00:57:01,600 --> 00:57:07,200
Speaker 5: me about is the big measure for them is basically

1103
00:57:08,040 --> 00:57:11,680
Speaker 5: number of patients scene and moving people through quickly. And

1104
00:57:11,719 --> 00:57:14,120
Speaker 5: I think you can quickly see that that's very easy

1105
00:57:14,120 --> 00:57:16,960
Speaker 5: to measure and runs against all kinds of human interaction

1106
00:57:17,640 --> 00:57:19,160
Speaker 5: and kinds of care.

1107
00:57:20,000 --> 00:57:21,000
Speaker 4: I know so many.

1108
00:57:20,840 --> 00:57:25,160
Speaker 5: Doctors who said, like, the burden of the measure, of

1109
00:57:25,200 --> 00:57:28,680
Speaker 5: the speed measure has just like obliterated everything they wanted

1110
00:57:29,520 --> 00:57:32,880
Speaker 5: out of their medical career, which is to actually connect

1111
00:57:32,880 --> 00:57:34,200
Speaker 5: to human beings.

1112
00:57:35,480 --> 00:57:37,480
Speaker 1: And make them better I'll give you an example from

1113
00:57:37,520 --> 00:57:39,760
Speaker 1: my life. When I was working at Men's Health Magazine.

1114
00:57:40,360 --> 00:57:44,640
Speaker 1: I was helping run the website and we would do

1115
00:57:45,440 --> 00:57:49,320
Speaker 1: five stories a day. They were all pretty deeply reported,

1116
00:57:49,400 --> 00:57:52,440
Speaker 1: We talked to multiple sources across the board, blah blah blah.

1117
00:57:52,880 --> 00:57:55,200
Speaker 1: We had a new editor and chief come in, who goes.

1118
00:57:55,920 --> 00:57:57,800
Speaker 1: The way that you get more page views is you

1119
00:57:57,840 --> 00:58:02,920
Speaker 1: have to publish more stories. So five that's not going

1120
00:58:02,920 --> 00:58:06,760
Speaker 1: to cut it. You need thirty. Well, what happens. You

1121
00:58:06,840 --> 00:58:09,040
Speaker 1: have to stop calling sources. You have to just start

1122
00:58:09,680 --> 00:58:12,760
Speaker 1: making shit up that'll work for a story. Oftentimes we

1123
00:58:12,800 --> 00:58:15,840
Speaker 1: would people would start finding videos online of like a

1124
00:58:15,880 --> 00:58:18,680
Speaker 1: fight and publishing that because we knew it would do

1125
00:58:18,760 --> 00:58:20,880
Speaker 1: well on page counts.

1126
00:58:21,480 --> 00:58:23,080
Speaker 2: But what is the goal of Men's Health Magazine.

1127
00:58:23,080 --> 00:58:27,000
Speaker 1: It's to inform readers about important health information they can

1128
00:58:27,080 --> 00:58:29,320
Speaker 1: use in their life and improve their life. So once

1129
00:58:29,360 --> 00:58:32,440
Speaker 1: we started pushing that to thirty, that went out the window.

1130
00:58:33,240 --> 00:58:36,480
Speaker 1: The site was just a mess and was no longer useful.

1131
00:58:36,600 --> 00:58:40,760
Speaker 1: Now the page counts, yes, they definitely went up, but

1132
00:58:40,880 --> 00:58:43,000
Speaker 1: in the long term, what was interesting is that it

1133
00:58:43,080 --> 00:58:46,120
Speaker 1: really hollowed out that magazine and people stopped coming.

1134
00:58:46,160 --> 00:58:46,760
Speaker 2: In the long run.

1135
00:58:46,800 --> 00:58:48,880
Speaker 1: So it was just this like got fixated on the target,

1136
00:58:49,360 --> 00:58:52,400
Speaker 1: lost sight of what this the purpose of this website

1137
00:58:52,480 --> 00:58:54,280
Speaker 1: really was for, and then in the long term you

1138
00:58:54,400 --> 00:58:56,640
Speaker 1: just saw this crash.

1139
00:58:56,800 --> 00:58:59,680
Speaker 5: This is a lesson from James Scott and seeing like

1140
00:58:59,720 --> 00:59:01,360
Speaker 5: at one of the inspirations to this book.

1141
00:59:01,400 --> 00:59:04,560
Speaker 4: Have you read that book. You should absolutely read that book.

1142
00:59:04,560 --> 00:59:07,480
Speaker 5: It's about how large scale states and he defined states

1143
00:59:07,520 --> 00:59:09,840
Speaker 5: at any kind of large bureaucratic institution, so it mean

1144
00:59:09,960 --> 00:59:11,840
Speaker 5: governments and corporations.

1145
00:59:12,600 --> 00:59:16,480
Speaker 4: He thinks that they can only see the parts of

1146
00:59:16,480 --> 00:59:17,680
Speaker 4: the world they're easily.

1147
00:59:17,360 --> 00:59:20,000
Speaker 5: Accountable in a bureaucratic way everything we've been talking about,

1148
00:59:20,240 --> 00:59:22,480
Speaker 5: and so everything else is invisible to them. What's seeable

1149
00:59:22,600 --> 00:59:24,880
Speaker 5: is what's legible to the state. And then he thinks

1150
00:59:24,880 --> 00:59:27,760
Speaker 5: that states have a motive to remake the world to

1151
00:59:27,800 --> 00:59:30,880
Speaker 5: make it more legible to them, and he has all

1152
00:59:30,960 --> 00:59:34,600
Speaker 5: these stories about so he opens with the story of

1153
00:59:35,720 --> 00:59:40,640
Speaker 5: the German managed agriculture industry starting to manage the German

1154
00:59:40,720 --> 00:59:43,520
Speaker 5: forests to optimize for a plant yield, and it turns

1155
00:59:43,520 --> 00:59:46,160
Speaker 5: out that it's much easier to track what's going on

1156
00:59:46,280 --> 00:59:48,280
Speaker 5: and to measure your interventions if.

1157
00:59:48,120 --> 00:59:49,480
Speaker 4: You reduce biodiversity.

