Would a World Without Algorithms Be Better? — With Kyle Chayka

Kyle Chayka is a New Yorker staff writer and author of FILTERWORLD: How Algorithms Flattened Culture. Chayka joins Big Technology Podcast to talk about his book — which debuts this week — and dig into whether algorithms really do make our culture flatter. In this spirited conversation, we interrogate the role of algorithms in society, ask how they reflect in the real world, and ponder how products would be redesigned to take back control. Stay tuned for the second half, where we discuss Chayka's story on people falling in love with AI bots. --- Enjoying Big Technology Podcast? Please rate us five stars ⭐⭐⭐⭐⭐ in your podcast app of choice. For weekly updates on the show, sign up for the pod newsletter on LinkedIn: https://www.linkedin.com/newsletters/6901970121829801984/ Questions? Feedback? Write to: [email protected] Learn more about your ad choices. Visit megaphone.fm/adchoices

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  Let's talk about how algorithms are flattening culture and whether there's a better way to solve the problem with a New Yorker writer whose new book on the subject comes out this week. All that and more coming up right after this. This episode is brought to you by Genesis. What does it actually take to put a Gentic AI to work across an entire enterprise? I recently spoke with Genesis chairman and CEO Tony Bates about why orchestration is emerging as a competitive advantage in customer experience and what companies need to get right in the AI era. Then I sat down with Adam Mitchell, head of enterprise business solutions at Voya Financial, to go inside a large scale agentic CX transformation, including the business decisions, trade offs, and lessons along the way.

• 0:45Speaker 00

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• 1:22Speaker 00

  Welcome to Big Technology Podcast, a show for cool-headed, nuanced conversation of the tech world and beyond. This week, we're joined by Kyle Chayka. He is a staff writer at The New Yorker, covers technology and culture on the internet. He's also the author of a new book called Filter World: How Algorithms Flattened Culture, coming out this week. Kyle, welcome to the show. Thanks for having me. Thanks for being here. Been a reader of your work for, I can't even remember, I mean, must be more than a decade at this point. I've always found you to be an extremely astute observer of what's going on online and more and more about how that reflects offline. So we're going to talk about all of that this week. And why don't we begin with, I mean, you're writing a story or a book about algorithms

• 2:07Speaker 00

  and how they filter our world. I mean, obviously, at this point, you're kind of throwing your hands up and being like, we don't like what the algorithms are doing. What's your criticism of algorithms?

• 2:21Speaker 01

  Well, I think, I mean, to begin with, I do think algorithms have been necessary for the internet as it exists at this point. Like, since the advent of social media, social networks have gotten bigger and bigger. We produce more and more content, like users generate content at an extremely fast pace, extremely high volumes. So you need some way of sorting it. You need a mechanism to figure out what you might actually want to see and sort that out from what you just don't care about or what you could easily miss. But I think at this point, we're facing this inflection point in social media and

• 3:01Speaker 01

  on the internet in general, where it's harder to, like, be outside of the algorithmic feed than it is to be within it. So these, these feeds and recommendations have just taken over so much of our experience online that I think that's kind of choking new experiences and making it harder to, like, find new or original or creative stuff.

• 3:26Speaker 00

  Okay, so let's just get into it because I have some counterpoints I want to bring up to you. First of all, like, it's definitely true that we're moving more towards algorithm and less toward human signal, right? We're going from a place where, like, we are not in the follow model anymore as much as we are the algorithm recommending. This is specifically for content, right? So it's less about who you design to follow on Facebook or Twitter and more about what TikTok shows you. But that being said, these algorithms do, like, they are designed to find new stuff that you might be interested in. The TikTok algorithm, for instance, looks for things that, you know, of course, that you have watched and you're more likely to watch and stay with. But also, every now and again, it will feed

• 4:09Speaker 00

  in a video of some interest that it's not sure whether or like you will want and see how you respond. And if you do like it, then it will send more. And that's how you end up in different rabbit holes. So there's an argument to be made here that algorithms actually do expose you to lots of new stuff you might not have otherwise. I'm sure you thought about this when you wrote the book. What's your, what's your take on that?

• 4:31Speaker 01

  I think they they do highlight new stuff. Otherwise, they wouldn't work at all. Right? Like, you don't just want the same thing over and over and over again. There's a variable in there, whether it's Spotify or X or TikTok. That's maybe marked surprise or a difference.

• 4:49Speaker 00

  I'm sure that's actually how it's labeled.

• 4:51Speaker 01

  Yes, let's twist the surprise knob a little more. And that would be like an experience of randomness, right? The TikTok for you, if he doesn't know if you're going to like this new video of a dog doing something funny, but you probably will. So it feeds that to you, sees if you engage, then delivers more if you do engage with it, delivers less if you don't. So I think it it's nice as like a discovery engine in some ways. But I think the overall effect. I mean, on on one level, I think there's not enough surprise, like the surprise knob is not turned up enough. And we have no way of turning it up ourselves. I can't tell TikTok to give me weirder stuff directly.

