0:00

First, the bad news. SAP

0:03

Business AI won't help you generate

0:05

cubist versions of your family's holiday

0:07

photos, but it will help

0:09

you understand which supplier is best to

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help you roll out your plant-based packaging

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in Southeast Asia, identify

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the training your junior project manager needs

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to rise up the ranks, and

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automate repetitive tasks while you

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focus on big innovations, so

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you can be ready for the next opportunity. Revolutionary

0:29

technology, real-world results.

0:32

That's SAP Business AI. First,

0:37

the bad news. SAP

0:39

Business AI won't help you generate

0:41

cubist versions of your family's holiday

0:44

photos, but it will help

0:46

you understand which supplier is best to

0:48

help you roll out your plant-based packaging

0:50

in Southeast Asia, identify

0:52

the training your junior project manager needs

0:54

to rise up the ranks, and

0:57

automate repetitive tasks while you

0:59

focus on big innovations, so

1:02

you can be ready for the next opportunity. Revolutionary

1:05

technology, real-world results.

1:08

That's SAP Business AI. On

1:18

the morning that I spoke to Kyle Chaco, I

1:20

dropped my son off at preschool and stopped to get

1:22

some coffee on the way to work. And

1:25

I wanted Kyle to try to guess

1:27

what the coffee shop that I went

1:29

to looked like. I

1:32

wondered if that was something he could do. I

1:35

think so. I mean, I'm going to

1:37

use my mental magician powers and say

1:39

that there were some hanging

1:41

pendant lamps that may have had Edison

1:43

bulbs in them. There might

1:46

have been some white subway tiles on

1:48

the wall behind the counter,

1:50

which might be like a nice marble

1:52

or even concrete. It's really cool.

1:55

Some nice reclaimed wood furniture or

1:58

some vintage bits and pieces. century

2:00

pieces that make you feel like you're in a

2:02

nice hotel from 1955. And

2:06

then probably some nice ceramic cups that

2:08

your cappuccino comes in. It

2:10

was a latte to go, but the rest

2:12

of this description is pretty spot on. Because

2:16

Kyle has thought a lot about

2:18

what particular signifiers a coffee shop

2:20

today might possess. He's

2:23

a staff writer at The New Yorker

2:25

and has just written the book Filter

2:27

World, How Algorithms Flattened Culture. In

2:30

one part of the book, Kyle talks about

2:32

how whenever he was traveling, he would type

2:34

Hipster Coffee Shop into Yelp and

2:37

Google Maps. Hipster,

2:39

in the 20s at least,

2:41

was the signifier of millennial

2:43

era consumers and tastes. And

2:47

the coffee shops all had to project

2:49

their image online through these apps like

2:52

Yelp or Google Maps. So

2:54

it was a kind of index. I

2:56

could use the phrase through the search

2:59

algorithm, through Yelp's rankings and star ratings

3:01

to find exactly what I was looking

3:03

for. When

3:09

you wrote about this phenomenon in

3:12

2016, you called it airspace. What

3:15

does that mean? At the time,

3:17

I used that word airspace

3:19

to talk about the style that was happening,

3:21

like the generic minimalist,

3:23

white subway tile, mid-century

3:25

furniture thing. And

3:28

I was seeing that not just in

3:30

coffee shops, but in co-working spaces and

3:32

restaurants and hotels and kind of like

3:35

the whole new geography that was popping

3:37

up with the sharing economy. When

3:40

readers saw the term airspace, they

3:42

knew exactly what Kyle meant and

3:45

started emailing in pictures of coffee

3:47

shops and hotel lobbies that hewed

3:49

to this same shareable aesthetic. It

3:52

was a geography and a physical space

3:55

that had a lot in common with the

3:57

digital spaces that we're in. like

4:00

interconnected and driven by the internet.