1158
00:59:49,560 --> 00:59:52,320
Speaker 5: So they took the German They replanted the forest from

1159
00:59:52,360 --> 00:59:54,640
Speaker 5: like about one hundred different trees to two different trees,

1160
00:59:54,680 --> 00:59:57,120
Speaker 5: and they also started panecting them and even rows instead

1161
00:59:57,120 --> 00:59:59,520
Speaker 5: of letting them grow with a tangle of underbrush. And

1162
00:59:59,560 --> 01:00:04,320
Speaker 5: what happened was they successfully optimized for plank yield for

1163
01:00:04,400 --> 01:00:09,440
Speaker 5: about sixty or seventy years, and then the ecosystem collapsed

1164
01:00:10,400 --> 01:00:15,280
Speaker 5: because so many important long term things weren't being tracked.

1165
01:00:15,880 --> 01:00:18,040
Speaker 5: And when you optimize for one thing that you can

1166
01:00:18,120 --> 01:00:21,320
Speaker 5: clearly see, you kind of decimate everything else because there's

1167
01:00:21,360 --> 01:00:25,919
Speaker 5: always trade offs behind everything. And I think the thing

1168
01:00:25,960 --> 01:00:28,600
Speaker 5: you're talking about, it's funny, it sounds exactly like the

1169
01:00:28,640 --> 01:00:31,320
Speaker 5: German forestry story, right, you had a small thing. It

1170
01:00:31,360 --> 01:00:32,720
Speaker 5: was really Once you have a small thing that you

1171
01:00:32,880 --> 01:00:35,040
Speaker 5: trackage really easy to optimize for it. And if you're

1172
01:00:35,040 --> 01:00:37,760
Speaker 5: optimizing just for that thing and cutting out all the

1173
01:00:37,840 --> 01:00:41,560
Speaker 5: kind of longer term, more sustainable but more subtle qualities,

1174
01:00:42,200 --> 01:00:45,520
Speaker 5: then you're gonna have a crash. Yeah, and I'm worried

1175
01:00:45,560 --> 01:00:46,400
Speaker 5: that this is the world.

1176
01:00:47,360 --> 01:00:49,320
Speaker 1: This made me think a lot about I don't know

1177
01:00:49,360 --> 01:00:52,160
Speaker 1: if you've been paying attention, but there's this big push

1178
01:00:52,200 --> 01:00:53,640
Speaker 1: to longevity culture.

1179
01:00:53,920 --> 01:00:54,760
Speaker 2: And living longer.

1180
01:00:54,800 --> 01:00:57,600
Speaker 1: How what does that make you think about loengevity culture?

1181
01:00:59,160 --> 01:01:01,240
Speaker 4: Same, exactly the same thing.

1182
01:01:01,400 --> 01:01:04,400
Speaker 5: But we've already, I mean, the medical world has already

1183
01:01:04,680 --> 01:01:07,880
Speaker 5: been through this in a part because I mean so

1184
01:01:07,960 --> 01:01:10,920
Speaker 5: I my department is full of bioethicists and medical ethicists,

1185
01:01:11,040 --> 01:01:12,720
Speaker 5: and this is a huge amount of the push. So

1186
01:01:12,760 --> 01:01:14,880
Speaker 5: in the medical world it was for a long time

1187
01:01:16,200 --> 01:01:17,880
Speaker 5: it was assumed that what you're trying to do is

1188
01:01:17,920 --> 01:01:20,640
Speaker 5: up people's longevity, and you want to do any intervention

1189
01:01:20,800 --> 01:01:23,760
Speaker 5: possible to increase the longevity. And because quality of life

1190
01:01:23,800 --> 01:01:26,440
Speaker 5: is hard to track, you just do all these interventions

1191
01:01:26,480 --> 01:01:28,400
Speaker 5: and what you get is, I think the thing that

1192
01:01:28,440 --> 01:01:33,800
Speaker 5: we're aware of, which is this brutal attitude, especially towards

1193
01:01:34,000 --> 01:01:38,160
Speaker 5: end of life care, that tends to push people, that

1194
01:01:38,240 --> 01:01:39,040
Speaker 5: tends to push for.

1195
01:01:39,080 --> 01:01:40,880
Speaker 4: Longer life no matter what.

1196
01:01:41,120 --> 01:01:43,160
Speaker 5: And now we're seeing the pushback right A lot of

1197
01:01:43,160 --> 01:01:46,280
Speaker 5: what we have now about a lot of us have

1198
01:01:46,440 --> 01:01:51,160
Speaker 5: you know, a lot of us have do not resuscitates,

1199
01:01:51,200 --> 01:01:53,400
Speaker 5: a lot of us have a lot of advanced directives.

1200
01:01:53,760 --> 01:01:58,800
Speaker 5: Because the medical establishment took decades to come off of

1201
01:01:58,960 --> 01:02:02,919
Speaker 5: just being obsessed with longevity at any price, towards being

1202
01:02:02,960 --> 01:02:06,200
Speaker 5: able to be open to people making decisions about quality

1203
01:02:06,200 --> 01:02:08,680
Speaker 5: of life versus longevity, And now it feels like a

1204
01:02:08,680 --> 01:02:12,320
Speaker 5: lot of people are just doing the same. I mean,

1205
01:02:12,800 --> 01:02:16,200
Speaker 5: George Carlin back in the day, he had one of

1206
01:02:16,200 --> 01:02:19,120
Speaker 5: his old jokes is, yeah, people say you live longer

1207
01:02:19,360 --> 01:02:21,160
Speaker 5: if you run more, but you spend all those years

1208
01:02:21,240 --> 01:02:24,280
Speaker 5: running and right, like, I.

1209
01:02:24,200 --> 01:02:28,880
Speaker 4: Mean it makes you want a good life, yeah, too.

1210
01:02:28,640 --> 01:02:32,320
Speaker 5: Short, not great, a life where you've made the number

1211
01:02:32,320 --> 01:02:35,000
Speaker 5: of years go up by forcing yourself to do a

1212
01:02:35,040 --> 01:02:39,120
Speaker 5: bunch of things you hate for your entire life, right,

1213
01:02:40,280 --> 01:02:42,400
Speaker 5: I mean, one of the things I was thinking about was.