• 5:35Speaker 01

  I can't shake Instagram's idea that I only want to see cheap European property. And so I'm kind of stuck in these like reflections of my own desires that I actually.

• 5:47Speaker 00

  That's your Instagram feed?

• 5:48Speaker 01

  Oh, yes. Yeah, like every every Italian stone village I'm seeing.

• 5:55Speaker 01

  That's that's the view into my subconscious. So I suppose.

• 6:01Speaker 01

  Like, algorithms absolutely deliver us new things. I think they desensitize us from like following those leads once we do find something new. Because we just expect that there's another new thing around the corner, another new thing. And I wish there was a way to talk back a bit more.

• 6:16Speaker 00

  But we do talk back, though, in in many ways. Like, if we hover on a video on TikTok, we're sending that signal. And in fact, like you

• 6:23Speaker 01

  Passive signal.

• 6:25Speaker 00

  Oh, I would disagree. I think it could be active, right? Like, I think the experience of using a TikTok right now is like, you almost are aware of how the algorithm is interpreting. So like, if you don't want to be recommended stuff as opposed to, first of all, I think you can say, show me less. But also, if you want to see more, you know, at this point to hover. And maybe I'm giving it too much credit, but you know to hover on that video. And so you'll get more of it. But maybe I feel like exaggerating what's

• 6:54Speaker 01

  The extremely online power users are more aware of how the algorithm works and how to like tune the algorithmic feed to what they want. So to talk back in that way of sending signals.

• 7:05Speaker 00

  Yeah.

• 7:05Speaker 01

  But I worry that kind of the mainstream user or the person who is not so aware of the influence of an algorithmic recommendation, just kind of like stays within that, that feed that's just still recommending kind of more content that may be engaging, but it's not ultimately leading you to more interesting places.

• 7:28Speaker 00

  So are you basically saying that the algorithms are not working the way that they are designed to? Because let's just talk about it, right? Like, it shows you that surprise to see if you're interested. So like, for instance, if I ended up with a TikTok video of property in Italy, that would be a surprise for me. But if I like sent signal, sent TikTok the signals, which I don't even have to think about, right? If I watched that video through, then it would send me more. So it sort of automatically follows those leads for you.

• 7:57Speaker 01

  Yeah, it's the sense of like surveillance, like you are communicating through your actions, what you're interested in or not.

• 8:05Speaker 00

  I mean, if the algorithms work the right way, yeah, for sure.

• 8:08Speaker 01

  Yeah. And like, I mean, I use TikTok a lot. I feel like I have that sense of how it reads your subconscious almost and directs you down these various rabbit holes. But I think, I mean,

• 8:23Speaker 01

  That model of surveillance and the passivity of those signals. I don't know. I don't think that ultimately is the only way we need to interact with culture. Like, I think.

• 8:36Speaker 00

  Yeah.

• 8:37Speaker 01

  I would like be, I would like there to be something more beyond the passive signals. To have people seek things out more, to have people even be able to follow artists more closely. I mean, I think another consequence of these feeds is that you might watch a musician's TikTok video for a while because you're interested in it and you might get more. But you kind of expect it to come back to you without you having to try at all. So it builds these kind of passive consumption habits. And that's like, I think it's kind of unhealthy for us, even though it's entertaining and hypnotizing. But it's really unhealthy for the artists who are not making as much money, who are not getting as much attention as they might.

• 9:19Speaker 01

  If they had a more direct audience that wasn't so mediated.

• 9:23Speaker 00

  That is, that is absolutely true. So we do now end up, instead of following, you know, a single artist that we love. We can follow a genre, like actually yesterday, one of my surprise box on Instagram, I got this guy like, you know, banking these pipes and making beautiful music of it. And I, I actually had a moment where I was like, should I follow this person? And then I was like, no, but I think that, you know, Instagram probably knows I played it like 60 times. Cause I'm like writing and I have this like bing, bing, bing, you know, just like music going on in the background. I'm like, they're gonna bring it back, but I don't have any incentive to follow the artist. And that's true that we now end up in a much more, you know, amorphous area of interest as opposed to much more intentional. And that does change things.

• 10:05Speaker 01

  There's like an ambient consumption of stuff that you're interested in rather than like a super engaged. Like in Spotify particularly, I think they talk a lot about lean in versus lean out consumption. Like lean in consumption being when you're truly paying attention, when you're actually like listening to the song that's in your ears and thinking about it. And that's leaning in, being, being attentive. And then there's lean out consumption, which is just letting stuff play, experiencing it ambiently.

