You Will Need This to Push Through | Is AI Making Us Stupid?

0:00Ryan Holiday: Welcome to the Daily Stoic Podcast, designed to help bring those four key stoic virtues, courage, discipline, justice, and wisdom, into the real world.

0:14Ryan Holiday: Look, if you hated the taste, if it didn't feel good, if you weren't getting good results, if it didn't guarantee a dopamine hit, it wouldn't exactly require much discipline to steer clear. That's the whole point of the virtue, though, isn't it? That it's requiring you to resist an impulse or forgo a pleasure. As we said recently, discipline is about doing what's hard. Just as courage is the triumph over fear, discipline is the triumph over another lower part of our nature. A lot of times discipline is pushing yourself to do something you don't want to do. But the other part of it, which we might call the temperance part, is not doing the stuff you want to do.

0:53Ryan Holiday: And in some ways, this takes the most strength. Seneca said that we're all slaves to one thing or another, sex or ambition or attention or chaos. And by indulging in these passions often enough, eventually we lose the freedom to abstain from them. We just can't not. We need discipline to push through that, to resist the urge to keep going when it's not serving us, to step back when our ambition tempts us to overreach, to recognize that rest and recovery and restraint are not signs of weakness, but also of strength and wisdom. True discipline means knowing when to stop. It's having the courage to say no to the extra hour, the extra project, the unsustainable pace, so that we can sustain ourselves for the long haul.

1:34Ryan Holiday: Discipline in this way isn't just about action. It's also about control, control over our impulses, our desires, even our most deeply ingrained habits. Without this, we are slaves. Only through temperance can we ever be free. And I talk a lot about that in Discipline is Destiny. I didn't just want it to be a book about do this, do this. There's a bunch of things we need to stop doing. And discipline is understanding that. You can grab a signed copy at store.dailystoic.com. But if you are looking for some better overall habits, you might like our Daily Stoic course, Habits for Success, Habits for Happiness, which is a six-week deep dive into better Stoic habits, which you can sign up for right now.

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5:20Ryan Holiday: So what does AI actually do? Like, what is it for? Does it make us better? Does it make us faster? Does it make life easier? Or is it here to replace us? Is it making us stupider? Is it ruining the world? is it undermining the sort of basic skills that we have to develop as people? And then we have to continue to develop it as people, you know, sort of being thoughtful, being reflective, thinking, researching, practicing our skills, right? These are the questions, right? These are the questions that if the people in the AI companies are not asking or if the politicians are not asking, than we ourselves have to ask personally and professionally.

6:09Ryan Holiday: And it's actually one of the things I asked today's guest, one of my friends, David Epstein, about. I've raved about David's work for years. He's the best-selling author of Range and the Sports Gene. He has this awesome new book called Inside the Box, How Constraints Make Us Better, which came out on May 5th. Loved it. I actually read it back in January, so I had to sit. Speaking of constraints, I couldn't tell you how awesome it was until closer to it coming out. But in today's episode, we riffed a little bit on AI, how we use these tools without letting them use us, how you have to use your brain first.

6:44Ryan Holiday: Remember that story I tell in Wisdom Takes Work from Seneca about where he says, like, nobody becomes wise by chance. You don't become good at anything by accident. If you don't develop these skills, they atrophy. That doesn't mean you can't use tools. That doesn't mean there aren't some ways that it can make you better. I think that's, in fact, quite clearly the case. But anyways, David and I are talking about using the brain first, then AI, how David uses it in his work, and how we need these constraints if we want technology to help us without becoming a crutch. We shape our tools and our tools shape us.

7:18Ryan Holiday: And that's what this conversation is about. Like I said, if you haven't read David's work, you absolutely should. He's been on the podcast a bunch. And this is just a short little episode with him and I talking about a very important topic in the news. Talk to me about your thoughts on AI, because like what it does is it makes a lot of really hard time consuming things easy. Yeah. And so is that a good thing or a bad thing? Yeah, a few things. I mean, we were talking about desirable difficulties, things that make learning more difficult. And so far, this this kind of first, let's say, like first run of research on AI looks terrible from that respect.

7:56There was an MIT study that got a lot of headlines talking about brain rot, how using chat GPT will rot your brain. But there was actually more nuance in the study. So these MIT students had to write essays on different topics, and they were broken up into groups. One group had to just write using their brains, and one group had to write using chat GPT. They could use chat GPT. They didn't have to, and they write on these topics. And then they're brought—I think they wrote three essays. And then they're brought back sometime later and they have to write on the same topics again. And they're asked about the things they wrote.