4:05

Was there a point in which you

4:07

realized, oh, this is more than

4:10

this design

4:12

phenomenon of coffee shops and

4:14

WeWorks and what have you,

4:17

that you realized I think

4:19

this is rippling out into something bigger? Yeah,

4:22

like the, to me the coffee shop aesthetic

4:24

was kind of the canary in the

4:26

coal mine. Like it was the most

4:28

visible symbol of this

4:30

homogenization that was happening over the

4:32

internet. So there was that

4:34

design, right? Like it was a cliche, stereotypical

4:37

design that I think a lot of people

4:39

kind of observed. And it became a cliche,

4:41

it was boring. You can kind of see

4:43

it everywhere. But I think the

4:45

like reality of it, the source of it

4:47

ran much deeper. It

4:50

ran, Kyle says, to a handful

4:52

of tech companies creating a larger handful

4:54

of algorithms that drove our behavior. Whether

4:56

we knew it or not. It

4:59

wasn't just about one style, but

5:01

this deeper homogenization and sameness

5:03

that was creeping into a lot of

5:06

different spaces driven by the Instagram

5:08

feed and now the

5:11

TikTok feed and Netflix streaming and Spotify

5:13

recommendations. It was kind of this aesthetic

5:16

that spread everywhere via the feeds.

5:22

Today on the show, are we living

5:24

in filter world? A place where

5:27

algorithms, not people, decide what

5:29

we like. I'm

5:31

Lizzie O'Leary, and you're listening to What Next

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TBD, a show about technology,

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6:24

First, the bad news. SAP

6:26

Business AI won't help you generate

6:28

cubist versions of your family's birthday

6:30

photos, but it will

6:33

help you understand which supplier is

6:35

best to help you roll out your

6:37

plant-based packaging in Southeast Asia. Identify

6:40

the training your junior project manager needs

6:42

to rise up the ranks and

6:44

automate repetitive tasks while you

6:46

focus on big innovations so

6:49

you can be ready for the next opportunity. Revolutionary

6:52

technology real-world results. That's

6:55

SAP Business AI. Kyle

7:02

describes filter world as the

7:04

vast interlocking and yet diffuse

7:06

network of algorithms that influence

7:09

our lives today. And

7:11

while you may have thought of that in

7:13

terms of politics, how Facebook

7:15

tends to surface outrageous selection

7:17

content, for example, Kyle's

7:19

book focuses on culture and

7:22

how he says the world

7:24

of algorithmic recommendations favors

7:26

a certain kind of culture. Things

7:29

that are easier, less challenging

7:31

to digest, made for

7:33

sharing and recommending over and over

7:36

and over. I

7:39

want you to try to describe

7:41

filter world as a place to

7:43

me. What are its

7:46

defining characteristics? Like if you're an

7:48

inhabitant of filter world, what is

7:50

your experience? It's almost

7:52

like being a rat, an image. You

7:55

are surrounded or we are surrounded as

7:58

internet users by all of these. these

8:00

different algorithmic systems and

8:02

we're constantly being guided in

8:04

one direction or another by

8:06

recommendations. So Spotify is pushing a

8:08

song at you or Netflix is

8:10

pushing a new TV show. So

8:13

I think as an inhabitant of filter worlds,

8:15

we're just immersed in

8:17

this bubble of our own desires

8:19

or a projection of our own

8:21

desires that come to us through

8:23

digital platforms. I use

8:26

the word filter because these

8:28

feeds and recommendations are a filter,

8:31

like they sort content for you. They

8:33

try to guide you towards something that

8:36

fits with your taste. But I think

8:38

that becomes an inescapable

8:41

environment. It's a

8:43

scrim or a filter that you can

8:45

actually see through, that blocks you from

8:47

experiencing other things. One

8:49

of the parts of the book that I

8:51

found really interesting was this

8:54

moment where you describe a shift

8:56

from chronological feeds, sort

8:58

of the infancy of social

9:01

media to algorithmic

9:03

recommendations. When do you

9:05

start to pinpoint that shift? Yeah, I

9:07

think there really was a shift over the course of

9:09

the 2010s. When

9:12

we all got on social media, when social

9:14

networks were beginning to be popular and say

9:16

like the late 2000s and early 2010s, most

9:21

of the feeds there were linear, meaning

9:24

that they were chronologically ordered. You saw

9:26

the posts that were posted most recently,

9:28

and then you saw the older ones,

9:30

and that's just how all content was

9:32

treated. Then there's

9:34

this watershed moment around 2015, 2016

9:39

where tech companies decided to make

9:41

the feeds more algorithmic, to mix

9:43

in a greater proportion of recommendations

9:45

versus things you chose to follow.

