Making Sense with Sam Harris - #363 — Knowledge Work

Episode Date: April 15, 2024

Sam Harris speaks with Cal Newport about our use of information technology and the cult of productivity. They discuss the state of social media, the "academic-in-exile effect," free speech and moderation, the effect of the pandemic on knowledge work, slow productivity, the example of Jane Austen, managing up in an organization, defragmenting one's work life, doing fewer things, reasonable deadlines, trading money for time, finding meaning in a post-scarcity world, the anti-work movement, the effects of artificial intelligence on knowledge work, and other topics. If the Making Sense podcast logo in your player is BLACK, you can SUBSCRIBE to gain access to all full-length episodes at samharris.org/subscribe. Learning how to train your mind is the single greatest investment you can make in life. That’s why Sam Harris created the Waking Up app. From rational mindfulness practice to lessons on some of life’s most important topics, join Sam as he demystifies the practice of meditation and explores the theory behind it.

Welcome to the Making Sense Podcast. This is Sam Harris. Just a note to say that if you're hearing this, you're not currently on our subscriber feed, and will only be hearing the first part of this conversation. In order to access full episodes of the Making Sense Podcast, you'll need to subscribe at samharris.org. There you'll also find our scholarship program, where we offer free accounts to anyone who can't afford one. We don't run ads on the

podcast, and therefore it's made possible entirely through the support of our subscribers. So if you enjoy what we're doing here, please consider becoming one. Well, there's a lot going on in the world. Iran recently attacked Israel to minimal effect, happily. I think there's one casualty at this point. Anyway, there'll be more to say about that soon enough. I will wait until I can do a proper podcast on the topic of Iran and what to do about it. Today I'm speaking with Cal Newport.

Cal is a professor of computer science at Georgetown University, where he is also a founding member of the Center for Digital Ethics. Cal is also a New York Times bestselling author and a frequent contributor to The New Yorker. He also hosts the Deep Questions podcast. And Cal's most recent book is Slow Productivity, The Lost Art of Accomplishment Without Burnout. And we talk about the book today. We generally discuss information technology and the cult of productivity. We talk about the state of social media, the academic in exile effect, free speech in moderation, the effect of the pandemic on knowledge work, and then we get into his book. We talk about Jane Austen as an example of

traditional productivity, managing up in an organization, defragmenting one's work life, Managing up in an organization, defragmenting one's work life, doing fewer things, reasonable deadlines, trading money for time, how we will find meaning in a post-scarcity world, the anti-work movement, the effects of artificial intelligence on knowledge work, and other topics. And now I bring you Cal Newport. I am here with Cal Newport. Cal, thanks for joining me again. Sam, it's always a pleasure to talk with you. So we're going to talk about your new book, Slow Productivity, The Lost Art of Accomplishment Without Burnout. But before we do, I first have to thank you. I think I must have thanked you by email in the intervening year and a half since we last spoke. But you, as you know, you were the final domino to fall that led me to get off Twitter. And as I've said,

really, every time I've touched this topic on this podcast and elsewhere, I'm just embarrassed to have discovered what a great life hack that was. I mean, it was just it was diagnostic of how much a problem Twitter had become for me. influence and your wisdom on that front and your actual intervention. I mean, you just straight up told me you thought I should get off Twitter in our podcast and your voice was definitely in my head when I finally pulled the plug. So thank you. I mean, you're welcome. I enjoyed and found fascinating the reaction to you leaving Twitter. I don't know if this is how you experienced it, but to me, it's what I imagine it's like when your buddy at the bar stops drinking because people got mad that you left. I can't imagine being mad about someone stopping doing something, but people is as if they took it personally, as far as I could tell, what do you mean you're leaving Twitter? What's wrong? I thought that was as instructive

as hearing about what your experience has been like after you left. Yeah, people did get mad. And from the top down, Elon Musk was one of the people who got quite mad. It was interesting. I mean, obviously much of the reaction I didn't see because I was no longer on Twitter, but I got a lot of it in my inbox. Many people immediately reached out, worried that I was suffering some kind of mental health crisis. I mean, how do you delete your Twitter account apart from being in extremis? But it's been wholly good and has allowed me to not just pay attention more to things I actually care about, but just it's allowed me to reflect on

what my engagement with Twitter had become. And it was, I mean, I think people's negative reaction to it is to some degree understandable because my decision really wasn't just for me and my perception of, you know, what Twitter was, you know, had done to my own mind, it is an implicit and even explicit, every time I talk about it, condemnation of what I think social media has done to most people on it. platforms. But for most of the so-called elites, journalists and scientists and public figures who think they are condemned to use this so-called digital town square to maintain their reputations and build their brands and all of that, and to just stay in touch with what's going on in the world, it has become so dysfunctional. And I don't think this, I can't recall if this came up in our conversation, but one of the reasons why I left was not so much my awareness of what it had done to me, but kind of the obvious evidence of what it was doing to Elon, not as the owner of the platform, but just as his most, you know,