8:29And this time they're switched. So the brain first group can now use ChatGPT and the ChatGPT can now go to brain. And basically everything for the ChatGPT group looked worse. They didn't remember anything they'd written. Their essays were more uniform and homogenous and less interesting. Whereas the group that used ChatGPT second did quite well. You know, there were stuff about their brain activation, but I don't like to lean on fMRI data. So I think the rule that comes out of it as a suggestion would be brain first, tool second. And there's just this mounting evidence that seeing that people are using it to kind of replace their thinking instead of to supplement it and that that's bad because then they do not learn.

9:05Like if they have it right, their first draft, they have real trouble recalling any of the content. It's actually even if they're like, and then I go over it. Right.

9:12Ryan Holiday: The point of writing the essay is is to write the essay, not to have the essay. It's to force yourself to do a hard thing, even if it's somewhat arbitrary thing. It's to force you into this structure that requires you to think and comprehend and communicate in a certain way. And then you, on the other side of it, yes, you do have the essay. But more importantly, you have the skills of having done the thing. A huge portion of the writing that everyone does, especially when they're younger, is not because you care about getting the best essay. Yes. It's because you're learning how to make an argument, how to think.

9:47You're learning the material that's in there. You're learning how to organize things coherently. It's not because you need the most polished essay in the world. And so I think this, so, you know, we're still early days for this research, but so far it's looking pretty bad for how it affects people's thinking. I think there are other things. I find it fascinating. Like there's a research use I have for it that turned something that would take me 10 hours into one. Of what? So I use this site where I can upload a paper, scientific paper, and it will immediately create a map of other papers that cite my paper with bubbles of different size showing how cited those papers are.

10:19So I can see which are the real big deals in this field that cite my paper. It'll try to automatically organize them into supporting or refuting. I'd say it's right, like say 75 % of the time. And then it will make a list that excerpts a few sentences around the mention of the paper that I'm interested in. That's something I used to control F my way through PDFs for, for hours and hours and hours. So that's amazing. And I mean, I find it interesting in all sorts of ways. At the same time, I think there's that issue with the undesirable ease that it does it thinking where it's, you know, it depends how you use it.

10:51The task is supposed to be hard. The task is supposed to be hard. That's the nuance that was lost in the brain rod headlines, which is that it did actually show that if you used brain first, it was good. The other thing I think is it just gives people an infinite capacity to just start a bajillion different things and to create, you know, now you're hearing this term work slop to just create a ton of mediocre stuff that buries the people who are getting it.

11:11Ryan Holiday: Research this for me. And then they give you 80 pages of shit they printed out as opposed to thinking about. So it's like creating more work in the system. It might offload from one person, but if there's this cartoon where someone is like, AI is great. I gave it these four bullet points. It turned it into a six page email. And then the other end, the person gets the email is like, AI is great. It took the six page email and turned it into four bullet points. So I think there's a lot of that going on. And I think, you know, through the lens that I'm thinking of the world right now, I think there's going to be even more need for proactive constraints because you can start so much stuff and do so much stuff.

11:42There's actually one AI company that I've spent a bunch of time with because I know the founder and I wanted to understand how these things work, how they train. So I sit in on their demos and all this stuff. I've talked to other companies that use them. And one of the things I've noticed is most of these companies are saying, I need AI. I know I need AI. But they haven't. So they implement it. But they didn't identify a problem. Yes. And define it well that the tool matches. Right. And so they'll end up implementing it and it starts. Generally instead of specifically. Yeah. And they're, you know, generating more of this work slop and all this stuff.

12:16And so I think we're often skipping over the define the problem and then let's see how the tool fits with this. Because there's this race, you know, you feel so behind if you haven't implemented it everywhere.

12:26Ryan Holiday: Yeah. I was thinking about AI through the lens of your last book about range, right? Because obviously if you only do a very specific thing, the chances of it replacing you, I guess, would be higher in some ways, right? Like we've spent the last 15 years telling everyone to become coders and now it's really good at coding. That was like supposed to be the safest job five years ago. That's not great. But I've also found it in my use of it, which is that like, if I have a decently broad base of knowledge about an area, actually, I find the AI is not that great because I'm able to spot all the ways that it's wrong.

13:02Ryan Holiday: And it's in fact where if you're a specialist, you're actually more vulnerable to this because you don't know what you don't know. And then you're more reliant on it. So there's some stuff it does really good, but I'm finding to be good at it, what you have to have is kind of a broad liberal arts knowledge base. Recognizing slop requires a lot of knowledge. Yeah, I think it requires actually knowing a ton of stuff, first of all. Yes, you're like, this is dog shit. Like knowing information. Yeah. Yeah. Which people think is just obviated now. Yeah. And just having a good sense of kind of information hygiene, like where to say this doesn't sound right.