9:49

That happened with the Facebook feed,

9:51

it happened with Instagram recommendations, it

9:53

happened with the Netflix homepage. They

9:57

all move toward sorting

9:59

content. for you rather than letting you

10:01

choose exactly what you were going to see.

10:04

That has been covered fairly relentlessly in the

10:06

media talking about the 2016 election and

10:09

Facebook showing, you know, more inflammatory content,

10:12

for example, things things that are

10:15

more likely to provoke an emotional response, getting

10:17

boosted by the algorithm, etc. But you

10:20

focus so much on culture

10:22

and taste. That is the heart of

10:24

this book. And there is a

10:27

quote in which you say, the

10:29

overall digital environment is dictated by

10:31

tech companies with ruthlessly capitalist expansionary

10:33

motives which do not provide the

10:36

most fertile ground for culture. Sounds

10:40

bad. It does sound bad. But

10:44

I want examples of that. I want to

10:46

understand where you

10:49

see Filter World sanding

10:51

off the difficult

10:53

edges of art or movies

10:55

or music. Yeah, I

10:58

mean, I think one of

11:00

the issues of Filter World is just

11:02

that so much of our consumption of

11:04

culture has become mediated by

11:06

these feeds. Like whenever we want to

11:08

listen to a song, we're on Spotify

11:10

and getting kind of redirected by the

11:13

platform. Whenever we want to watch

11:16

a TV show or film, we are

11:18

like not just choosing what to see,

11:20

but experiencing the recommendations of Netflix. So

11:22

I think our consumption is being guided

11:24

in manipulative ways. For

11:27

one example, Netflix changes

11:30

the thumbnails of the shows it presents

11:32

to you based on what it sees

11:34

as your personal taste. So not

11:36

only is the selection of content on their

11:38

change, but actually how it's presented to you.

11:41

And so if you're a person who,

11:44

say, only watches rom-coms, but

11:46

Netflix wants to push you toward a

11:48

sports documentary or something, it might show

11:50

you an image that leads you to

11:52

think a sports documentary is a rom-com.

11:54

And that kind

11:57

of fools you into not thinking about your own

11:59

taste. and into consuming something that

12:02

doesn't necessarily appeal to you. On

12:04

the creator side, because all

12:07

of our attention is so mediated by these feeds,

12:09

creators like artists, musicians,

12:12

designers, whoever have to

12:14

tailor their work in a

12:16

way that works for the feed. I

12:19

mean, you see that on TikTok

12:21

where music producers focus on making

12:23

sound bites that are like 10

12:25

seconds long, but are so densely

12:27

packed with sound and drama that

12:29

you just instantly

12:32

stick in your head and they're repeatable

12:34

infinitely. I mean, in one case

12:37

in the book, I spoke with

12:39

an illustrator friend of mine, Hallie

12:41

Bateman, who experienced this algorithmic

12:43

pressure on Instagram. When

12:45

she started doing a series of

12:48

drawings of just little self-help

12:50

commandments or suggestions on brightly

12:52

colored construction paper, and

12:55

immediately that work blew up on Instagram.

12:57

That became her most successful project ever.

12:59

She was getting tons of followers. But

13:02

then she also experienced this pressure to

13:04

keep doing that, to serve the audience

13:06

that was only coming to her for

13:08

that thing. For her, it

13:11

felt like that was just

13:13

a distortion of her own creative practice. That's

13:15

not what she wanted to be known for.