most prominent user. And I just saw, it was just kind of staring into the funhouse mirror of his life derangement, which was just quite obviously happening as result of his addiction to the platform. I then began to reflect on the way in which I was sharing in that symptomology, you know, albeit somewhat differently, but still, I still, once I pulled the plug, it was like I had almost like a digital phantom limb syndrome. In fact, it was analogous to amputating a phantom limb because I felt that the pain I was experiencing was happening in a space that wasn't quite real ever. The digital reputation

you imagine you're maintaining isn't quite, I mean, you can't quite say it's not your reputation. Obviously, it is your reputation, but it is almost a second presence in your mind and life, which doesn't totally map onto your life in real social space with real people in the real world. Even with the same people who you might be fighting with online, when you actually meet them face to face, those conversations are different. And so it just, it was like amputating a phantom limb. And I mean, I just can't say enough about what a positive change has been. It's been quite incredible. Well, I did some writing about this more recently, and I had you in mind a little bit

when I was thinking about this. I wrote this New Yorker essay late last summer, early fall. And one of the big questions I had in there is, why did we come to believe that the right way to use the internet to have discussions, the sort of surface ideas, the spread news, why did we think the right way to do this was to try to get everyone to use the same global platform? And we take this for granted as like, of course, this is what you should do. We should have everyone use the same global conversation platform because if we're all on the platform, we all can see each other. But of course, the reality, and I sort of laid this out in the article, is when you have 500 million tweets being generated per day, and the average person is going to see 100 in their feed, what you have to do is just incredibly aggressive curation. You can't have 500 million people using the same platform and yet have a sort of globalized, centralized, zeitgeisty feed where you're trying to surface a small number of trends for everyone to see. This requires incredible curation, this sort of amazing cybernetic part algorithm, part human, part network theory powered curation that Twitter uses.

And it's, of course, that incredibly aggressive curation that makes this a platform that just fuels outrage, that fuels the darker side of people. And one of the arguments I made in that article is here's what works better. Small communities that have weak-tight connections between them. You have lots of small communities online and they have overlapping membership. We know from network theory, really interesting ideas can spread to these network of networks. Really important news will spread to these network of networks. But most of your interaction in this sort of digital vision is going to be with a small number of other people that have a sort of emergent shared sort of community standard. It's much richer, much more personal. That's really what the internet envisioned. Everyone is going to have the possibility to be connected to everyone

else. Not everyone actually needs to to be connected to everyone else. Everyone actually needs to be directly connected to everyone else on the same platform. So I've really been thinking about the folly of global conversation platform as one of the key follies of the sort of 2010s internet. Yeah, I think when we last spoke, you were pretty bearish on the major social media networks because I think it was because you thought TikTok had successfully disrupted everything because they weren't relying on the social graph. So you have Facebook and Twitter that had a kind of first mover advantage

where they got all of us to build out our social networks in this common space. And that was really the, you know, that and some, you know, algorithmic gaming of the system was really the basis of surfacing content. And, you know, as we all know, it privileged outrage and kind of a negatively biased engagement. But what TikTok did is it just never even went in the direction of establishing a social graph. It just used a pure algorithmic surfacing of entertainment. And insofar as the social media platforms have had to emulate TikTok, maybe Twitter is still an exception here, but certainly Facebook or Instagram. Do you still think that the writing is still on the wall for

the major platforms, or do you think they're going to figure out how to still claim the better part of humanity for the rest of our lives? I still feel strong about that hypothesis. I think we see, for various reasons, but we see the dethroning of Twitter as having that same central cultural status it had before. TikTok, we see, for example, like my argument was about TikTok is without this entrenched advantage of my social graph is in there. I've already spent years trying to set up follower networks that I said the connection to TikTok would be very superficial and weak. And we are seeing that. I think last year, for example, there was double-digit drops in TikTok users among the sort of 20, especially the upper 20s

and in the 30s, that sort of demographic, sort of young adult demographics at enough. And they really had no problem leaving because what's actually connecting there, it's a very zeitgeisty platform that people can take or leave. I mean, Instagram is holding it there, but I don't think it has that same, again, centrality that it might've had two or three years ago. And the alternatives, independent media, so podcasting, email newsletters, these really are ascendant in the last year, year and a half since we've talked. And that's the opposite of the centralized platform model because this is independently produced information. People discover these things almost entirely through point-to-point curated trust.

Someone I know forwarded me an email newsletter I signed up. Someone I know told me about this podcast. I started listening to this podcast. They mentioned another podcast. Now I listen to that one. That distributed trust model of curation, as opposed to a centralized algorithmic model, I think really works well. And we're seeing that.