1214
01:02:45,600 --> 01:02:46,640
Speaker 4: In public policy.

1215
01:02:46,760 --> 01:02:50,480
Speaker 5: In health policy, we often have these fights between what

1216
01:02:50,600 --> 01:02:53,240
Speaker 5: makes people live longer or use their cardiac arrests and

1217
01:02:53,360 --> 01:02:55,680
Speaker 5: things that make people happy. So I'm just thinking about

1218
01:02:55,680 --> 01:02:59,880
Speaker 5: like incredibly rich foods, right like, bree, Like, it's really

1219
01:03:00,120 --> 01:03:04,320
Speaker 5: easy to do a social measure about lower bre rate,

1220
01:03:04,520 --> 01:03:08,520
Speaker 5: eating lower amounts of super fatty foods decreasing people's heart

1221
01:03:08,520 --> 01:03:13,280
Speaker 5: attack rates, and it's really hard to assess how that

1222
01:03:13,360 --> 01:03:15,680
Speaker 5: changes people's happiness levels.

1223
01:03:15,760 --> 01:03:15,960
Speaker 4: Right.

1224
01:03:16,400 --> 01:03:19,360
Speaker 5: And I'm not saying it's not important to like lower

1225
01:03:19,400 --> 01:03:23,040
Speaker 5: heart attack rates, but there's a complex value trade off here.

1226
01:03:23,160 --> 01:03:25,440
Speaker 5: But when one end is easy to measure, and the

1227
01:03:25,520 --> 01:03:28,240
Speaker 5: other end is not the end that's easy to measure,

1228
01:03:28,720 --> 01:03:31,680
Speaker 5: tends to auto win fights without consideration, right, and the

1229
01:03:31,720 --> 01:03:36,600
Speaker 5: hearder account stuff just disappears from our deliberation.

1230
01:03:36,960 --> 01:03:39,760
Speaker 4: And that's yeah.

1231
01:03:39,800 --> 01:03:43,080
Speaker 1: We just had a guy named Dean Statn and come on,

1232
01:03:43,200 --> 01:03:46,600
Speaker 1: he wrote an article for GQ about how his New

1233
01:03:46,680 --> 01:03:49,880
Speaker 1: Year's resolution was to drink more. So he's one of

1234
01:03:49,920 --> 01:03:54,280
Speaker 1: these guys who's kind of like hyper optimizer fitness culture guys.

1235
01:03:55,200 --> 01:03:58,040
Speaker 1: He hears all these podcasts where they say the absolute

1236
01:03:58,160 --> 01:04:02,360
Speaker 1: best amount of alcohol is zero. Alcohol's associated with xyz

1237
01:04:02,520 --> 01:04:05,160
Speaker 1: bad health outcomes. So he goes, Okay, I'm going to

1238
01:04:05,200 --> 01:04:08,320
Speaker 1: stop drinking. And over the course of about three or

1239
01:04:08,320 --> 01:04:11,919
Speaker 1: four months, he realizes he's depressed and he goes, why

1240
01:04:12,000 --> 01:04:13,840
Speaker 1: is He's less happy? He goes, why is this happening?

1241
01:04:14,640 --> 01:04:16,400
Speaker 1: And he goes, oh, because when I would go out

1242
01:04:16,400 --> 01:04:17,560
Speaker 1: for a drink or two, and he was not a

1243
01:04:17,560 --> 01:04:18,160
Speaker 1: heavy drinker.

1244
01:04:18,320 --> 01:04:19,080
Speaker 2: This is important.

1245
01:04:20,080 --> 01:04:22,920
Speaker 1: He was hanging out with his friends, he was doing

1246
01:04:23,480 --> 01:04:25,600
Speaker 1: new he was going to different places, he was going

1247
01:04:25,600 --> 01:04:27,360
Speaker 1: to sporting events, and he would drink and he would

1248
01:04:27,360 --> 01:04:28,920
Speaker 1: he would go to bars and he'd had these wacky

1249
01:04:28,920 --> 01:04:30,920
Speaker 1: conversations with people at the bar that he never met,

1250
01:04:31,240 --> 01:04:33,640
Speaker 1: and those things are really hard to measure, right, so

1251
01:04:33,680 --> 01:04:35,480
Speaker 1: it seems very clear like, oh, if you just want

1252
01:04:35,520 --> 01:04:39,000
Speaker 1: to optimize your health, you stop doing this thing. But

1253
01:04:39,040 --> 01:04:40,560
Speaker 1: then once he does, he goes, oh, there was all

1254
01:04:40,600 --> 01:04:44,400
Speaker 1: these unmeasurables, Like no one on the long health podcasts

1255
01:04:44,440 --> 01:04:47,120
Speaker 1: are going like, well, we can quantify that if you

1256
01:04:47,200 --> 01:04:50,840
Speaker 1: talk to you know, Sully from Dorchester at the bar

1257
01:04:51,000 --> 01:04:54,160
Speaker 1: for ten minutes, that will increase your happiness by six points.

1258
01:04:54,160 --> 01:04:56,000
Speaker 1: So try and find your version of that, Like that

1259
01:04:56,040 --> 01:04:59,760
Speaker 1: doesn't never happen. And so I think it's that hyper optimization.

1260
01:05:00,080 --> 01:05:04,680
Speaker 1: The number removed all these unmeasurables that people don't often

1261
01:05:04,720 --> 01:05:06,440
Speaker 1: account for, and you can just apply that to a

1262
01:05:06,440 --> 01:05:07,960
Speaker 1: lot of different areas of life.

1263
01:05:08,880 --> 01:05:10,200
Speaker 4: There's I was on this.