• 10:36Speaker 01

  Putting it in the background essentially. And I worry that all of these algorithmic feeds kind of lead to more lean out consumption than they do lean in consumption. So you have this pipe banging guy and you're like, oh, cool. I like a little bit of this. I like to hear it. So if I listen to it, it's going to come back to me, you know, like a piece of driftwood on the tide or something. I'm not going to take that next step to follow the guy. You're not buying his album of pipe banging.

• 11:06Speaker 00

  Well, I did. I did share him on my WhatsApp channel. His name is Jake Chapman. His, uh, his, uh, handle is Chappy Mike, Chappy Milkshake. So if anybody's interested in what I'm hearing, it's actually terrific music. So maybe I will follow after this, but you're right. We don't, we're not in the moment where we are following this stuff intentionally. And that leads to like a sort of a dissociation between our interests and the stuff that we follow. But, okay, I think that this is kind of clear, like how this conversation was going to go. But for the sake of argument, I'll stand on the side of, of the algorithms and we'll let you, you know, stand on the side of algorithms are maybe not all they're cracked up to be. From that vantage point, I would say that maybe, uh, uh, they really do work in pointing

• 11:50Speaker 00

  us to the stuff that, that they, they've basically, what they do, and I think you've mentioned this, is they kind of strip out like a lot of the middle class of content creation and they point us to a much smaller amount of, of stuff that is really well liked. And the argument that would, I would make on the behalf of the argument, uh, on behalf of the algorithms is that a lot of that middle class was actually really dull and uninteresting. And I'm not talking about professional content creators, but I'm just saying like, let's take the Facebook news feed, right? So the Facebook news feed, most of the stuff posted within it is, is pretty boring and not engaging. And what it does is it takes all these posts from these thousands of different inputs

• 12:32Speaker 00

  and shows you, you know, maybe here, these are the three or four, like really interesting things that you will engage with, you, you will learn from, you will find interesting. Now, of course, there's been problems with that because it's pointed you to the things that will most outrage you and most make you want to, you know, overthrow a government or whatever. But they, but, but, but when it works the way it's intended, it actually sifts through like so much of the boring, dull stuff and actually gets you to interesting things. And as a consumer, that's maybe something to celebrate.

• 13:00Speaker 01

  For sure. I mean, in the Facebook case, Facebook made this decision to collect all kinds of content into its feed, right? It's it's not just friends and family, it's articles, it's videos, it's random meme group page content. So they piled everything into one platform. And because you have all that different kinds of content, because you have such a high volume of it, suddenly need to sort it in a much more aggressive way.

• 13:29Speaker 01

  So in that context, the algorithmic feed really works because it's giving you the stuff that other people engaged with, that other people commented on. But I think it's also possible that maybe we just didn't need that fire hose of everything at once to begin with. Like, I think

• 13:48Speaker 01

  you really need that filtering and that sorting when you have an undifferentiated mass of all kinds of stuff. And you need to like pick through it because it's not all very high quality. It's a lot of mediocrity.

• 14:01Speaker 01

  If you rewind to like a bygone era of, say, Facebook in 2011 or Instagram in 2013 or something, you didn't need so much sorting because it really was just the people who you were in direct contact with. You were following a much smaller number of people. The feeds felt quieter in a way.

• 14:22Speaker 01

  So I think the algorithmic, the rise of algorithmic recommendations has followed this expansion of of digital platforms into all types of content. And I kind of have a desire to go back to that earlier stage where maybe we didn't need so much sorting because things were more built for a specific purpose and stuck to that purpose rather than like every platform doing everything at once.

• 14:45Speaker 00

  Yeah, this was a debate that I had with Frances Haugen, the whistleblower at Facebook, who like didn't really like the interpretation of one of the papers that I had, I guess, found in her document dump. I didn't like my interpretation, which was that if you took the Facebook did this study and found that if you took the newsfeed algorithm out and just did reverse chronological stuff, you had much more spam and content that people didn't like, and it's just a disaster, and therefore we need the algorithm. And what she was like, and I think this is like a pretty good point in retrospect, which is that if you take the algorithm out, you're not just left with the experience of the platform absent the algorithm. You're left with the platform that needs design changes to make it.

• 15:27Speaker 00

  So that you could use it and enjoy it without this recommendation algorithm. And what my argument did was leave out the fact that like Facebook would then make changes to its platform, potentially good changes that leave it less reliant on the algorithm and more encouraging, maybe like you said, smaller communities as opposed to this big fire hose.

• 15:48Speaker 01

  Yeah, I mean, I think the idea that every platform should do everything has led us in a not great direction as far as user experience. And I think, I mean, if you think about some non-algorithmic spaces online right now, like a Discord server,

• 16:09Speaker 01

  or maybe a linear Reddit forum, just like the most recent posts, those work because they're not huge, because they're more intimate, because they're based on a specific context. And that's not how Facebook or Instagram or X or TikTok work at this point. So I do think you kind of have to rethink the entire mode of how we consume things online in order to build things that are not so algorithmic and encourage more intentional consumption.

