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apply. Not

1:03

all search engines are good. Some

1:05

are morally dubious. A

1:08

couple months ago, I found myself using a

1:10

morally dubious search engine. This

1:12

search engine lives on a website. I'm not going to tell you

1:15

the name of it for reasons that will become clear, but

1:17

I am going to describe to you how it works. So

1:22

you open the site, you upload a

1:24

photo of a person's face. I

1:27

can upload a photo of myself right now. Wait

1:30

about 30 seconds for the search to run,

1:32

and then I get taken to this page,

1:34

which includes all these different photos of my

1:36

face from all these different places on

1:38

the internet. I can click on

1:40

any of the photos and it'll take me to the site

1:43

where the photo lives. This

1:45

is Shazam for faces. If

1:48

I put it in a stranger's face, I'll almost

1:50

always get their real name because it'll take me

1:52

to one of their social media profiles. From

1:54

there, I can typically use a different search

1:56

engine to find a physical address, often a

1:58

phone number. And the

2:01

site itself, I also usually see stills

2:03

from any videos the person has appeared in.

2:06

When I first learned about this site, I

2:09

did what you do when you get Google for the first time. I

2:11

looked myself up. And then I

2:14

started looking at my friends. And

2:16

it took about 30 seconds before I saw things

2:18

that made me pretty uncomfortable. I

2:21

was just seeing stuff I should not be seeing. I

2:23

don't know the most delicate way to say this, except

2:27

people I knew had compromising stuff on

2:30

the internet. Stuff

2:34

they had put there, but not under

2:36

their real names. And I don't

2:38

think they knew, I certainly hadn't known, that

2:40

the technology to search someone's face was right

2:43

around the corner. I

2:47

decided to stop using the search engine. The

2:50

line between general internet curiosity and

2:52

stalking, this felt like the wrong side of

2:55

it. It felt seedy. But now, even

2:58

just knowing this tool existed changed

3:00

how I thought in the real world. I

3:03

found myself trying to reach for it. The way any

3:05

digital tool that works begins to feel like another

3:07

limb. I found a driver's

3:09

license on the floor of a dance club. The

3:12

person had a name too common to Google,

3:14

like Jane Smith. But I realized, you

3:16

just find their face with the search engine. Another

3:19

night, two people at a restaurant were talking. One

3:22

of them, the guy, sounded like

3:24

a very personal story about the vice

3:26

president of America. Who

3:28

was this guy? I realized, if I

3:31

snapped a photo of him, I now

3:33

had the ability to know. We

3:35

take for granted the idea that we have a degree of

3:37

privacy in public, that we are mostly

3:40

anonymous to the strangers we pass. I

3:42

realized, this just wasn't true anymore.

3:48

Right now, there are a lot of discussions about AI

3:51

chatbots, about the ethics and problems

3:53

of a very powerful new technology.

3:57

I feel like we should also be talking about

3:59

this technology. these search engines because

4:01

my feeling using one was we

4:04

are not at all ready for this. This

4:06

thing that is already here.

4:08

And I wanted to know, is it

4:10

too late? Is there a way to stop

4:12

these tools or limit them? And I

4:14

especially wanted to know who

4:17

unleashed this on us. So

4:19

I called the person you call when you have

4:21

questions like this. Can you introduce yourself? Sure.

4:23

I'm Kashmir Hill. I am a technology reporter

4:25

at the New York Times. And I've been

4:27

writing about privacy for more than a decade

4:30

now. Kashmir is one of

4:32

the best privacy and technology reporters in

4:34

America. She published a book a few

4:36

months ago about these search engines and

4:38

about the very strange story of how

4:40

she discovered that they even existed. It's

4:42

called appropriately, your face

4:44

belongs to us. Her

4:47

reporting follows a company called Clearview AI, which

4:49

is not the search engine I was referencing

4:51

before. Clearview AI is actually much

4:53

more powerful and not available

4:55

to the public. But

4:57

in many ways, Clearview created the blueprint for

4:59

copycats like the one I'd found. Kashmir

5:02

told me the story of when she learned

5:04

of Clearview AI's existence back when the company

5:06

was still in deep stealth mode. So

5:09

I heard about Clearview AI. It was

5:11

November 2019. I was in Switzerland doing

5:13

this kind of fellowship

5:17

there. And I got

5:19

an email from a guy named

5:21

Freddy Martinez, who worked

5:23

for a nonprofit called Open the

5:25

Government. And he does public

5:27

records research. And he's obsessed

5:29

with privacy and security as I am. And I've known

5:32

him for years. And he sent me

5:34

this email saying, I found

5:36

out about this company that's crossed the

5:38

Rubicon on facial recognition. That's how we

5:40

put it. He said he'd gotten this

5:43

public records response from the Atlanta

5:45

Police Department describing this facial recognition

5:48

technology they were using. And

5:50

he said, it's not like anything I've seen before. They're

5:53

selling our Facebook photos to the cops.

5:56

And he had attached the PDF he got

5:58

from the Atlanta Police Department. It was was 26 pages. And

6:02

when I opened it up, the

6:04

first page was labeled

6:06

privileged and confidential. And

6:09

it was this memo written by

6:11

Paul Clement, whose name I recognize, because he's

6:13

kind of a big deal lawyer, was solicitor

6:16

general under George Bush, now in private practice.