1264
01:05:10,960 --> 01:05:12,720
Speaker 5: I was talking to this doctum on a podcast and

1265
01:05:12,720 --> 01:05:14,400
Speaker 5: he was really on board with this stuff. He's worried

1266
01:05:14,440 --> 01:05:16,840
Speaker 5: about metrics and I was like, yeah, you know, happiness

1267
01:05:16,840 --> 01:05:18,120
Speaker 5: and enjoy is so important and he was like yeah,

1268
01:05:18,160 --> 01:05:20,040
Speaker 5: and when you feel joy, we have a lot of

1269
01:05:20,080 --> 01:05:22,120
Speaker 5: evidence that it makes your heart pressure go down, you

1270
01:05:22,160 --> 01:05:25,920
Speaker 5: live a little longer. And I was just like hold on, Like,

1271
01:05:26,480 --> 01:05:31,000
Speaker 5: if we are justifying joy in terms of a medical effect.

1272
01:05:31,480 --> 01:05:34,600
Speaker 5: Then we have gotten things the wrong way. Like that

1273
01:05:34,880 --> 01:05:40,520
Speaker 5: doesn't need further justification in some sort of quantifiable right.

1274
01:05:40,760 --> 01:05:44,120
Speaker 4: I mean, I think you've been drifting around this thought.

1275
01:05:44,160 --> 01:05:45,960
Speaker 5: We've been drifting around this thought, and I want to

1276
01:05:46,000 --> 01:05:48,160
Speaker 5: put one more story down to you. This is something

1277
01:05:48,160 --> 01:05:52,760
Speaker 5: I learned from the philosopher of food, Megandine. She told

1278
01:05:52,800 --> 01:05:57,760
Speaker 5: me about a bunch of medical research about people that

1279
01:05:57,840 --> 01:06:01,880
Speaker 5: had been anorexics for a lot time trying to come

1280
01:06:01,920 --> 01:06:05,920
Speaker 5: off of anorexia. And what people will tell you is, well,

1281
01:06:06,120 --> 01:06:08,840
Speaker 5: what you need to do is till you're satisfied, Just

1282
01:06:08,880 --> 01:06:11,160
Speaker 5: eat till you feel full. And it turns out that

1283
01:06:11,200 --> 01:06:13,680
Speaker 5: a lot of people who have been anorexics for so

1284
01:06:13,800 --> 01:06:17,200
Speaker 5: long have lost their sense of being able to tell

1285
01:06:17,600 --> 01:06:21,200
Speaker 5: that they're full. They lose that internal sensibility. And part

1286
01:06:21,200 --> 01:06:22,840
Speaker 5: of the thing seems to be that when you're so

1287
01:06:22,920 --> 01:06:27,000
Speaker 5: externally oriented towards accountable, you lose touch with an internal

1288
01:06:27,080 --> 01:06:34,080
Speaker 5: sensation of your own feelings. I was talking to I'm

1289
01:06:34,080 --> 01:06:36,960
Speaker 5: making Child's journal she runs, she does, one of the

1290
01:06:37,040 --> 01:06:40,800
Speaker 5: journalists who's on Planet Money. We were talking about this

1291
01:06:40,800 --> 01:06:42,640
Speaker 5: stuff and I told her the story and she was like,

1292
01:06:42,720 --> 01:06:46,200
Speaker 5: oh my god, I realize that I've been working so

1293
01:06:46,280 --> 01:06:48,600
Speaker 5: hard for so long that I can no longer tell

1294
01:06:48,600 --> 01:06:51,680
Speaker 5: when I'm sick because I've just learned to tune that out,

1295
01:06:52,040 --> 01:06:54,160
Speaker 5: And I just like for and I rely on my

1296
01:06:54,200 --> 01:06:56,840
Speaker 5: coworkers to tell me when I'm sick because I can

1297
01:06:56,880 --> 01:07:00,040
Speaker 5: no longer feel it. And I think this is this

1298
01:07:00,480 --> 01:07:02,920
Speaker 5: is related to one of these things where this is

1299
01:07:03,000 --> 01:07:06,960
Speaker 5: like the this is the weird arc, this horseshoe, like

1300
01:07:08,000 --> 01:07:11,200
Speaker 5: it's so interesting to me that when I was completely

1301
01:07:11,320 --> 01:07:13,840
Speaker 5: untuned to my body, what I needed was a simple

1302
01:07:13,840 --> 01:07:17,520
Speaker 5: scoring system to tell me, to give me enough information

1303
01:07:17,880 --> 01:07:19,440
Speaker 5: to be able to tune in and feel pleasure in

1304
01:07:19,440 --> 01:07:21,040
Speaker 5: my body moving and also be able to tune in

1305
01:07:21,080 --> 01:07:23,520
Speaker 5: and tell that eating two pounds of cheesy pasta made.

1306
01:07:23,360 --> 01:07:25,360
Speaker 4: Me feel weird. I needed the data.

1307
01:07:25,920 --> 01:07:28,320
Speaker 5: But on the other end, there's a level of data

1308
01:07:28,360 --> 01:07:32,600
Speaker 5: fixation such that it just overwrites any sensations from your

1309
01:07:32,600 --> 01:07:36,880
Speaker 5: body or your happiness, and you no longer seem to

1310
01:07:36,920 --> 01:07:40,560
Speaker 5: be able to steer by whether things make your life happier,

1311
01:07:40,640 --> 01:07:44,480
Speaker 5: make your body feel better. And that's like the tragedy

1312
01:07:44,520 --> 01:07:47,280
Speaker 5: at the other end that I don't know.

1313
01:07:47,920 --> 01:07:50,520
Speaker 4: It just seems like, yeah, the.

1314
01:07:50,360 --> 01:07:52,760
Speaker 5: Worst thing and a thing I've done to myself like

1315
01:07:52,960 --> 01:07:54,000
Speaker 5: one hundred different times.

1316
01:07:54,040 --> 01:07:57,360
Speaker 1: I feel like anyone listening can probably find an example

1317
01:07:57,400 --> 01:08:00,560
Speaker 1: where this has happened in their life. Where do people

1318
01:08:00,600 --> 01:08:02,520
Speaker 1: go from here? If they're listening, Like how do you

1319
01:08:02,560 --> 01:08:04,960
Speaker 1: identify this? And like what are the conversations you have

1320
01:08:05,040 --> 01:08:07,360
Speaker 1: to have? I don't know if there's a clear answer,

1321
01:08:07,400 --> 01:08:08,600
Speaker 1: but what are your thoughts there?