• 16:40Speaker 00

  And that sort of goes to the second main thing in your book that I wanted to press you on, which was that like,

• 16:47Speaker 00

  if you don't have the algorithms, what do you have? So you can potentially redesign, you know, certain products to end up with smaller communities and smaller experiences and potentially that solves some of the problem of filtering the signal from the noise. But you're still going to have this big society with all this stuff out there. And so like, what do you do with it? Like, who then determines, you know, who, what you're, what you might find interesting? Now, of course, part of that is going to be you, you'll have the agency. But of course, like in the vacuum, we're going to have tastemakers.

• 17:24Speaker 00

  I kind of hate tastemakers. I find them to, first of all, be, there's, there's like tastemakers are so elite and often like follow elite tastes. But the, the real thing, and you know, maybe this is just me because I have about the as much basic taste as possible. So I'm kind of a sucker for Filterworld. Both the book, I guess, and the, and the algorithms. But what, what tastemakers often do is tell us like how, how, how things don't measure up to the bar. How things are bad and why that music is bad. That art is bad. And that movie that got mass appeal is bad. And like, I think they just sometimes try a little bit too hard to disparage things as opposed to appreciate the good for when it's good for so many people. What do you think?

• 18:07Speaker 01

  Hmm. I mean,

• 18:10Speaker 01

  the, the link between taste and elitism, I find so annoying, like problematic. I think it's like, I don't know when to trace it back to, like, was it the eighties, was it the nineties? But there's this idea that when you have taste, it is pretentious, or to say that you have taste is pretentious and is elitist. I think to me, this is just talking about taste philosophically, I suppose.

• 18:38Speaker 00

  Yeah.

• 18:38Speaker 01

  Everyone has taste in stuff. Like you have things you like. Other people have things that they like lesser more than you do. And it's not a problem to think about that. It's not like inherently problematic to be like, I really enjoy this thing, whether it's a sports team or noise music or like, you know, minimalist classical composition from 1973. Like, everyone can like all of those things.

• 19:10Speaker 01

  So I suppose rather than encouraging the return of elitist gatekeepers and tastemakers, I would rather encourage like everyone to become their own tastemaker. I think in a way I see that happening on Butterbox, the film review social network, where it kind of encourages all sorts of people, everyone on the site, to post their own little reviews, to think about what they like about a film, to rate it. I suppose that's the kind of tastemaking that I want to see more of. And that's also an example of a of a non-algorithmic platform that's still fun and cool.

• 19:50Speaker 00

  But is it chicken and egg a little bit? Because then like, how do you find the stuff that you're interested in?

• 19:56Speaker 01

  No, it's it's very true. But how did people find it before the internet? Like, they read magazines, they read newspapers, they talked to their friends about what records they bought in the record shop, which was probably helped along by a human being. Like, I think the human being as a cultivator of culture and as like a accelerator of that connection of of one recommendation passing to another person is good.

• 20:27Speaker 01

  I'm a big fan of recommendations. Yeah, yeah, word of mouth. Like, you should tell your friends what you like and why you like it. And that's not an inherently elitist act.

• 20:38Speaker 00

  Yeah, totally. No, I think that you're right. That's more of the grassroots tastemaking is like a great way to sort of replace some of those or hedge against some of the elitist tastemaking. Like, when I travel, and we're going to get into travel in the second half, but like, I'll, of course, like, read what's on TripAdvisor and stuff like that and Google Maps. But my favorite way to find out, and I think that I don't think this makes me special, again, going back to the basic tastes, but my favorite way to find out what's interesting around a place is just to go and ask the people that live there and are familiar with the places themselves, because they'll know better than the internet, you know, 10 times out of 10.

• 21:12Speaker 01

  Right. I mean, everyone, like, you have that friend who goes to Mexico City fairly often and has like the Google Doc of their own personal recommendations of where to go. And that's an example of human tastemaking. And that doesn't feel Pretentious or brow beating or something. It's just like, here's what this one person liked in this place. And maybe if you follow some of these suggestions, you'll find some cool stuff. You'll find more stuff. You'll figure out your own opinion of these things.

• 21:44Speaker 01

  And I think, I mean, you see different modes of this happening online now too. I mean, Substack and email newsletters are a great bottom up grassroots kind of way of spreading ideas and talking about stuff. And I mean, at least so far, email is relatively unsorted. Like, I still get a lot of, like, a fairly good linear feed of the stuff I want to see in my Gmail inbox.

• 22:11Speaker 00

  Yeah, although one thing that you wrote about really resonated with me when it comes to sending email, you write about this thing called, maybe we can go deeper into it, called algorithmic anxiety, where like, anytime maybe you try to communicate with someone or put a piece of, is it putting a piece of content out? You sort of feel some anxiety about how the algorithm is interpreting it and whether you did everything the algorithm asked for. And then I was just like, well, you know what? Like, I'm not subject to the algorithms because I do an email newsletter. And then I'm like, no, actually, I have the same exact thing. Have I been filtered into spam and my updates versus the primary inbox? I do have algorithmic anxiety. So can you talk a little bit about what that is as a, as a thing?