13:17

That's not what she wanted to chase in

13:19

a way to keep her audience's attention. I

13:22

guess that makes sense if you

13:24

are thinking about someone who is

13:26

gaining fame, or gaining followers,

13:28

or gaining money from existing

13:31

on the Internet. But there's a

13:33

section of the book where you seem

13:35

to pause it, and I want to

13:37

dig into this, that it goes deeper

13:40

than that. That the popularity of Sheila

13:42

Hetty or Nausgarde, or

13:45

this particular kind of auto fiction

13:47

is what? Is

13:51

the rise of these books because

13:53

we are used

13:56

to viewing the world in

13:58

an Instagram protagonist way? I

14:01

think Instagram and

14:03

other feeds have really

14:06

shaped how we see everything in the world.

14:08

All forms of culture has to kind of

14:10

flow through them. And in

14:13

the case of auto-fiction, my

14:15

book was kind of responding to

14:17

this academic Mark McGurrell's work

14:20

on Amazon, the algorithmic marketplace of

14:22

books that exists on there. And

14:25

he argued that Amazon and

14:27

algorithmic recommendations kind of slot

14:30

authors into very specific genres

14:32

of stuff, whether that's like

14:35

romance or fantasy

14:37

or something like auto-fiction, which has kind

14:39

of become a dominant literary

14:42

mode. And

14:44

to me, the way that auto-fiction resonates

14:46

with Instagram is that we

14:48

want the author to be a

14:50

kind of influencer. We want the author, we want

14:53

to know about the author's life. We

14:55

want to know what kinds of coffee shops they're

14:57

going to. We want to know what's in their

14:59

home. We want to kind of consume

15:01

their lifestyle in a way as

15:03

much as we consume their

15:06

work of literature itself. So I

15:09

think there's a resonance with how

15:11

auto-fiction plays with the presentation of

15:13

the self and authenticity in

15:15

the same way that an influencer on Instagram

15:17

kind of presents some of their self and

15:20

shows off some of their real identity.

15:22

But then it's also kind of inauthentic

15:25

and artificial as well. I

15:27

talked to some of my colleagues about this and sort of

15:30

said, do you see experiences of

15:32

flattened culture? And one question that came

15:34

back to them was like, but isn't

15:37

it kind of fun and cool to learn

15:39

about cottagecore, gremlin's

15:42

core, dark academia?

15:45

Even if these are like weird flash in the

15:47

pan things that circulate via social media, they

15:52

seem organic. No, not

15:55

prescribed by Anna Wintour on high.

15:58

Yeah, I think there's this bottom. generation

16:00

of culture that is really interesting online.

16:04

I think these digital platforms highlight a

16:06

ton of interesting stuff and they allow

16:08

us to experience the breasts of what

16:11

everyone makes. There are fewer

16:13

gatekeepers. And I love

16:15

exploring that field like Grandma or Coastal

16:19

Grandmother aesthetic. Whatever the one

16:21

is that we're talking about this week or

16:23

month, it's always fun to know. And

16:26

I think what becomes overwhelming is the

16:29

specificity and speed that these

16:32

things emerge and pass by with.

16:35

All of a sudden everyone is talking about Mobwife

16:38

core or something. That's the one I've

16:40

been seeing this week. TikTok has spoken.

16:42

The clean girl aesthetic is out and the

16:44

Mobwife aesthetic is in. I am

16:47

so excited. It's time for the fur coats. It's

16:49

time for the makeup girlies. It's time for series,

16:51

all black leather outfits. I

16:53

want dramatic. I want maximalism. So let's talk

16:55

about how to dress like this. And it's

16:58

just like the trends percolate

17:01

up and then pass by so

17:03

quickly that you almost don't have a

17:05

chance to actually engage with what the content is

17:07

there. To me

17:09

it's almost...it creates this

17:11

atmosphere in which there's more pressure to

17:14

keep up with the thing that's new

17:16

and the thing that's going viral this

17:18

second. Then there is to really

17:20

go deep in a single one of these areas.

17:23

So I worry that it's almost like too much flavor of

17:25

the week. And we're

17:27

not allowing ourselves to think

17:30

slower thoughts and develop a

17:32

different sense of identity. I mean,

17:34

I contrast the

17:37

flash in the pan, coastal grandmother, etc.,

17:41

Cottagecore, Tran, TikTok with maybe

17:43

a more long-term cultural identity

17:45

like punks or

17:48

goths. Or even

17:50

the hipster in a way. It was like, produce

17:52

a more meaningful body of culture than

17:54

just this instant adaptation to an aesthetic

17:56

that then passes by when it no

17:59

longer gets engaged. management. When

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we come back, the anxiety that

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18:56

the bad news. SAP Business

18:58

AI won't help you generate cubist

19:01

versions of your family's holiday photos.