1322
01:08:09,200 --> 01:08:12,520
Speaker 5: I am the weird kind of optimist about well or

1323
01:08:12,560 --> 01:08:16,960
Speaker 5: romantic maybe. I think games kind of give us an example.

1324
01:08:17,760 --> 01:08:21,560
Speaker 5: I mean, what games are if you're playing them reflectively,

1325
01:08:21,640 --> 01:08:24,120
Speaker 5: if you're playing them in this striving way, is you

1326
01:08:24,160 --> 01:08:26,120
Speaker 5: try on a scoring system and then you step back

1327
01:08:26,560 --> 01:08:30,559
Speaker 5: and you ask yourself, is this what I really want

1328
01:08:30,560 --> 01:08:34,040
Speaker 5: to be doing? You don't just, for most of us,

1329
01:08:34,120 --> 01:08:37,640
Speaker 5: play a game relentlessly. You step back and ask if

1330
01:08:37,680 --> 01:08:40,479
Speaker 5: it's fulfilling to you? And I think that is at

1331
01:08:40,600 --> 01:08:43,360
Speaker 5: least something we can try to carry over towards other things.

1332
01:08:43,360 --> 01:08:45,080
Speaker 5: But it's harder. I mean, part of the difference. I'm

1333
01:08:45,120 --> 01:08:46,880
Speaker 5: not going to just say it's just a flip. You

1334
01:08:46,880 --> 01:08:51,800
Speaker 5: can switch, Yeah, I switch, you can flip. Because the

1335
01:08:52,000 --> 01:08:55,800
Speaker 5: basic our basic relationship to games is one of variety. Right,

1336
01:08:55,840 --> 01:08:57,439
Speaker 5: there's so many games. You can try them, you can

1337
01:08:57,479 --> 01:08:59,759
Speaker 5: move them, you can modify them. And our basic relationship

1338
01:08:59,800 --> 01:09:03,920
Speaker 5: to me is not like the way metrics function. One

1339
01:09:04,200 --> 01:09:07,760
Speaker 5: system tends to become dominant in a social arena, and

1340
01:09:07,760 --> 01:09:11,599
Speaker 5: that's just it's much harder. So the philosopher of Marie

1341
01:09:11,720 --> 01:09:15,080
Speaker 5: Lagonez says that what playfulness is is the ability to

1342
01:09:15,800 --> 01:09:19,800
Speaker 5: hold rule worlds lightly, to step into an out of

1343
01:09:20,000 --> 01:09:23,599
Speaker 5: different world with different rules easily, and to be in them,

1344
01:09:23,680 --> 01:09:24,640
Speaker 5: she says creatively.

1345
01:09:25,080 --> 01:09:27,040
Speaker 4: And I think that's that's.

1346
01:09:26,840 --> 01:09:32,840
Speaker 5: That that that kind of relationship of being able to

1347
01:09:32,960 --> 01:09:38,120
Speaker 5: enter but being distant, reflective, willing to tinker with that's

1348
01:09:37,800 --> 01:09:39,360
Speaker 5: a that's a useful spirit.

1349
01:09:39,439 --> 01:09:43,960
Speaker 4: But it's so damn hard to do well. I love it.

1350
01:09:43,960 --> 01:09:45,160
Speaker 2: In the book, you had this line.

1351
01:09:45,400 --> 01:09:48,200
Speaker 1: The reason you wrote the book, you had a student

1352
01:09:48,880 --> 01:09:52,080
Speaker 1: where you gave a long lecture about all of these topics.

1353
01:09:53,320 --> 01:09:55,439
Speaker 1: You can tell us about the student and why she

1354
01:09:55,520 --> 01:09:58,839
Speaker 1: did this, But she put this question on her phone

1355
01:09:59,160 --> 01:10:01,559
Speaker 1: after your lecture, that said, is this the game you

1356
01:10:01,640 --> 01:10:02,839
Speaker 1: really want to be playing?

1357
01:10:03,680 --> 01:10:04,559
Speaker 2: So tell us about that?

1358
01:10:05,439 --> 01:10:09,360
Speaker 5: Yeah, she wrote me after some of the early I

1359
01:10:09,400 --> 01:10:11,280
Speaker 5: was giving some of the early material from this book

1360
01:10:11,280 --> 01:10:14,800
Speaker 5: and lectures, and she said that it had pulled her

1361
01:10:14,840 --> 01:10:18,880
Speaker 5: out of five years of depression because she realized now

1362
01:10:19,000 --> 01:10:21,040
Speaker 5: she was stuck in games she didn't want to be playing.

1363
01:10:21,080 --> 01:10:23,200
Speaker 5: So she was I mean, she told me, she gave

1364
01:10:23,200 --> 01:10:26,080
Speaker 5: me permission to tell this story. She said she was

1365
01:10:26,560 --> 01:10:29,360
Speaker 5: like me, you know, first generation Asian American immigrant, pushed

1366
01:10:29,360 --> 01:10:32,280
Speaker 5: to get good grades. Also unlike me, of varsity athletes,

1367
01:10:32,320 --> 01:10:36,639
Speaker 5: so pushed to score better, also anorexic, also so obsessed

1368
01:10:36,680 --> 01:10:42,800
Speaker 5: with grades and BMI and nutrition and doing well in

1369
01:10:42,800 --> 01:10:46,120
Speaker 5: her sport, and just spiraling into misery. And what she

1370
01:10:46,160 --> 01:10:49,519
Speaker 5: said she realized was she was stuck in bad games

1371
01:10:50,160 --> 01:10:54,120
Speaker 5: that she hadn't known were bad games, and she hadn't

1372
01:10:54,200 --> 01:10:57,280
Speaker 5: realized she had a choice over And so she said,

1373
01:10:57,320 --> 01:11:00,720
Speaker 5: she programmed her phone, I mean, she just changed the backscreen,

1374
01:11:00,840 --> 01:11:03,400
Speaker 5: the background on her phone to always show her the

1375
01:11:03,400 --> 01:11:06,160
Speaker 5: same question, which is is this the game you really

1376
01:11:06,200 --> 01:11:09,840
Speaker 5: want to be playing? And I think that encapsulates the thing,

1377
01:11:11,479 --> 01:11:16,920
Speaker 5: this frame switch that I'm trying to think about, which

1378
01:11:16,960 --> 01:11:19,960
Speaker 5: is to treat these things the world is shoving at you.