• 22:51Speaker 01

  Yeah, it was this really interesting term that was only coined in 2018, surprisingly, by this academic Shagun Javer. And he was kind of embedded at Airbnb as a sociologist. And he took on this project of interviewing Airbnb hosts about how they felt about Airbnb's search engine, the rankings of their listings. And what he found was that the hosts basically had no idea how the platform was working. They had all of these kind of folk tale methods of gaming the search engine and trying to provoke the algorithm into paying attention to them. Like, they would change their calendar a bunch of times. They would log on to the website more times a day.

• 23:35Speaker 01

  Like, they felt like these little tricks were giving them an edge when, in reality, it probably was not those variables.

• 23:44Speaker 01

  So I think the origin of that algorithmic anxiety is like the mismatch between how the algorithmic feed or recommendations affects us and how little we understand or can control them. Like in the context of a newsletter, you are wondering where your email is getting sorted into and if you're actually reaching your readers. I mean, when, when I put out a tweet or a X post or whatever we're calling them, I worry, like I, I think through, okay, how can I get the algorithmic feeds attention? What can I do to sustain it? Am I doing the right thing? And that's like a source of anxiety in part because I measured the success of the tweet

• 24:28Speaker 01

  based on likes, um, which is my own problem.

• 24:31Speaker 00

  I think everybody on Twitter does that.

• 24:33Speaker 01

  It's the scorekeeping.

• 24:36Speaker 00

  Yeah, exactly. Okay. So let me ask you this before we go to break. When people write a book like this, they, they have a goal in mind sometimes, like you want, you want to write a book and you want it to do something. I mean, obviously you want it to sell, but beyond that, like maybe it could have an impact. So is your intention here, is it to get the builders of tech to like, remove algorithms, to get the users of tech to think about their relationship with algorithms in a different way? Like, what are you trying to do here?

• 25:06Speaker 01

  I was really trying to provoke this conversation.

• 25:09Speaker 00

  Okay, well, here we are.

• 25:11Speaker 01

  Which is like, I think a lot of users are not aware of just how much algorithmic recommendations shape what they experience online. And we all underestimate how much they influence all of the culture that's around us. So I wanted to kind of shake, like grab you by the shoulders and shake you and be like, look at how these are influencing everything at once. Um, and I wanted to, like, not to be so hopeless as all that and like, offer some optimism, both in the form of like, showing how regulation is happening in the EU that is mandating algorithmic transparency and other things, and how new platforms are working online and there are like digital alternatives to these consumption

• 25:56Speaker 01

  habits that we have developed.

• 25:59Speaker 00

  What would you say to builders of products that, I mean, we have a lot of builders listening here. Um, they build, they use algorithms. If they hit the brakes or.

• 26:10Speaker 01

  I think, I mean, for me, as a user of this technology myself, like I've experienced all of these feeds, I've been as online as anyone over the past decade. I think we've reached a tipping point. People are tired of just how algorithmic these feeds have become, the kind of proportion of recommendations to things that you've chosen to follow. And I think users are thirsty for some sense of human to human connection that has become or gone missing in some of these larger platforms. And I mean, that used to happen on Facebook and Instagram. It can happen again.

• 26:52Speaker 01

  On TikTok, there are kind of dregs of human interaction when you like a comment or something. But ultimately, I think I want to see more apps and more experiences that are about cultivating one person communicating with one person, users' ability to follow a single voice in a sustainable way. And just like a, I think I want tech builders to have more of a sense of culture that's not just about popularity, that's not just about how many faves or how much engagement something gets. Like, I think obscurity is an important value, just as much as popularity is.

• 27:30Speaker 00

  Yeah, I guess like the question is, how would you code that into an algorithm? That is, that is a challenge. That is a challenge.

• 27:37Speaker 01

  Yes, it is.

• 27:38Speaker 00

  But maybe the way, maybe there's, I mean, two sides of the same coin. Yeah, maybe you do turn up the surprise knob, or the other thing that you could do is potentially allow for that more human input for, you know, broader signal, like maybe, I guess the follow signal's gone away for a reason, right? It just wasn't strong enough, but maybe finding ways to have people tune their experience, their experiences could be good. All right, we're. We're here with Kyle Cheka. He's the author of Filter World: How Algorithms Flattened Culture. I've got a chance to read it, enjoy it. In the second half, we're going to talk a little bit. So we've talked a little bit about online. In the second half, we're going to talk a little bit about how algorithms shape offline experiences. So plenty more coming up right after this.