So I remain bearish on the idea of a small number of social platforms that dominate internet culture. Yeah, one of the biggest changes for me, which I didn't anticipate, was that shutting down my Twitter account changed my relationship as a producer of content, as somebody with a fairly large platform. It changed my relationship to my own engagement with current events and the world of ideas and just my audience. It's just changed the time course of everything. So when you're on Twitter, you feel an obligation to react to something that everyone is reacting to, or at least you have to consider whether or not you should, right? So something happens in the news and

everyone is forwarding a specific article or dunking on some response to current events. And you, because it's just implicit, you have the platform, you have the massive audience, you're part of this conversation. What are you going to say about it? And no longer having that outlet, the time course of my response to everything has slowed way down.

And so now I have this podcast, and I podcast more or less once a week. And so I really have a better part of a week to decide whether I should say anything about what just happened, you know, in Ukraine or anywhere else. And, you know, most things, I would say 99% of things don't survive that interval, right? It's just, there's no reason for me to react to the thing that happened four days ago. And, you know, there has been memory hold for almost everyone at this point. And so it's just changed my relationship to information, to the news, to my own sense of just how I needed to think and talk about things. And I really wasn't anticipating that. It just, it was, you that. There's probably something lost there. I mean, there are moments in public conversation where it's probably an advantage to be able to say something immediately and you're part of the first things that are getting said or

something you're contributing to. But I don't know just there's so much more noise than signal there and just the feeling of moving through the day is so different when it's not being punctuated by dozens of interruptions but you know with just to see what was said or or or to decide whether you're going to say something about this next thing that happened. It's just, I mean, honestly, it feels like I've just come out of some kind of decade long flirtation with mental illness. I mean, I just, it's, it's not actually too strong of a way to put it. It's, it's just, it is a profound relief. I mean, it's an, and a humbling, a humbling one really, really. Yeah. Do you find it surprising the number i'm thinking journalists in particular who very much dislike elon musk right so they have a a sort of moral personal ethical commitment to stop using his platform and they'll still talk about i don't like what's happening

on x i don't like elon musk and yet almost none of them have left. I find that interesting. I think, again, I think there's something interesting in that where it would, for a lot of people who are writing like in tech journalism, business journalism, really dislike, clearly dislike Elon Musk, still can't bring themselves to leaving the platform, which again, I think speaks to something interesting about the way the platform plays, especially people with some sort of public profile, the way it plays and how they understand their influence on the world or their impact. But to me, that's been the more interesting observation of the post-Musk period is actually how rare you still are, which is, I thought there'd

be a lot more Sam Harris's, a lot more people saying, yeah, I'm just leaving. People are having a hard time. Yeah. Well, I mean, I do have to recognize that I'm immensely lucky to already have built my platform in the ways that I've built it so that I didn't feel that really I was putting anything in jeopardy by just pulling the plug on my social media presence. I still have a minor presence in the sense that my team puts out stuff on the various platforms. It's just sheer marketing, right? But those were always much smaller accounts. And because everyone knows it's not me, people are much less interested in it. So those are just maintained in a perfunctory way. But I think most people who are still building their reputations as writers or journalists, or certainly people in politics, feel that they just can't forsake the opportunity

to build an audience there. And they certainly can't pull the plug on a large audience already built if they're busy whittling away on their various projects, and I just see no other way to effectively market them. I mean, I just think everyone's been captured by it. And what's more, there is just this sense that if you're not there, you don't know what's actually happening as soon as you need to know it, especially if you're a journalist. And I mean, the thing is that it's so distorting of priorities and of real information. I mean, I see so many people in the podcast space and in the alternative media space pushed around by misinformation and conspiracy thinking. And even when they're occasionally right about something, I mean,, there's a conspiracy theory that really turns out to be true.

It's just so everyone's priorities are so upside down. And there's just this, what it has engineered for, this is now kind of outside of mainstream channels. I mean, this wouldn't be true of the New Yorker where you write, but it's just out in what I call podcastistan and substakistan. out in what I call podcastistan and substakistan, it has created this new religion of anti-establishment thinking, where it's just the alternative explanation of everything is the thing that we're now going to spend 90% of our time talking about. And it's just so often wrong and misleading and deranging that, I mean, it really, it has made me increasingly worried that we have, you know, politically, you know, certainly in the aftermath of COVID, rendered ourselves almost ungovernable in how we talk about, you know, or attempt to have a conversation about what used to be the world of facts. Yeah. Well, I mean, I think this is one of the more engaging human psychological experiences

is this idea of most people were thinking this, but then me and my group figured out that that is true, right? That inversion, the inversion of the whatever, the empiricism structure is incredibly engaging. And it occurs every once in a while in reality. Like everyone was thinking this, and then we, whatever, DNA is a double helix. It's amazing. Online culture, especially algorithmic-driven online culture, has given a way to basically commodify that and spread that.