13:37Two things, to your point. First of all, I had this experience recently of conversing with AI, I guess. And it brought up a fact that I was like, how did you know that? It was about the number of Charles Darwin's pen pals that he kept, and he would like hit them up for information on. And I was like, man, that is a very obscure fact that I happen to know because I read this specific paper that went into range for it. And then it said and then it talked about the researcher that studied his pen pal correspondence. I'm like, that is so weird. I know both of these things and that's the right fact, but the wrong researcher.

14:08And it's creating this whole narrative about it. And so I started asking, what's your source? Yeah. It turns out it's me. It was excerpts that somebody put up on Goodreads or whatever, some part of my book. And it had taken two things that were close in physical proximity, mashed them together, and then like filled it out with a narrative, basically. Added slop on top of it. Yeah. I'm like, you would never, like, I might be the one person that would have caught this particular thing, right? Yes. So there's that aspect of it. And also, I mean, one thing that's happened, Range is kind of having a little bit of a second life because the beginning of the book is framed early in this like looking at kind and wicked learning environments in the world.

14:49Like these situations that are sort of more stable where you solve the same problem over and over versus those where you have to kind of reinvent and learn new things all the time. And increasingly, we're all in that wicked world where like work next year won't look like work last year. And the argument it makes is that people with breath are particularly prepared for that kind of world. and even gets into, you know, using human-computer chess partnerships as a model, like where things are going. And I had no idea where we were going to be with AI now, but people have started to view that as prescient, as this argument for, like, these synthesizers being more powerful.

15:24And, like, Anthropic just said they only want programmers with side quests. and the Financial Times just did this big analysis that showed that the returns to like collaborative and coordination skills are accelerating and how fast they're outpacing, like just technical skills. So I think we're going to need people building the LLMs, of course, are specialists, but other people are going to have to learn broadly and reinvent if they want to not just be producing a ton of slop.

15:51Ryan Holiday: When do you think even like what they call sort of query management or prompt engineering? Prompt engineering. But like, so if you're like, hey draw me a picture of this it's going to give you some random slot basically but if you're like if you're able to go hey i want a picture of this in the style of this artist from this era by the way i don't want it to look like x y or z like the more precise you're able to be and the irony of that preciseness coming from your broad sense of all the different avenues that it could go it's really important. Like you have to have this sense of knowledge. I was having to do something in this book I'm researching now.

16:30Ryan Holiday: I'm exploring like this brief period in somebody's life when he was on a college football team. And I have this letter where he's listing some of the people he remembered playing with. And so I like upload this chunk of the letter and I'm able to, I'm asking, okay, like what did these people go on to do? Right. And so this is eight, 70 years ago or something, you know, some of the names are common, some of them are not. And it's telling me, oh, this person went on to do this and this person went on to do this, this person went on to do this. And like, it makes this one confusion, you know, Stan Turner goes on to play, you know, has a moderate professional football career.

17:08Ryan Holiday: And it's like, okay, no, no, this is clearly Stan's field Turner, who goes on to be the director of the CIA and the Carter administration. But I knew enough to go, hey, you've confused this person and this person. It is never going to be like, it could be this person or it could be this person. I don't know. It's going to confidently give me the answer. And I have to not confidently, but be just unsure enough that I go, are you sure you don't mean this? And then we're able, like, so you have to have this basis of knowledge that allows you to spot bullshit. Yeah. And then just like anyone that's ever used a research assistant, also you have to have this meta understanding that you can never trust anything anyone gives you.

17:52Ryan Holiday: You have to, if someone is prepping stuff for you, you have to then go independently verify all this information or there's a vulnerability in your system. And so like the ability to know, have that sort of just intuitive bullshit detector and then the knowledge base to know what's not working and not working. And then also the standards, which is like I will never turn in or publish or show anyone anything that I haven't personally vetted. These are all skills that you're going to need to function in this. I think those take a while to develop, though, too. When I think about some of the mistakes I made as an early journalist, I didn't recognize certain potholes that are obvious in retrospect until I like got something wrong.

18:35Yeah.