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• 30:24Speaker 00

  And we're back here on Big Technology Podcast with Kyle Jakka. He's the author of Filter World: How Algorithms Flattened Culture. He also writes for The New Yorker, writes about tech for The New Yorker, covers AI, a lot of social media, really good stuff. Okay, so another thing that I read in the book that I found to be pretty interesting is that algorithms are shaping the physical world, right? That I don't fully know exactly how it works, but maybe things that do really well on Google Maps like have a, you know, similar type of feel and vibe to them and therefore they beget other physical places that look exactly the same. Can you talk a little bit more about that? That's really interesting to me.

• 31:03Speaker 01

  For sure. I mean, I think we all feel how algorithmic recommendations shape the physical worlds. Like, one example in the book is that Google Maps, for example, when passing by my wife's hometown of Westport, Connecticut, if the highway is too busy leaving New York, it will, Google Maps will route all of the traffic through downtown Westport, which is a tiny town, cannot handle many cars, there are many traffic lights. But it completely warps the quality of this downtown from being something that's for locals, like relatively slow, to this massive line of cars that's just circumventing I-95 or whatever.

• 31:45Speaker 01

  So that's an example of a recommendation literally reshaping how people move through the world. I think in, I write a lot in Filter World about coffee shops and restaurants and how they have to kind of mold themselves to digital platforms in order to succeed. And I mean, you see that, you see symbols of that as in the case of restaurants that name themselves Thai Food Near Me.

• 32:15Speaker 00

  Yeah, I love that.

• 32:16Speaker 01

  Thai Food Near Me does not make sense without the answer that, like... That as a name is illogical unless you consider that when people search for Thai food near me on Google Maps, this restaurant will likely come up because they've kind of gamed the system. So I find that same effect in a way with restaurants and cafes adopting certain design symbols, making sure they have really optimized internet presences, worrying about their Google Maps and Yelp ratings. I mean, lately, I've been traveling a bunch in the past month. And when I use Google Maps, it's really very blatant which

• 32:58Speaker 01

  restaurants have either paid for promotion or just really do well on Google Maps and they show up as these massive stars in the midst of neighborhoods or cities and I my attention is drawn to them inevitably. Like, it very much, Google Maps makes it easier for me to go to those places versus other places that might not be so online. So I think I just want to call attention to that fact that are even our choice of a restaurant is guided by how something has adapted to the internet.

• 33:29Speaker 00

  Yeah. And look, I think that first of all, the Thai food near me thing is just kind of hilarious. Maybe it doesn't really change. I mean, maybe you end up at a Thai food place because you search for it. But, but you also talk a little bit about how coffee shops have all started to look the same and they're like, I mean, let me see if I can capture it like kind of minimalist. They got the subway tiles on the, you know, white subway tiles on the wall. Everybody kind of knows exactly like the clear, the clear glass case with some pasties in it.

• 34:00Speaker 01

  Succulents and ceramic vases, nice little chunky mugs, latte art.

• 34:07Speaker 00

  I don't doubt that those things, like, there's a certain taste that people will like and they will go to these things and, and they'll rate them well. But I also sort of feel like if you had a kick ass coffee shop that was different, it would still break out and rate well. So can you talk a little bit about like, you know, are we just destined because of the algorithm to have all these different, you know, all these similar looking coffee shops? Like, why won't difference also rate well on Google?

• 34:35Speaker 01

  I think it's kind of going with the flow versus treading your own path in a way like

• 34:41Speaker 00

  It's too risky to open something that's different or?

• 34:44Speaker 01

  Well, I think so if you are an entrepreneur who is opening a coffee shop somewhere like I I reported this out for the book, I interviewed like a dozen coffee shop founders all over the world and asked them why they designed their coffee shop in the way that they did. And they all talked the most about Instagram and needing to cultivate the attention of the Instagram demographic, the the tourist who is planning their trip based on what they saw online. And they also talked about the kind of network effect of being able to connect with so many other coffee shop entrepreneurs and baristas so that the barista in Beijing could see what

• 35:27Speaker 01

  the barista in Brooklyn was doing all the time. So I think there's almost this peer pressure, both from the consumers and from the the shop owners themselves to all kind of move toward the same point. And if you want to attract that Instagram audience, which includes probably people like you and me, you want to look like Instagram, you want to follow the aesthetic that's already popular on Instagram. And I feel very guilty of this, like I'm part of the system because I do, you know, when I'm in a new city, I look on Google Maps, I look through the coffee shop listings, and I usually go to one that has all these symbols because I kind of know that it will be something that I like. I think it just creates this kind of self reinforcing cycle.

• 36:12Speaker 00

  Same here. And like, even though you like, go to these independent coffee shops, like, what you really end up in is, I don't guess I might get in trouble for saying this, but what it is, is it's like Starbucks, but it's just a different form of Starbucks, which is that it's uniform, but just shaped differently.