We can create, you can build an entire epistemology around everyone thinks this is true, but it's really that. Everyone thinks this is bad for you, it's good. Everyone thinks like this about this disease, but it's that. Everyone thinks that. And you can build an entire epistemology around that. Your entire world can be that, and there can be a whole audience that's just going to reward that. The algorithm is going to reward that. So I have definitely seen that as well. I mean, there's a well-known effect among professors called the sort of academic in exile or academic in the wilds effect, which is if you take an academic and then they leave academia, they go independent. Eight times out of 10, they go to some really conspiratorial

places. And partially what's going on here is, well, first of all, they're smart. So it completely makes sense to them that I could figure something out that other people didn't understand because I'm very smart. But one of the purposes and services academia plays is there's this checking mechanism. Everyone else is smart too. And so when you're like, hey, I think, look, here's this whole new way of seeing it. The earth is hollow. You have all these other smart people being like, here's why you're dumb. And they take you down, right? But when you leave, you have this academic in exile.

And this is sort of like Linus Pauling with vitamin megadosing, right? It's much, much higher rate now in the age of social media. Because now when you leave, you can immediately algorithmically have constructed an audience that cheers you on. And so now I think the severity of academic in exile effect is much more pronounced and much more ubiquitous than it used to be. That when you sort of leave academia to start your podcast, it's not too long until there's world-changing conspiracies that you're uncovering. And it could be medical and it could be governmental and it doesn't matter. And so I think that effect is like one of the more interesting effects that's been happening is that you can get a cheering section and the

algorithmically constructed cheering section of people that you're being rewarded for saying, I think this is the way it really happens. And you see this all the time. I think I like podcast to stand as a term, this idea of there can be a hundred studies saying something, but if there's one study saying something different, the way you perceive that is, well, everyone knows now that thing's not true. It's this interesting sort of sampling of evidence, this sort of destabilization of Bayesian priors that is amplified and supported in sort of the world of algorithmically disseminated information. Yeah, that's really interesting. Yeah, this is a, you just described an effect that I've referred to, I believe previously, as watching people get radicalized

by their own audience, right? I mean, that cheering section has the effect of people notice the signal in their own audience, and then they begin to cater to that signal. And then there's just this ratchet effect where it just gets, you know, crazier and crazier, and they begin to cater to that signal. And then there's just this ratchet effect where it just gets crazier and crazier, and there's more and more sunk cost reputationally for having been the guy who was sure that there's so many examples of this in the midst of COVID that focus on vaccines and medical conspiracies, et cetera. You go all in and then you would have to completely repudiate how you spent the last 12 months if you were going to have a second thought and anyone's going to talk any sense into you. So there's one thing that reliably confuses people here

around the norms of our online conversation. And it's the analogy of Twitter being the so-called digital town square and this notion that a commitment to free speech should more or less bar the door to any kind of real moderation policy, right? Like what you want is a total free-for-all where the best idea wins and sunlight is the best disinfectant. So we should be able to entertain any notion at whatever scale for however long in proximity to any other world events and any effort to put your thumb on the scale to deplatform Alex Jones or to try to clean up a digital sewer that's introducing bias by definition and worse, it's actually just a repudiation of free speech in the constitutional sense, repudiation of, you know, free speech in the constitutional sense. And it's forsaking the best error correcting mechanisms we have, which are just let everything suffer collision with

everything else and see what wins, right? And so the, you know, people never, when they're championing this commitment to something like free speech absolutism, they never take a moment to recognize that there are places online that are much closer to the absolute than Twitter ever was, and no one wants to be there. I mean, places like 4chan and 8chan, I mean, that's where you really get your absolutes, right? Where you can just, you know, I mean, everything up to child pornography might populate your feed. But there's also just this point that is also overlooked, which you just referenced, which is the algorithmically boosted aspect of the speech, which changes the nature of what speech is online. So perhaps you could just give me your thoughts on how you view this tension between our commitment to free speech, our commitment to leveraging the wisdom of the crowd insofar as it exists,

and to correcting errors at scale, but this need to not suffer the 4chanification of everything in our digital lives. Yeah. Well, I think the town square, it's a town square analogy that's causing the problem here, right? I mean, the concept of a town square, the sort of central gathering place where people can democratically discuss depends on scale being reasonable, right? I mean, we call it the town square.

We don't call it the city or the state square, right? Because it's a place where the demos in Athens, we sort of a relatively constrained group of people who all know each other and have other ties to each other. You have other social trust ties to each other. We live in the same town. I run the hardware store that you come to to buy your nails. Them to come together, there's this free speech notion of, well, we don't want to

buy fiat in advance, say here are topics that are off limits because how are we going to work together to advance what we understand? Twitter is not a town square, right? When you have 500 million users, that's not a town square, it's an entertainment product. We have 500 million users who are inputting lots of different possible bits of content that could be interesting. We're going to run them through this cybernetic curation algorithms this is what i mean by that is there's algorithms involved but it's also the expansion properties of the underlying follower graph means that individual decisions to retweet or not retweet so these are human decisions interacting with these digital networks can create these cascades of information spreading that's a lot about how trends arise it's a really powerful actual curation mechanism. It's unlike TikTok, which is purely algorithmic. On Twitter, it's cybernetic.