18:36Ryan Holiday: You trusted a source and then your editor was like, well, what do you mean you just printed what they said or whatever? Yeah. You learn. And you don't even know some of the assumptions you make. Right. So in this book, I ran a lot of stuff I was writing through AI, you know, for fact check, but I had hired a human fact checker also. Yes. And I was a fact checker in the past. And I also went through it myself, like line by line, crossing out one line at a time. and when I finished the book, because I kept really good, in my first book, The Sports Gene, I was a little sloppy with citation. I was like, this is so interesting.

19:05I'll remember where this came from. And then it took me six weeks to like recreate my sources and do bibliography. With range, I kept better track, but still sometimes was trying to recreate something. This time it was like every line I annotated. So I wouldn't, so this time when I finished with Inside the Box, I was like, do I need to spend 10 grand on a fact checker? Like, I think I was really careful this time. I probably nailed it. And then I fact-checked myself. I probably made a change on every page going back through. Like you just are not attuned to all the assumptions you make. And if you're slowing down to catch them all, you never get the thing done also.

19:38Ryan Holiday: Well, isn't that one of the benefits though, to flip your book's premise on its head, right? Like there are things that constraints would prevent you from doing, right? So it's like, I would say AI is not great at fact-checking, but it's also free. So like I, yeah, on my last book, I ran it through or even stuff as I'm writing now, I'll run it through and I'll go, hey, what am I missing? Where could this be better? What's wrong? You know, is anything jump out at you as being incorrect? And I would say 85 percent of what it brings up is totally wrong. Like it caught this thing where it was like, hey, you know, it says this.

20:13Ryan Holiday: That can't possibly be true. It's like, OK, well, I have a letter from 1962. Yeah, yeah. Like this is, in fact, exactly what happened. And so it's false positives are very high. But if it gives you one or two or three or 10 things that you wouldn't have caught otherwise. And all you're paying is this monthly fee. That's great. Right. Like you probably wouldn't have hired two fact checkers or three fact checkers. So you still do it the old way. And then you get this other way on top. That's only upside. And in this case. Right. Only upside. Because you're just saying, oh, I better take a closer look at that.

20:47Essentially. You're not saying this is going in. Right. So it's just attuning you to things you may have overlooked, which I think is great. And I would say for people that are listening to us and thinking about using it in this way, I would say use very, very small chunks when you put that in. Because I think that people have a tendency, if it spits out a long answer, the more text you're looking at at once, the less meticulous I think you're going to be about questioning this. If it gives you a few sentences, I think you're going to focus in and question the things that it said. if you're like fact check these 20 pages and it spits out 20 pages i just don't think you're going to be as careful so i would do it in very one chunk two chunk which again is hard because you could throw in hundreds of pages and say fact check this thing right well the and then the other

21:29Ryan Holiday: interesting thing about constraints right is like so you you can have you read this section give me your notes and then it does it and then you can you can do as you wouldn't do with a person because you're not a monster you'd be like do it again do it again do it again and what's remarkable is how you'll get different answers each time. And so again, the lack of constraints, the reduction in cost, let's put aside the environmental impact, which I don't know enough about to speak a throat table, but you can have it do the task many, many times. So if you're like, hey, I want a picture for a presentation.

21:59Ryan Holiday: I want it to look like this. I want it to look like this. And then it does it and you go, okay, try it again. Actually, give me three options. Make it better. Right. You just say, make it better. And you get it. And so the reduction in constraints allows you to get things that you wouldn't get out of a human, which is five options, and then you can mix and match them together. And there's benefits there. For sure. For sure. And I mean, that's like the march of a lot of efficiency and a lot of our tools, right? Or what Clayton Christensen called empowering innovations. They bring something that, you know, maybe someone with a staff could have done, but now someone without a staff can do it much more cheaply.

22:33It's like where, you know, you used to have to have like a desktop computer and then it gets cheaper and everybody can carry went around with them. But I do still think it's incumbent upon people to put a lot of constraints into that process or else you just end up with the work slop stuff and outsourcing your thinking completely, which is a whole other problem. Like I wonder for some jobs now, you know, so five years ago coding is you learn to code. You never need another job. Now it's like the least safe thing. Maybe other than some of what we do, I don't know. But I wonder how do you get kind of senior coders if you don't have junior, like where are the minor leagues for a lot of these things or when I didn't end up working as a, I mean, I did when I was a grad student, worked as a scientist, but how do you get your hours to be this?

23:15Yeah. Like I developed in, so much of my work has been based on research, peer reviewed research that I thought was wrong that I picked out because I had a strong quantitative background and I got that intuition from being in grad school for geology. Right. Right. And so it's like, where do you, if you just skip over that, you don't really get that intuition that allows you to pick out stuff that's wrong.