• 36:27Speaker 01

  It's decentralized Starbucks.

• 36:28Speaker 00

  Exactly.

• 36:29Speaker 01

  That's what we've invented here is like a completely homogenized, flattened experience that you can get anywhere, but it's not dictated by some corporate monolith.

• 36:39Speaker 00

  Interesting also because it does provide some comfort being able to be in a familiar place and in an unfamiliar place. Like, there's this, so there's this German rapper, his name's Aligato, he's a big, he's very, very popular there. I've been listening to some of his music. And one of his songs is about Going to Starbucks in Phuket and like how it's like, you know, it's so exotic, but you feel so at home. Sorry?

• 37:04Speaker 01

  Yeah, yeah. How that's a good thing.

• 37:06Speaker 00

  Just actually, I think just kind of making fun of the whole thing like, yeah, look at me. I'm in Phuket, Thailand, but I'm in Starbucks. But there is, I don't know, it is interesting. It's there's a comfort in it.

• 37:17Speaker 01

  Yeah. And I think, I mean, in, in the book, I'm kind of observing this as a phenomenon. I think it's a kind of like pressure or force. It's acting on a lot of things we experience now. I think in the context of a cafe or a restaurant, even this can be like a very nice experience to, to find something that you know is going to be good. Like I can reasonably be assured that if there's subway tiles on the coffee shop walls, then I'll get a good cappuccino. And that's usually

• 37:47Speaker 00

  Yeah, they're gonna have cold brew.

• 37:49Speaker 01

  Yeah, exactly. But what I want to argue is that that kind of familiarity and comfort might be what we want from a cafe, but I don't think it should be what we want from music or art or design that's supposed to like move you and make you become a better person. Like I don't think these coffee shops are making me a more moral or purposeful or like enlightened person. They're just giving me a good space in which to basically like numb myself.

• 38:19Speaker 00

  Yeah, it totally dulls the experience. Right. And my wife and I were just talking about this, about how travel, like, you know, a bunch of years ago, probably was not was, was way more exciting because you had no idea what you were walking into and you just sort of stumbled into amazing or heard word of mouth, you know, ended up at these great sights and wonders. And now it's like, okay, you go to Google Babs, you know exactly how to do it, you know exactly what it looks like, you know, exactly the angle to take the Instagram photo.

• 38:48Speaker 00

  You're grimacing here, and I think it just seems like this is resonating with you.

• 38:53Speaker 01

  It hurts in a way like that, that idea that everything is totally pre-visualized and predicted, and it's a kind of like easy frictionless path. And I feel like, I mean, travel used to be more challenging in many ways. It was harder to plan things out. You didn't have Google Translate. You didn't have the camera that could translate signs for you. But in a way, I think that challenge made things more satisfying, or at least gave a sense of purpose.

• 39:22Speaker 00

  Yeah, and some of your best stories about how you were so totally screwed on the side of a road, not having any idea where you were, and actually having to say hello to somebody.

• 39:31Speaker 01

  It pushes you into a scenario you wouldn't actually be in. Whereas if you're just like landing in a place and calling an Uber, and like going to your minimalist hotel, and then going to your minimalist cafe, like, that's actually not an experience of a place, or maybe an experience at all.

• 39:49Speaker 00

  So totally true.

• 39:50Speaker 01

  I mean, I like, as I said, I've been traveling a fair amount recently, and the, even the kind of Apple Pay or contactless pay that you can do with your phone has erased a bunch of experiences, like having to go to a ticket machine to buy a subway ticket in Amsterdam, or in where I am right now. Like, you can just carry your phone, swipe everything, and walk right in. And that's super easy and cool, and it really helps. But I almost miss the trouble of like figuring out how to get a ticket or get a new card for a different city.

• 40:28Speaker 00

  That is one step too far for me, Kyle. I'm not gonna blaspheme Apple Pay on this podcast, for sure. But I hear your point. Okay, so, so we're in this era right now of, you know, generative AI right now, it's like, it's almost like algorithms are gonna start mediating the other algorithms that we're using, and it'll just be algorithms all the way down. So obviously, like, as you wrote, this whole era of LLMs and generative AI was unfolding. How do you think that changes or accentuates some of these issues that you're talking about?

• 41:00Speaker 01

  I mean, my, my theory for a little while has been that algorithmic feeds, I mean, algorithmic feeds are a form of AI. There's machine learning there. There's like adaptability there. The algorithmic feeds have encouraged people to behave in kind of generic ways and culture to fit in specific molds, like the generic Spotify song or generic TikTok choreography. And I think generative AI now has this ability to like spit out the generic culture instantly based on a user's prompts, like rather than just guiding us toward a kind of generic culture, it's literally creating the generic culture from the get go. And you kind of see that in

• 41:42Speaker 01

  the, the cliche mid journey aesthetic of the kind of like average style of all of these AI images that kind of look like sci fi Lord of the Rings or whatever. Like there's a, a certain vision that just looks kind of good and looks kind of like AI and smooth and like reasonably coherent without being completely coherent. So I feel like as users start adopting these new tools, not just to like consume culture, but to create it, we'll be in the zone of like even more generic stuff at a higher and higher volume.