19:04

It will help you understand which supplier

19:06

is best to help you roll out

19:08

your plant-based packaging in Southeast Asia, identify

19:11

the training your junior project manager needs

19:13

to rise up the ranks, and

19:16

automate repetitive tasks while you

19:18

focus on big innovations so

19:21

you can be ready for the next opportunity. Revolutionary

19:24

Technology Real World Results.

19:27

That's SAP Business AI. This

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coverage match limited by state law. In

20:27

one of the most fascinating sections of the book, Kyle

20:30

writes about something called algorithmic

20:32

anxiety. Because by now, we

20:34

all know that algorithms are affecting our lives,

20:37

but we don't always know exactly how. The

20:41

term itself was coined by an

20:43

academic to describe the way Airbnb

20:45

hosts tried to alter their property

20:47

listings to appeal to the company's

20:49

search algorithm, changing the

20:52

photos of their listings or describing them

20:54

with slightly different keywords so they would

20:56

be shown to more potential renters.

20:59

And these things didn't actually work. Like

21:01

they were just strategies of

21:03

coping with the unknowability of

21:06

that digital platform. And

21:08

I think we all kind of experienced that unknowability.

21:12

Like we don't know what the TikTok feed

21:14

is thinking of us. We don't know exactly

21:16

how the Netflix homepage works. And

21:18

so we're constantly negotiating with how

21:21

our behaviors are being perceived by

21:23

the technology, what signals we're

21:25

sending or not sending. And

21:28

I think we also feel anxiety because we

21:30

can't talk back to these systems. Like they

21:32

exert so much power over us and

21:35

we exist through them so often, but

21:37

we can't change how the X

21:39

algorithm works. We can't tell Netflix

21:42

to stop recommending one thing or

21:44

another. Right, I have no

21:46

idea how Spotify is gonna put this podcast

21:48

up today, right? It could

21:50

display it prominently or not. Right, right,

21:53

and those are technological systems that we

21:55

just don't have any agency over. And almost,

21:57

I mean, no human does in a way.

22:00

They are quite black box

22:02

systems that are operating at a

22:04

scale that is beyond any one person.

22:07

There maybe is not a person choosing to

22:10

highlight one Spotify song or another. It's just

22:12

what's popular and what gets automatically recommended.

22:15

But I think what I struggle with is the

22:18

human response to that, right? Like you talk about

22:20

this woman who bought leg

22:22

warmers because she saw a bunch

22:24

of influencers by leg

22:26

warmers. And

22:29

it seemed to really inspire like

22:31

a crisis of confidence in her that she sort

22:33

of felt like she didn't know who she was

22:35

and she couldn't figure out her

22:38

own style or identity. And

22:40

maybe this is because I'm 48, but I read that

22:42

section of the book and thought, why are you

22:44

letting this do this to you? Just

22:48

wear what you want to wear. Who cares what

22:50

the internet thinks? Yeah,

22:52

I mean, it sounds so simple. Like

22:54

to just say, oh, we'll think about

22:56

what you like, kind of separate yourself

22:58

from the feeds. But

23:01

I mean, as a

23:03

millennial and talking to a lot of

23:05

younger people, like Gen

23:07

Z people on TikTok,

23:09

particularly, their identity is almost

23:12

more manipulated by the

23:14

feeds online. Like they have experienced

23:16

this for more of their lives.

23:19

Their tastes or preferences were already

23:21

developed within these systems. And

23:24

so I think there's a sense in which they haven't learned

23:26

to distrust them, or for a long time it's

23:28

worked and shown them what they did like, or

23:31

they believed it showed them what they liked, unless

23:33

they trusted the feed more than they

23:36

might trust a human tastemaker. They

23:38

haven't had those kinds of conversations or

23:41

developed like almost the skill of thinking

23:43

about what you as a person like,

23:45

as opposed to what's popular. I

23:48

mean, to me, that feels extraordinarily naive.