1379
01:11:20,680 --> 01:11:24,760
Speaker 5: Sometimes you can't escape them entirely, like a student can't

1380
01:11:24,880 --> 01:11:26,439
Speaker 5: escape what GPA means to.

1381
01:11:26,360 --> 01:11:27,120
Speaker 4: The rest of the world.

1382
01:11:27,479 --> 01:11:30,720
Speaker 5: But there's still a huge amount of difference between being like, well,

1383
01:11:30,720 --> 01:11:33,200
Speaker 5: these grades are something the rest of the world cares about,

1384
01:11:33,280 --> 01:11:35,120
Speaker 5: but I have my own reasons for education.

1385
01:11:35,200 --> 01:11:35,960
Speaker 4: I'm going to pursue it in.

1386
01:11:36,000 --> 01:11:38,240
Speaker 5: My way versus all I'm just going to do is

1387
01:11:38,280 --> 01:11:39,920
Speaker 5: optimize for grades. All I'm just going to do is

1388
01:11:39,920 --> 01:11:42,040
Speaker 5: optimize for right.

1389
01:11:41,920 --> 01:11:43,880
Speaker 4: Yeah, be a my likes whatever.

1390
01:11:43,920 --> 01:11:46,879
Speaker 1: And what I think is so interesting too is outwardly,

1391
01:11:46,920 --> 01:11:50,839
Speaker 1: if the average person ask that student about their life

1392
01:11:50,920 --> 01:11:54,879
Speaker 1: before your lecture and go, wow, this person's this person's

1393
01:11:54,880 --> 01:11:58,679
Speaker 1: winning four point zero varsity athletes scored twenty five points

1394
01:11:58,760 --> 01:12:02,439
Speaker 1: last game. They're thin, they're fit great, And so that

1395
01:12:02,479 --> 01:12:05,280
Speaker 1: almost reinforces getting stuck in that loop because you have

1396
01:12:05,360 --> 01:12:09,479
Speaker 1: this outside reinforcement, but internally, in that process to get it,

1397
01:12:09,880 --> 01:12:14,080
Speaker 1: misery happened. And so framing back, you know, publicly, maybe

1398
01:12:14,400 --> 01:12:16,320
Speaker 1: if she starts behaving different and now she's got a

1399
01:12:16,320 --> 01:12:18,880
Speaker 1: three point nine, people go, oh, that's not four point zero,

1400
01:12:20,479 --> 01:12:22,160
Speaker 1: But internally she's much better off.

1401
01:12:23,160 --> 01:12:26,800
Speaker 5: Yeah, And I think the whole point is, this is

1402
01:12:26,840 --> 01:12:33,160
Speaker 5: what Porter taught me, the portability theory of quantification, right,

1403
01:12:33,360 --> 01:12:40,080
Speaker 5: that it's no accident that these numbers are what everyone

1404
01:12:40,080 --> 01:12:43,320
Speaker 5: will instantly recognize success because that's what they're made to be.

1405
01:12:43,920 --> 01:12:48,680
Speaker 5: They're made to be instantly accessible, instantly transportable, instantly comprehensible

1406
01:12:49,400 --> 01:12:53,759
Speaker 5: success measures. I mean one of Okay, this is definitely

1407
01:12:53,760 --> 01:12:55,479
Speaker 5: something I found out after the last time I talked

1408
01:12:55,479 --> 01:13:00,400
Speaker 5: to you, the telling some of this stuff to a

1409
01:13:00,400 --> 01:13:02,840
Speaker 5: political phiosopher. He's like, oh, yeah, Hobbs thought a lot

1410
01:13:02,880 --> 01:13:04,800
Speaker 5: about this, and then he told me something that blew

1411
01:13:04,840 --> 01:13:07,320
Speaker 5: my mind. So Thomas Hobbs, political philosopher. A lot of

1412
01:13:07,320 --> 01:13:09,160
Speaker 5: people know him as the person that said that morality

1413
01:13:09,160 --> 01:13:11,759
Speaker 5: comes down to political power and who has more political power,

1414
01:13:12,360 --> 01:13:14,720
Speaker 5: and he ended up saying but he ended up giving

1415
01:13:14,800 --> 01:13:17,120
Speaker 5: us an account of political power that I didn't know about.

1416
01:13:17,520 --> 01:13:20,920
Speaker 5: He says that the true ultimate political power is not

1417
01:13:21,240 --> 01:13:24,240
Speaker 5: military might or strength or force of arms, but the

1418
01:13:24,280 --> 01:13:28,040
Speaker 5: power over language, the power to define what success and

1419
01:13:28,120 --> 01:13:31,120
Speaker 5: failure mean for people, and the power to define what

1420
01:13:31,240 --> 01:13:34,519
Speaker 5: good and bad mean for people. And scoring systems are

1421
01:13:34,640 --> 01:13:38,880
Speaker 5: just definitions of success. Yeah, And if you accept one

1422
01:13:38,920 --> 01:13:43,679
Speaker 5: from somewhere else, you're letting them rule you and letting

1423
01:13:43,720 --> 01:13:46,320
Speaker 5: them tell you the terms in which you think of

1424
01:13:46,360 --> 01:13:49,640
Speaker 5: your own success and flourishing amazing incorrect.

1425
01:13:50,160 --> 01:13:51,400
Speaker 1: We're going to take a quick break, and then we're

1426
01:13:51,400 --> 01:13:55,320
Speaker 1: going to talk about why conspiracy theories are so pervasive

1427
01:13:55,360 --> 01:14:06,519
Speaker 1: and popular in our modern society. It's surprising. Take gonna

1428
01:14:06,520 --> 01:14:10,160
Speaker 1: start landing the plant. I got two final questions. Okay,

1429
01:14:11,479 --> 01:14:13,439
Speaker 1: you have a good theory on why people fall into

1430
01:14:13,600 --> 01:14:14,599
Speaker 1: conspiracy theories.