• 42:23Speaker 00

  I'm with you. I mean, I do think that generative AI is starting to homogenize creativity in many ways. And I guess creativity has also been homogenized in a big way, which is a whole

• 42:35Speaker 01

  I feel like we're, we talk a lot about creativity right now. And it's like, we have such a desire for creativity. Creativity is like such a good thing. No one says that creativity is bad. And yet we don't, we want creativity to be easy in a way. Like we want creativity to mean describing a thing to an AI model and then pushing the button, like as if that's fundamentally creative. And I don't think it necessarily is.

• 43:01Speaker 00

  Yeah. I mean, it, it is homogenizing, but the other side of this is that. It does allow for creative people to become even more creative by experimenting with so many different potential ways as opposed to just one and sticking with it. So I guess it's yet to be seen. I guess like one thing, one other thing I wanted to talk to you about before we leave, and I'm not 100% sure if it's related, but I think it might be, but you did write about it, and I feel like it's fair game, is that you did recently do this long piece about how people are starting to like really fall in love and build companionship with AI models. And I'm just kind of curious, like, if you could share a little bit about that, and if that sort of, is that the type of person that we fall in love with also kind of sort of

• 43:46Speaker 00

  be flattened by AI, or might it be AI, you know, completely?

• 43:51Speaker 01

  That doing that story on chatbots made me believe in AI more than anything else that I've experienced, like more than mid-journey, more than chat GPT turning, you know, refrigerator instructions into Shakespeare sonnets. Like, the chatbots truly feel like something new and different, I think, because people really relate to them as sentient creatures. And they, they relate to them as personalities, as characters with a depth and history and interactivity that I don't think much technology has at this point. Like, we don't think that our iPhones

• 44:32Speaker 01

  have personalities, right? It's just, it's one device for everyone, and it might have like quirks or flaws, but you don't say, oh, my iPhone is annoyed at me, or, oh, my iPhone said something really funny. Whereas these chatbot users really developed these deep relationships and senses of coherence and kind of three dimensionality with this technological product. And I found that really fascinating. I think in part, it works that way because people interact with them for so long, the chatbots do build up memories and kinds of shared frames of reference. And it becomes this human interaction in a way, or it draws more human interaction

• 45:17Speaker 01

  out of the human in the equation. It's, it feels inspiring, I suppose, in a way that few technological products have to me.

• 45:26Speaker 00

  So there's hope.

• 45:28Speaker 01

  Yes, I mean, we we just saw the new that new little red cube AI personal device.

• 45:35Speaker 00

  Rabbit. Yeah, Ron just talked about on the Friday show. He's trying to preorder it already.

• 45:40Speaker 01

  To me, what I want is like the Tamagotchi version of that, you know, the the AI Tamagotchi with its own personality. Maybe, okay, here's maybe what it is. The the depth of learning and training and the kind of experience and memories of a specific AI character is specific. Like, your chatbot is not like other people's chatbots.

• 46:05Speaker 00

  Right.

• 46:05Speaker 01

  And that's a not homogenous thing. That's that can maybe cultivate more specificity and more unique experience.

• 46:12Speaker 00

  Well, just wait till we all end up in Vision Pro and we're starting to not only have these as Tamagotchis, but talking to them. And, you know, those are all going to be algorithmically generated as well, but maybe not sorting algorithms. But if you think you're living in a filter world now, just wait until you put those things on and then you're really going to be there.

• 46:31Speaker 01

  Right. I think this book was really about the past decade. It was like about the 2010s and what happened to us during the 2010s. And now we're just on the cusp of like some other thing. And it'll take a decade to figure out what that's about, too.

• 46:46Speaker 00

  The book is Filter World: How Algorithms Flattened Culture by Kyle Chayka, who's here with us today. You can find it this week in any bookstore you'd like, Amazon or any of the local indies. I have a feeling of which one Kyle's going to want you to visit, maybe one that doesn't have an algorithm in the in the front door.

• 47:05Speaker 01

  Call your bookstore. Call up your local bookstore and request it.

• 47:08Speaker 00

  Exactly. Kyle, thanks so much for joining.

• 47:12Speaker 01

  Yes, it's really fun. Thank you.

• 47:14Speaker 00

  Great stuff. Thanks, everybody, for listening. Thank you, Nick Otteney, for handling the audio. LinkedIn for having me as part of your podcast network. And all of you, the listeners, we will be back on Friday to break down the week's news. Until next time, we will see you then on Big Technology Podcast.

• 47:37Speaker 03

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