23:52

I mean, tech companies

23:54

have occupied so much of our mental

23:56

landscape in a way. Like the more

23:58

online you are, the more you're... influenced

24:00

by these systems. And

24:02

so I think it is easy to forget

24:04

that there's a world outside of that, to

24:06

forget that you can figure

24:08

out what you like, not on the

24:11

TikTok feed, not just chase what influencers

24:13

are doing or what Twitter pushes at

24:15

you. So I said same

24:17

woman Valerie Peter, she

24:20

was on Twitter or on X and

24:22

was looking at astrology content and

24:24

had been interested in it for a while. And

24:28

all of a sudden she got bombarded

24:30

with all of this astrology that she

24:32

then started to dislike and felt like

24:34

kind of misled or anxious

24:37

about getting. But she couldn't

24:39

tell Twitter to stop giving her this

24:41

content. She couldn't send a strong enough

24:44

signal to stay away from the astrology.

24:46

And I feel like it shows in

24:48

a way how the feeds direct you

24:51

in ways that you don't necessarily like.

24:54

You bring me to the idea of pushing back and I

24:56

feel like there are sort of two

24:58

buckets there. One is on

25:00

the individual level and one is on the

25:02

societal or regulatory level. The

25:05

final chapter in this book is about your algorithmic

25:08

cleanse or algorithm cleanse. Tell

25:11

me about that. I

25:14

wanted to do a kind of algorithm

25:16

cleanse, like almost like a diet

25:18

or like giving up something

25:21

for a length or a dry January,

25:23

like just getting outside of the feeds.

25:25

In part because I just become so

25:27

overwhelmed with them. Like I am as

25:30

online as anyone. I was on X

25:33

for work. I was looking at Instagram all the time.

25:36

And so I kind of decided that the only way

25:38

I could truly see who I was without these things

25:40

was to just get off them for a while. And

25:43

so I deleted everything from my phone, logged

25:46

off all the apps. I

25:48

was kind of confronted with this sudden

25:50

silence of the absence of

25:52

the feeds and the absence of these thousand

25:54

posts a day that I was

25:57

used to consuming. But I think

25:59

like cutting that stuff off. off and going cold

26:01

turkey, did reframe how

26:03

I think about digital platforms. It

26:06

reminded me in a way that you don't

26:08

need them. That there's a world outside of

26:11

what gets recommended to you. I

26:13

think it lessens that algorithmic anxiety

26:16

simply because I didn't have to

26:18

contend with this image

26:20

of myself that existed online, that

26:22

I was constantly being manipulated by.