1431
01:14:15,680 --> 01:14:19,760
Speaker 4: Tell us, yeah, it's actually super related. Yeah.

1432
01:14:19,840 --> 01:14:22,880
Speaker 5: So, clarity, I think is the feeling of getting things,

1433
01:14:22,920 --> 01:14:25,120
Speaker 5: the feeling that everything makes sense. The way that some

1434
01:14:25,120 --> 01:14:30,080
Speaker 5: philosophers of science and education put it is that when

1435
01:14:30,120 --> 01:14:32,120
Speaker 5: you understand something, you have a good model for you

1436
01:14:32,360 --> 01:14:35,599
Speaker 5: see how everything connects together. And one of the things

1437
01:14:35,640 --> 01:14:39,719
Speaker 5: I think is that you often get these fake models

1438
01:14:39,720 --> 01:14:42,799
Speaker 5: that oversimplify things and make everything easy to connect.

1439
01:14:42,920 --> 01:14:44,639
Speaker 4: That's what a conspiracy theory is, right.

1440
01:14:44,720 --> 01:14:47,559
Speaker 5: Suddenly, instead of the complexity of the world, you just

1441
01:14:47,600 --> 01:14:51,360
Speaker 5: have one thing that will explain everything really powerfully. Do

1442
01:14:51,439 --> 01:14:54,320
Speaker 5: I also think metrics do something similar. Instead of having

1443
01:14:54,360 --> 01:14:57,639
Speaker 5: to justify yourself with a million different values, you suddenly

1444
01:14:57,680 --> 01:15:00,000
Speaker 5: have this one thing that tie Like, everything I'm doing

1445
01:15:00,120 --> 01:15:03,719
Speaker 5: is because it makes my salary go off. For everything

1446
01:15:03,760 --> 01:15:06,320
Speaker 5: I'm doing is because it makes my sleep score go up.

1447
01:15:06,320 --> 01:15:08,680
Speaker 5: You have this one all consuming measure that can just

1448
01:15:08,720 --> 01:15:12,719
Speaker 5: reach out into everything and make explanation really simple.

1449
01:15:12,880 --> 01:15:15,519
Speaker 1: Yeah, and that was so I loved it so much

1450
01:15:16,120 --> 01:15:18,599
Speaker 1: because there's almost a paradox when you look at when

1451
01:15:18,600 --> 01:15:21,000
Speaker 1: you hear people talk about conspiracy theories. You know, we

1452
01:15:21,040 --> 01:15:23,960
Speaker 1: have the image of the person who's on the wall

1453
01:15:24,000 --> 01:15:27,439
Speaker 1: of their house. They have like fifty pictures and one

1454
01:15:27,439 --> 01:15:29,360
Speaker 1: thing leads to another and another and another, and it

1455
01:15:29,400 --> 01:15:32,439
Speaker 1: looks very complicated, but in the end there is a

1456
01:15:33,040 --> 01:15:36,559
Speaker 1: very specific answer. It's a government conspiracy. It can't just

1457
01:15:36,560 --> 01:15:38,800
Speaker 1: be like, oh, well, maybe someone was incompetent down the line.

1458
01:15:38,800 --> 01:15:41,639
Speaker 1: Maybe this is just really complicated, like we don't really

1459
01:15:41,680 --> 01:15:42,719
Speaker 1: know who knows.

1460
01:15:43,479 --> 01:15:46,320
Speaker 2: You get that clear answer and it's like, ah, that's

1461
01:15:46,400 --> 01:15:48,760
Speaker 2: the read. That's why things are not good.

1462
01:15:49,640 --> 01:15:53,439
Speaker 5: I mean, it's a lot of what's behind a lot

1463
01:15:53,520 --> 01:15:56,479
Speaker 5: of what I've been thinking about is that the world

1464
01:15:56,560 --> 01:16:00,200
Speaker 5: is unbelievably complicated and human brains are tiny and small,

1465
01:16:00,880 --> 01:16:05,200
Speaker 5: and it feels good when we can simplify the world.

1466
01:16:05,240 --> 01:16:07,960
Speaker 5: And in games, that's what games are. There's simplifications of value.

1467
01:16:08,000 --> 01:16:10,920
Speaker 5: You just get to focus on this one thing. But

1468
01:16:11,000 --> 01:16:16,439
Speaker 5: it's temporary. With games, we know it's temporary. With other stuff.

1469
01:16:17,320 --> 01:16:22,160
Speaker 4: When you reduce everything to a single conspiracy theory or

1470
01:16:22,960 --> 01:16:28,320
Speaker 4: an attempt to maneuver your entire life around your longevity,

1471
01:16:29,840 --> 01:16:31,000
Speaker 4: it's an illusion.

1472
01:16:30,680 --> 01:16:35,040
Speaker 1: Or grades or salary or insert so many things. Yeah, yep,

1473
01:16:35,920 --> 01:16:40,400
Speaker 1: all right, you are a You are like a foremost

1474
01:16:40,560 --> 01:16:46,320
Speaker 1: expert in board games, and you actually got me. After

1475
01:16:46,360 --> 01:16:49,200
Speaker 1: we talked, I started getting into board games, and I

1476
01:16:49,200 --> 01:16:51,880
Speaker 1: thank you for that. There's so much fun. Those were

1477
01:16:51,880 --> 01:16:55,000
Speaker 1: missing from my life. One hundred percent. Three board games

1478
01:16:55,000 --> 01:16:58,040
Speaker 1: that you would recommend to everyone. Start with one that's accessible,

1479
01:16:58,080 --> 01:16:59,759
Speaker 1: and then get into whatever you want from there.

1480
01:17:00,200 --> 01:17:04,320
Speaker 5: Okay, The most accessible, simple game that you can be

1481
01:17:04,400 --> 01:17:06,759
Speaker 5: playing in like three minutes, it's amazing, is The Mind.

1482
01:17:07,120 --> 01:17:10,000
Speaker 5: This is like modern game design. So The Mind is

1483
01:17:10,000 --> 01:17:13,960
Speaker 5: a cooperative game where you're trying to do the simplest task.