And so you have these digital networks with good expansion properties and 100 million people making individual decisions whether or not to click, retweet or not, whether to quote tweet or not, which is a whole interesting sort of computer science question. All of this aimed towards how can we take this giant pool of potential content and choose the sort of small number of streams of content that are going to be relatively globalized or interesting and engaging. That's not a town square. It's an entertainment product.

It's why in a New Yorker piece I wrote right after Musk took over Twitter, as I said, it's not the town square. It's much more the Coliseum. That's much more the better idea. It's tons of people watching carefully curated entertainment. In that context, of course, you have all sorts of thumbs on the scale. The whole point is we're trying to put on this show. And I think of the trending topics of the day as the show on the Coliseum floor with all the huge crowds just watching and chiming in to see the blood sport between, hey, Sam today is having a war with whoever, right?

This is the entertainment for today. It's an entertainment product. Of course, the thumb is on the scale because you're trying to find something that just pushes the buttons right. Maybe there's some outrage, but not too much. Maybe it's absurd, but not in a sort of 8chan, completely over the top-top, Lulz-type absurd. You're trying to program a television station. You're trying to program entertainment in a coliseum. It's not a town square. Now, if you have actual digital town squares, here's a place where a

small number of people who have other ties to each other are gathering to think things through and talk things through. We've seen examples of those can have a wide variety of different community standards, including standards where almost anything's going to go on this discussion group, but it works because we're all whatever, lumberjacks from this part of the country, and we sort of have other ties to each other. And so I think it's that town square metaphor that threw us off, is we took this entertainment product and somehow tried to make it seem like this was the Roman Senate. This is where just this reasonable scaled group of people were getting together to hash things out, and that's never what they were actually trying to do there.

It seems reasonable to have made this mistake, though. The structure you're positing, like a network of networks online, that at least is implied on Twitter because you have the people you're following and you have the people you're following and you have the people who are following you. And that's not all of Twitter, right? It's just, you're just tending to see what you're following and everyone sees, you know, everyone who's following you sees what you react to. And that's just, that's its own little space. Why is that so easily corrupted by being in contact with the rest of the ocean of information? Well, what ends up happening on Twitter is that more local interactions just get swamped out by the ultra-amplified content, right? And increasingly their feed is driven by this. So

there's some stuff in there from people you straight follow, but the feed is algorithmically sorted. And one of the major criteria on which things follow, but the feed is algorithmically sorted. And one of the major criteria on which things are sorted for your feed is their engagement across the network. So really what's happened is it's the content that has really gained this big boosting effect, this sort of cascade of retweets leading to retweets. That's what's being programmed for. And there's some conceptual regionalization. So if you follow a lot of a certain type of people, you might be seeing what's really being amplified in that subgroup. That's true. There's some of that going on as well. But it's a really large scale at which a lot of this

is happening. And especially when it comes to the most town-squary piece of this, which is discussions of politics, discussions of policy, discussions of world events, the stuff we think of as the grist of civic discussion, those are incredibly large subnetworks in which information is spreading. And that's where you really have the Coliseum effect. It's people competing to get their turn on the Coliseum floor. They have their trident ready. And that's like that most civic-minded aspect that we associate with Twitter, I think is the mostiseum floor. They have their trident ready. And that's like that most civic-minded aspect that we associate with Twitter, I think is the most entertainment-centric. Yeah. And the most corrupting of our conversation about important topics, because one of the thumbs on the scale here is outrage. And outrage is a word we keep using in

this context, and it seems to have been, at least in my hearing, it doesn't quite convey the attitude that one sees so often online, which is, it really is kind of in-group sanctimony and out-group to your in-group, it's a simulacrum of conversation. Sometimes someone's responding to somebody else, but it's almost always a bad faith response. It's a response that is meant to be enjoyed by the in-group that despises the target of the remark in the out-group. It's so obviously driving us apart at the level of society. Again, not when you're talking about how beautiful a full solar eclipse is, but, you know, when you're talking about politics or anything that is polarizing. Yeah. No. And I'm with you on this, right? It does that. It does that. And you're auditioning, you're auditioning when you comment on someone's tweet. You're auditioning for the algorithm. There's this sort of cybernetic amplification effect.