26:24

Yeah. I have to admit that there's a part of

26:26

me that was like, dude, just log off. Easier

26:30

said than done sometimes. Well,

26:32

that brings me to the macro stuff. I

26:34

mean, and this is

26:36

where I think you

26:39

get to some of the most interesting parts

26:41

of the book, is that perhaps culture

26:44

and society is

26:46

being manipulated, even if you have

26:49

logged off, even if you

26:52

are not a part of this on

26:54

a micro level, even if you're Marty

26:57

Scorsese, you feel the influence

27:00

of these companies. It

27:03

makes me wonder if this

27:05

is a question of algorithmic

27:07

influence or monopolistic influence. If

27:09

there were 500 companies

27:14

driving social

27:16

media feeds, would it be different? I

27:20

think it would be. I mean, as users,

27:22

we feel that we don't have that much

27:25

choice of what we experience. Meta

27:28

as a company owns Facebook and

27:30

Instagram and WhatsApp, which are three

27:32

of the biggest platforms in

27:34

the world. Even if

27:36

you are not on those platforms, the

27:38

actions and decisions of billions of people

27:40

around the world are being guided by

27:42

them. That impacts what

27:44

music gets made, it impacts what

27:46

films get produced. The

27:49

response of the Martin Scorsese concern, influences

27:53

how restaurants advertise themselves, and

27:55

what kinds of dishes

27:57

they put on their menus. Because even if you don't

27:59

care, about how something works on TikTok,

28:02

a lot of other people will. So

28:05

I think we are all kind

28:07

of living in this world shaped

28:09

by algorithmic recommendations. And I think

28:12

increased competition, if we can break

28:14

down the monopolies of

28:16

meta and Google, would

28:18

actually lead to a wider diversity of

28:21

experiences. We could change

28:24

how algorithmic feeds work perhaps, or

28:26

we could drift to

28:28

different flavors of platforms that might better

28:30

serve our personal preferences. At

28:32

the end of writing this book and talking about

28:34

it, it just strikes me so much that

28:37

the idea that a billion people should

28:40

be on one digital platform and all

28:42

being pushed through the same pipes in

28:44

a way is deeply disturbing. That's

28:47

the biggest homogenizing force

28:50

of us that we've ever seen

28:52

in human experience. It's

28:55

kind of gross to me at this

28:57

point. LISA K. H United

29:21

States, we've had a really hard time

29:24

passing any regulation on social media, just

29:26

because there isn't fully the political

29:29

willpower and the platforms themselves have

29:31

become so dominant. They spend so

29:34

much money on lobbying. But if

29:36

you look outside of the US

29:38

at European Union regulation, they

29:41

are actively putting laws into place

29:43

that give users rights to their

29:45

data, for example, or give you

29:47

the ability to opt out of

29:49

surveillance, or even with

29:51

the more recent Digital Services Act

29:53

in the EU, it mandates

29:55

that you can opt out of algorithmic

29:58

feeds. Like if you don't have a chance to do that, you can't just do that. don't

30:00

want to experience recommendations, you will have the

30:02

option to not do that. And

30:05

that's almost unthinkable in the United

30:07

States right now. You

30:10

see the platforms kind of responding to

30:12

those regulations and changing how they work

30:14

for everyone because they use. It's easier

30:16

for them to just make one big change. Yes,

30:19

yeah, yeah. But I think actual

30:22

regulation in the United States where these companies

30:24

exist could accomplish a lot more and just

30:26

give us more options for how we live

30:28

online. How should one

30:30

arrive at the idea of taste and culture?

30:32

Because you talk a lot

30:35

about the local DJ or the art critic or

30:39

whatever. But I think about

30:42

going to the movies in the early 90s,

30:45

and my family had this joke about our

30:47

movie theater as the Bethesda monoculture, that

30:49

it catered to

30:52

upper middle class white

30:54

people. And those were

30:56

the tastes that spread

31:00

society wide. And

31:02

so the democratizing

31:04

aspects of the internet are

31:07

incredible. I

31:09

worry that if we

31:11

go the other way, it's racist,

31:14

it's classist, it's sexist, that

31:17

you're subject to the taste of just a handful of people.

31:20

Yeah, there were these gatekeepers in

31:22

the past, like these human gatekeepers.

31:25

And there still are. Yeah. And

31:28

now I think we have this

31:30

algorithmic gatekeeping mechanism. But we do

31:32

have the total democratization of publishing

31:35

and of allowing anyone

31:37

to put something online and access an

31:39

audience. And I think that's amazing

31:41

and really a positive force

31:43

in culture. What I

31:46

don't like is the total

31:48

domination of algorithmic gatekeeping in

31:50

a way. Anyone can

31:52

put something online. But that

31:54

doesn't guarantee that you're going to get an

31:56

audience for it. You don't have a right

31:59

to other people. people's attention. And

32:02

algorithmic feeds push people's attention toward

32:04

a very specific set of content

32:06

that works for the platforms that sparks

32:08

the right kinds of reaction on people.

32:11

So I think, you know, we gain

32:13

something in the system, in the ecosystem of

32:16

the internet that anyone can put something out

32:18

there, but we also lose it with

32:21

just the sheer extent that

32:23

our attention is directed by algorithmic feeds.