1484
01:17:14,240 --> 01:17:17,040
Speaker 5: The game randomizes number of cards cards to people, and

1485
01:17:17,080 --> 01:17:19,000
Speaker 5: you have to play them out in order. You have

1486
01:17:19,000 --> 01:17:21,640
Speaker 5: to cooperate to play them out in order, except you

1487
01:17:21,680 --> 01:17:24,200
Speaker 5: can't talk or signal or communicate in any way.

1488
01:17:24,400 --> 01:17:24,759
Speaker 2: Awesome.

1489
01:17:25,160 --> 01:17:29,639
Speaker 5: So the game forces you to develop a shared vibe

1490
01:17:29,800 --> 01:17:33,400
Speaker 5: about the appropriate amount of time to wait. It teaches

1491
01:17:33,439 --> 01:17:37,720
Speaker 5: you to silently learn to like develop a sense of

1492
01:17:37,760 --> 01:17:40,479
Speaker 5: timing together. One of my students said it felt a

1493
01:17:40,520 --> 01:17:42,840
Speaker 5: lot like learning to be in a jazz band together,

1494
01:17:42,960 --> 01:17:45,080
Speaker 5: except you could get there in like thirty minutes with

1495
01:17:45,120 --> 01:17:48,000
Speaker 5: one group because the task was so simple. That is

1496
01:17:48,520 --> 01:17:54,519
Speaker 5: my favorite simple game. My favorite ultra complicated board game

1497
01:17:54,600 --> 01:18:01,440
Speaker 5: right now is Cole Worley's Route, which is a simulation

1498
01:18:01,560 --> 01:18:04,719
Speaker 5: of a complex economic social conflict translated into cute little

1499
01:18:04,720 --> 01:18:07,880
Speaker 5: fairy tale animals. But one of you is like an industrialist,

1500
01:18:07,880 --> 01:18:09,880
Speaker 5: and one of you is like communist revolutionaries, and one

1501
01:18:09,880 --> 01:18:12,120
Speaker 5: of you is like an arms dealer, and you're viewing

1502
01:18:12,120 --> 01:18:13,160
Speaker 5: the world in total different way.

1503
01:18:13,160 --> 01:18:14,639
Speaker 4: It's super interesting, awesome.

1504
01:18:16,439 --> 01:18:19,439
Speaker 5: The last so there's this world of indie tabletop role

1505
01:18:19,439 --> 01:18:22,200
Speaker 5: playing and maybe my favorite right now from that space

1506
01:18:22,280 --> 01:18:25,040
Speaker 5: is called The Quiet Year by Every Archer, and it's

1507
01:18:25,080 --> 01:18:30,200
Speaker 5: a storytelling game in which you play the spiritual godlike

1508
01:18:30,280 --> 01:18:34,040
Speaker 5: forces that surround a village barely surviving after the apocalypse,

1509
01:18:34,439 --> 01:18:36,599
Speaker 5: and you have to respond to various prompts and tell

1510
01:18:36,600 --> 01:18:39,559
Speaker 5: a story about the villagers, and every turn you have

1511
01:18:39,600 --> 01:18:42,880
Speaker 5: to draw the event that just happened onto a shared map,

1512
01:18:43,000 --> 01:18:47,280
Speaker 5: so you slowly build this beautiful shared map as you

1513
01:18:47,479 --> 01:18:50,320
Speaker 5: like tell the trials and tribulations and you have people

1514
01:18:50,439 --> 01:18:52,559
Speaker 5: die and help you to other learn survive, And it's

1515
01:18:52,640 --> 01:18:56,200
Speaker 5: just like this piece of collective narrative magic that you

1516
01:18:56,200 --> 01:18:56,640
Speaker 5: can just do.

1517
01:18:56,760 --> 01:18:59,400
Speaker 1: It's like a Russian novels translated into board games.

1518
01:19:00,040 --> 01:19:01,559
Speaker 4: Yeah, amazing, you live improvise.

1519
01:19:01,760 --> 01:19:03,240
Speaker 2: I love it well.

1520
01:19:03,280 --> 01:19:05,280
Speaker 1: Tee, thanks for so thanks so much for coming on

1521
01:19:05,320 --> 01:19:08,920
Speaker 1: the show. This was fantastic. Thank you so much, Man,

1522
01:19:10,560 --> 01:19:12,439
Speaker 1: Thanks as always for checking out the show, and many

1523
01:19:12,479 --> 01:19:15,559
Speaker 1: thanks to t for coming on the episode. His book

1524
01:19:15,640 --> 01:19:18,800
Speaker 1: is called The Score, How to Stop Playing somebody Else's Game.

1525
01:19:18,960 --> 01:19:20,720
Speaker 1: If you want to live better and think better, I

1526
01:19:20,800 --> 01:19:23,599
Speaker 1: highly recommend you get that book. It is probably number

1527
01:19:23,640 --> 01:19:27,719
Speaker 1: one on the best books I've read this year. As always,

1528
01:19:27,920 --> 01:19:29,880
Speaker 1: we are going to be in your feeds twice a week,

1529
01:19:30,040 --> 01:19:32,320
Speaker 1: so keep an eye out for more. Send us questions

1530
01:19:32,320 --> 01:19:35,720
Speaker 1: for our Ask Michael Anything section to media at twopct

1531
01:19:35,840 --> 01:19:39,200
Speaker 1: dot com or drop them in the comments, Send us

1532
01:19:39,200 --> 01:19:40,559
Speaker 1: a voice memo or a video.

1533
01:19:40,840 --> 01:19:41,360
Speaker 2: We love that.

1534
01:19:41,520 --> 01:19:45,559
Speaker 1: Try and answer as many questions as possible, and please

1535
01:19:45,640 --> 01:19:49,280
Speaker 1: do not forget to subscribe, because if that number gets higher, clearly,

1536
01:19:49,320 --> 01:19:51,479
Speaker 1: as we just learned in today's episode, my life will

1537
01:19:51,479 --> 01:19:56,080
Speaker 1: get so much better. Have fun, don't die, and maybe

1538
01:19:56,080 --> 01:20:02,120
Speaker 1: don't always abide by the numbers.

1539
01:20:04,200 --> 01:20:04,960
Speaker 2: Glascock