So everyone tries to one-up each other. I mean, I hear a lot from people, what they're worried about mainly is not the contempt from the other side, but that the in-group policing, I think, has had a massive impact. You see it in journalism. You see it in academia. You see it in sort of theoretical frameworks. You certainly see it to some degree in politics, though it in academia. You see it in theoretical frameworks. You certainly see it to some degree in politics, though it's interesting. Politicians, they're so used to that. It's almost as if they're the one group that at least understands the social dynamics of

something like Twitter. This is their lives, is in-group policing, out-group contempt, being okay with these people are upset, who am I going to hitch my wagon to, putting their finger to the wind. But for most other people aren't used to that. And so it's definitely an effect that makes you either cower or makes you conform. I only get some taste of this when I'm doing book tours, because I'm not on social media, so I'm not subject to people talking about me in these sort of contexts. When you have a book out, people do talk, you get reviews and people come out to talk about your book or whatever. And I hate it. And I couldn't imagine if that was just all the time. If all the time that was the world I was in is every week I have to get the two or

three people that are taking their swing at me or whatever. I mean, that would drastically affect, I'm sure, what I write about, how I went through my life, just the subjective well-being. I was really hoping for Elon to destabilize Twitter so much that it essentially collapsed. It would actually be a great civic duty that he would have done. But it seems to be holding on to some degree, at least as far as I can tell, which is, I think, unfortunate. Yeah, well, he's destabilized something, and it's been his own brain. But yeah, it's just, he really is a cautionary tale at this point. And that has always been my concern about his

engagement with Twitter, not so much what he was going to do to the platform. For the longest time, I remained agnostic as to whether or not he could actually significantly improve it. It doesn't seem likely to me now, but I'm productive people in any generation, it hasn't been good. Let's turn to your book because it's really, I mean, you've written a series of books that have targeted the same kind of object here, which is a life well-lived, right? I mean, the question is like, how do we answer the question, what is life good for, right? I mean, the people, especially when you get to a certain level of privilege and abundance and just sheer good luck, and this is almost by definition, much of our audience, you know, for a podcast like this or for a book like yours, when we're talking about people who have the time to think about how to improve their lives and how to live more wisely and get to a place where they more and more are not

regretting how they use their time. I mean, that does suggest at least a few degrees of freedom there in the kinds of choices they make. You know, presumably, if you're listening to this podcast, you're not digging a ditch in the sun under the lash of some tyrant, right? So you seem to be at least implicitly and rather often explicitly asking these types of questions, you know, just like, what is the point of all of this? What does winning the game actually look like? And in this most recent book, you're talking about a new approach to productivity, which you say is a lost art. So you're suggesting that we were once much better at this. Let's just start with your basic concept.

What do you mean by slow productivity and how have we lost touch with it? Well, I agree with your characterization of the questions I think about. I would add something else to it, which is as a computer scientist, as a digital theorist, I care in particular how technology intersects with that story as well. So in most of my writing of the last decade, there's usually an unintended consequence of a technological development that gets us out of touch or becomes an obstacle to living some life that's going to be deeper, more meaningful. And we have to grapple with that and understand that technology, the opportunities, the perils, and navigate around it. So even this book, Slow Productivity, the problem that I'm solving, there's actually a techno story behind it. So even this book, Slow Productivity, the problem that I'm solving, there's actually a

techno story behind it. So there's an easier way of summarizing it, which is, look, there's a key question that a lot of people are in, mainly, as you say, this sort of knowledge work world. These are people who are doing pretty well. You have a job in which you look at a computer screen and you're an air conditioner. So a lucky place to be. But that group of people, and these are the people, these are a big group of my readers. A big question a lot of them have is, okay, how do I do my work well? How do I produce things I'm proud of, have impact, support my family, and yet not let work just take over all of my life? How do I avoid sort of falling into burnout?

I don't want to be like pre-Twitter Elon Musk and just don't sleep and have seven businesses and just get after it. How do I still do stuff I'm proud of, but also spend time with my kids? There's this big question. And the book looks at that question from both the perspective of someone like creatives that have a huge amount of autonomy, and also from the perspective of sort of a standard office worker who has less autonomy, how can they still navigate that knife's edge? But there's a techno story behind how we got to a place where that question became more and more relevant. And the story that I'm trying to tell in the first part of the book is knowledge work itself,

when that emerged as a major sector, which is really like mid-20th century, had this issue of not really knowing how to define productivity. Because we had industrial productivity was a quantitative concept. It's a ratio. It's model T's per paid labor hour. Agricultural productivity is a quantitative idea. It's bushels of corn per acre of land. You could measure this. Industrial manufacturing, agriculture, you had well-defined production systems. So you could tweak something very specific and see how it impacted that number. Knowledge work comes along under that works. Knowledge work is more haphazard and autonomous and ambiguous. I might be working on seven things that are different than the eight things you're working on. There's not one thing we're producing. There's no well-defined production

systems we use for our work as well. Organizing labor is very independent and individualized in knowledge work. And so in response to that, the knowledge sector came up with this idea of we will use visible activity as a proxy for you doing something useful. So we'll all gather in the same building like we would a factory. We'll work factory shift hours. And if I see you here doing stuff, I'm assuming that's useful stuff. And if we need to be more productive,