32:25

We're not just seeing everything that everyone

32:28

puts out there. And from

32:31

the perspective of creators, like

32:34

the independent kid who might

32:36

upload music to Spotify, Spotify

32:38

literally put into place

32:40

a new rule that they are

32:42

not going to monetarily reward any

32:44

song under a thousand streams. So

32:47

that essentially argues that

32:50

if you can't reach over a

32:52

thousand streams, if you can't game

32:54

the system and get an audience,

32:56

then your art is literally worthless,

32:58

that you shouldn't get rewarded for it.

33:00

And that means you can't make it in

33:03

the future. Like I think this

33:05

algorithmic ecosystem is unsanable for

33:07

the production of culture. That

33:11

makes me wonder how much

33:13

of this might be transient,

33:16

either because as a consumer, you

33:19

age out, right? You

33:22

reach a point and you just

33:24

think like, this is who I am, and I'm okay

33:26

with that. Or because if

33:28

you're a younger person, and you've

33:31

been brought up with this, you're pretty

33:33

savvy. Like you might start to question

33:36

what the algorithm is doing. Did

33:38

you find any points in

33:41

your reporting process where you thought like, maybe

33:44

I'm capturing a moment in time, but it's not always

33:46

going to be this way? Yeah,

33:49

yeah. I mean, the internet changes so

33:51

much that one fear I had

33:53

in writing the book was just that I would be

33:56

capturing something that wasn't relevant anymore that

33:58

had like disappeared and I

34:00

added into the ether. And I

34:02

think change has happened a bit slower

34:04

than I expected. I

34:06

think the way that I framed

34:09

the book or the way that I think about it

34:11

now is that it's about the internet of the 20

34:13

times. It's about how a

34:16

certain ecosystem evolved, how

34:19

we responded as consumers to it,

34:21

how digital platforms developed to

34:23

be the way they are. And

34:26

now I kind of see the on-wee and

34:28

the anxiety growing to the point that

34:30

people are rebelling against these systems and

34:33

looking really intentionally for alternatives.

34:36

I don't think the alternatives exist yet

34:39

necessarily, like in part due

34:41

to the lack of monopoly regulation and

34:43

things like that. But there's

34:45

a desire for a new internet. There's

34:47

like a desire to not

34:50

exist in this filter world and to

34:52

move beyond it. And I think by

34:54

the end of the book, when I finished writing

34:57

a year or so ago, I

34:59

started to watch Twitter fall apart

35:02

under the pond ask. I started

35:04

to see the Facebook scrambling

35:06

and trying to do the metaverse. That

35:09

didn't work either. So

35:12

I think by the tail ends, I

35:14

got the sense that we're moving out of the phase

35:16

of the internet that happens. But

35:18

that phase dictated so much of what culture

35:20

was popular in the past eight to 10

35:23

years. Does that leave you hopeful? Yes,

35:26

it does. I mean, the

35:29

internet's always changing. Like there's always

35:31

new things popping up and new

35:33

mechanisms and experiments to try. And

35:36

like human creativity, there's no depth of

35:39

culture here. There's no end to the

35:41

human desire to make art and to

35:43

make original stuff. I

35:46

just think the digital ecosystem

35:48

could support that more. And

35:50

what I'm hopeful for is like different kinds

35:53

of platforms that are more sustainable, both

35:55

for our attention and for the careers

35:57

of the artists and creators. Kal

36:05

Chayka, thank you so much for coming on and

36:07

spending this time with me. Thanks for

36:09

having me. Kal

36:12

Chayka is a staff writer at

36:15

The New Yorker and the author

36:17

of Filter World, How Algorithms Flattened

36:19

Culture. And that is

36:21

it for our show today. What Next TBD

36:23

is produced by Evan Campbell, Anna Phillips, and

36:25

Patrick Farr. Our show is

36:28

edited by Mia Armstrong Lopez. Alicia

36:30

Montgomery is vice president of audio for

36:33

Slate. And TBD is part of the

36:35

larger What Next family. We're

36:37

also part of Future Tense, a partnership

36:39

of Slate, Arizona State University, and New

36:41

America. And if you are

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36:53

All right, we will be back next week

36:55

with more episodes. I'm Lizzie O'Leary. Thanks for

36:57

listening.