come early, stay late, right? I call that pseudo productivity. The techno story is that worked okay. Not great, but worked okay until the front office IT revolution of the late 90s and early 2000s. And then once we threw network computers and then later mobile computing into the sort of office work sphere, pseudo productivity spun off the rails, right? Because the personal computer came in and now suddenly the amount of different things you could work on quadrupled. No longer

do we have specialists to type and specialists to handle communication. Like the amount of work you could do quadrupled. Low friction communication networks made it really easy to ask people to do things. So workload skyrocketed. Email, chat really changed the game when it came to demonstrating visible effort. Now you could be doing this in incredible fine granularity at a frenetic pace. How quickly I respond to a message might be really important signal in trying to show how pseudo productiveproductive I actually am. So my argument was the front office IT revolution plus this older idea of pseudo-productivity, they didn't mix. And it led to this increasing exhaustion of knowledge workers as the amount of stuff they're working on increased, the amount of their day dedicated to talking about work

instead of actually doing work increased, the freneticism and speed of their work increased. At the same time, they were getting more nihilistic, like, what am I actually doing here? I'm just doing all these visible signs of productivity. I'm sending emails, I'm in meetings, but I'm not actually writing the marketing report. I'm not actually programming the computer.

And it led to the burnout epidemic. And so there's that underlying techno story of technology plus that crude metric didn't work well. So we have to reassess what does it mean to produce really good stuff? Can we do that in a way that doesn't make work really exhausting? So I have that sort of personal angle. And then there's also this sort of deeper techno-social economic story. And they're both circling, I think, the same issues. Well, what did COVID do to this picture? I mean, there's this profound change. I mean, again, we're talking about knowledge workers almost by definition here, and perhaps you should bound that concept for us a little more.

But the rise of remote work in the aftermath of COVID and the seeming durability of our commitment to that, I mean, there's just, I guess, many organizations are still struggling with just how to get the balance right, but there does seem to be this hybrid level of commitment to remote and in-office work for many organizations. level of commitment to remote and in-office work for many organizations. And there are upsides and downsides to that, but it does change this, at least the optics of pseudo-productivity. I mean, if you're not condemning people to have to be at their desk for 40 hours a week, whether that's the best use of their time or not, because so much of their time is now remote and you're not actually, you know, they don't get the credit for being at their desk because they're, you know, there is no desk to be at much of the time. And then there's this phenomenon of, you know,

the quiet quitting that has been much discussed. How do you view the, what recent years, you know, during and post COVID have done to this conversation? I think the beginning of COVID pushed this increasing issue people were having with the unsustainability of pseudo-productivity. It pushed it over the edge. Because a couple of things happened when knowledge workers had to go remote right away. When we were shifting remote, we were already, for the most part,

at our max capacity for the amount of work that we could have on our plate at the same time and have any chance of not drowning. And the reason why we're our max capacity for the amount of work that we could have on our plate at the same time and have any chance of not drowning. And the reason why we're at max capacity is because in knowledge work, we leave workload management up to the individual. For the most part, that's up to you to figure out how to manage what you're doing and what you say yes to. There's a lot of autonomy and ambiguity in knowledge work. So how a lot of people began to manage their workloads is they would wait until the stress of their workload got high enough that it outweighed their concern about the negative social cost of saying no to new work.

This became the primary governor mechanism by which so many knowledge workers managed their workloads. So of course, this keeps you at a state of having a stressful, stressfully large amount of work. If you have to be stressed before you begin to say no, everyone has a stressful amount of work. Then the pandemic hit, which automatically gave us like 25% more tasks overnight because we had to adjust unexpectedly to, oh, we got to run our company. You had to wipe down your groceries. Yeah. And just work itself. How do we deliver our services? I remember this going on at the New Yorker. How do we move our whole production process to a digital pipeline? It was just new work, came out of nowhere. The collaboration then also became less efficient because we lost all of the,

oh, I see your office door is open. So I'll poke my head in and be like, hey, what are we going to do about this client? And it takes two minutes. Instead, we had to start scheduling Zoom meetings. But the smallest granularity of these meetings was a half hour because it's hard to drag anything smaller on your calendar. And so now we were making the collaboration, the overhead related to work, that became a lot less efficient. And then finally, to compensate for the fact that I can't see you doing visible activity, we just moved this over to being even more frenetic with digital communication. It really now is important for me not to reply quickly. I have to reply very

quickly to Slack because this is maybe the only way I have right now to demonstrate that I'm being pseudo-productive. So all these things happened overnight and people just said enough is enough. And I actually argue, this is a piece I wrote a couple months ago, I argued that many of these sort of spasmodic, emergent grassroots revolution reform movements and work that we saw throughout the pandemic period were in part people responding in a primal way to this, I've been pushed over the edge with what's going on in knowledge work. So I think the knowledge work component of the great resignation was a response, the people saying enough is enough. I think quiet quitting was a response for the younger

generation who couldn't resign or switch down the half hours and move to a cabin. So quiet quitting was a response. I think much of the fury around the remote work wars that really picked up steam in 2021 and 2022 was also a sort of misguided response to this deeper primal rejection of work has just become sort of intolerably frenetic and overloaded. And I'm getting actually almost no real work done. Objectively, the remote work wars didn't make a ton of sense, right? You had this thing that did not exist 16 months earlier, and now you had worker groups talking about it like it was a Geneva Convention. It was this fundamental right that, of course, work is supposed to happen at home. How could we ever take this away? This didn't even exist 16 months earlier.

I think part of that was just a generalized zeal for reform. Because when we took this already exhausting tempo and this nihilism of all we do is talk about work and rarely get work done, when we pushed that over the edge in the pandemic, it broke a lot of people. And a lot of the unrest we saw in the knowledge work sector throughout the pandemic, I think, was people just responding to enough is enough, but they didn't really know exactly what they were responding to. And I think a lot of those efforts were sort of misguided energy. And we missed a lot of the opportunities we had to really make better reform here. That's the context in which I was thinking about slow productivity. Well, let's talk about the principles of achieving slow productivity. What is signified by the phrase, and you frame your discussion around many interesting case studies, the main being John McPhee, but you talk about Benjamin Franklin and Jane Austen and a bunch of scientists. And it does suggest, I mean, this is really your thesis,

you talk about the ways in which our engagement with new information technology has deranged our sense of what it is to be productive and how we measure success. And so if you go far enough back in time, it's not a surprise that you see examples of people who didn't have this technology, who were succeeding by the lights of history in spectacular ways at a very different cadence with respect to how they worked. You know, feel free to bring up any of the principal case studies you want, but we should talk about your three stages here. Do fewer things, work at a natural pace, and obsess over quality. Yeah. I mean, because it was a big decision. But the reason I chose to use as the primary case studies these sort of historical figures, there's really two aspects to that that I think is important to sort of set the stage. One, I was wary of the uncanny valley effect. I've seen this

a lot when talking about sort of contemporary work. There's an uncanny valley effect. I've seen this a lot when talking about contemporary work. There's an uncanny valley effect. If you say, look, I'm going to tell you about a company that exists right now that's doing things differently, or a specific employee at a marketing company, and here's how they do things differently. Their job is so similar to yours that the differences really begin to matter. And people have a hard time getting past like, oh, but that's a client service firm and our client, we have a timesheet firm. And it's actually, I found that it's difficult for people to get past that uncanny valley. It's too close. If it's too close to what they do, but not exactly what they do, it becomes an unbridgeable or disorienting gap. So I said, why don't I look at what I call traditional knowledge workers

who are actually defined by, like this could be the critique, but I'm twisting the critique to be a benefit. They're defined by all the freedom and autonomy they had to experiment with what's the best way to create value using my brain. I said, this is why these people are important because they had all the freedom in the world to figure out what works. So if we look at what they settled on, they're probably uncovering some useful universal principles about the best way of creating valuable things using the human brain. Now, what we could then do is once we isolate those principles, I can do the hard work of, okay, so how can we make that relevant to someone who works in a cubicle? How can we make that relevant to an entrepreneur in 2024? Yeah, there's a lot

of work then to translate those principles to tactical things that make sense to people today. But I thought that was the right way to do it. So those three principles you mentioned were the three big things that came up if you study historically people who were good with creating valuable things with their brain. They didn't work on too many things at the same time. They really avoided overload. Their pace was varied, same time. They really avoided overload. Their pace was varied, hard periods, less hard periods. Also, they would measure productivity on very large timescales. So many of the most productive people in history, if you go back and look at a random month in their life, they seem incredibly nonproductive, right? Because they didn't think about productivity in terms of like today needs to be productive. They thought about it like the next 10 years, I want to produce something that matters. And then finally, they cared a lot about craft.

That was a sort of antidote to the appeal of busyness was to instead reorient their interest towards, I want to do something really well and I want to keep better at what I'm doing. All three of those principles, I argue, can be first adapted to modern knowledge workers with a lot of freedom and then can be further adapted even to knowledge workers who are in a situation where they have less freedom. We can get ideas from there that transmute into interesting, tangible advice for people in various situations in our current moment. The purest case is the person who really is his or her own boss and can just

decide to create whatever they want and then the analogy to the historical people. If you'd like to continue listening to this conversation, you'll need to subscribe at samharris.org. Once you do, you'll get access to all full-length episodes of the Making Sense podcast. The podcast is available to everyone through our scholarship program, so if you can't afford a subscription, please request a free account on the website. The Making Sense podcast is ad-free and relies entirely on listener support, and you can subscribe now at SamHarris.org.