6:18

And he was talking about the

6:20

legal implications of Clearview AI. And

6:23

he's describing it as this company that

6:25

has scraped billions of photos from the

6:28

public web, including social media sites, in

6:30

order to produce a spatial recognition app where you

6:32

take a photo of somebody and it returns all

6:35

the other places on the internet where

6:37

their photo appears. And he said,

6:39

we've used it our firm. It returns

6:41

fast and reliable results. It works with something

6:43

like 99% accuracy. There's

6:46

hundreds of law enforcement agencies that are

6:48

already using it. And he

6:50

had written this memo to reassure any police

6:53

who wanted to use it that they wouldn't

6:55

be breaking federal or state privacy laws

6:57

by doing so. And

6:59

then there was a brochure for Clearview

7:01

that said, stop searching, start solving, and

7:04

that it was a Google for faces. And

7:06

as I'm reading it, I'm just like, wow,

7:10

how have I never heard of this company before? Why

7:13

is this company doing this and not Google

7:15

or Facebook? And does

7:18

this actually work? Is this real?

7:20

Because it is violating things that I

7:22

have been hearing from the tech industry for

7:24

years now about

7:27

what should be done about facial recognition technology.

7:30

I flashback to this workshop I've

7:32

gone to in DC organized by the Federal

7:34

Trade Commission, which is kind of our de

7:37

facto privacy regulator in the United States. And

7:39

they had a bunch of what we call stakeholders

7:42

there. Google was there. Facebook was there. Little

7:44

startups, privacy advocates, civil

7:47

society organizations, academics. Good

7:49

morning, and I want to welcome all of you, both

7:51

here in Washington, DC and those

7:54

watching online, To

7:56

Today's Workshop on Facial recognition Technology.

7:58

This Workshop That Kashmir. Members it

8:00

happened in Two thousand Eleven is called

8:02

Face Facts or maybe Face Facts. The

8:05

video of the worse up on the

8:07

Ftc. His website shows a string of

8:09

speakers brazilian a podium in front of

8:11

a limp looking American flags. We will

8:14

focus on the commercial use that is

8:16

on the possibilities that these technologies open

8:18

up for consumers are well as as

8:21

their potential threats to privacy. Must you

8:23

know. Admissions The Of.

8:27

The talking about the nitty gritty of facial

8:29

recognition technology. what safeguards need to be put

8:31

in place around the Sec Now see that

8:33

rapidly becoming more powerful and everyone in the

8:35

room had different ideas about what we should

8:38

be doing. you know, group on Facebook that

8:40

point where does tagging friends and thought as

8:42

and there's some people they're saying we need

8:44

to have. Banned this. But there is one

8:46

thing that everybody in the room agreed on

8:48

and now is that nobody said build a

8:50

facial. Recognition at that you could

8:52

use on strangers and identify them

8:55

on the upper South. Avoid

8:57

the one who's case anybody fears which

9:00

has to do in a while and

9:02

then on my people that's the Ceo

9:04

of a facial recognition company and soon

9:06

be acquired by. You

9:08

saying they had to prevent the use

9:10

case? no one wanted Sam to faces

9:13

for the input and try to thing

9:15

is Barb. Photos. And

9:18

the people that you want to. To. Have identified

9:20

know over the back. So.

9:24

Apartment mother of and wouldn't do not

9:27

know about Martha. Faith is this is

9:29

one thing that we wanted to make

9:31

sure that doesn't help. And. So

9:33

now I'm looking at this memo

9:35

that says that has happened. Rice

9:37

and. So yeah, I was very soft

9:39

and I told Friday I'm deathly gonna look

9:41

into this like a suicide attack the United

9:43

States. And that's when I did. so

9:48

at this point in my twenty nineteen

9:50

years which has her knows about clear

9:53

the way i it's supposedly a very

9:55

powerful technology that has great billions of

9:57

photos from the public that And

10:00

it's being used by the Atlanta Police

10:02

Department. She doesn't know who's

10:04

behind the company, but she

10:06

has ideas about how to find them. She

10:08

starts calling their clients. And

10:13

so I reached out to the Atlanta Police Department,

10:15

they never responded. Other FOIA's were

10:17

starting to come in that showed other departments

10:19

using Clearview, and I just

10:21

did a kind of Google dorking

10:23

thing where I searched for Clearview

10:25

and then site.gov to see if

10:28

it showed up on budgets.

10:30

Oh, that's really smart. Yeah, and

10:32

so I started seeing Clearview, and it was really tiny

10:34

amounts, like $2,000, $6,000, but

10:37

it was appearing on budgets around the country. And so

10:39

I would reach out to those police departments and

10:41

say, hey, I'm looking to Clearview AI, I

10:43

saw that you're paying for it, would you talk to me? And

10:47

eventually, the first

10:49

people to call me back were

10:51

the Gainesville Police Department, a detective

10:53

there named Nick Ferrara. He's

10:56

a financial crimes detective, and he

10:58

calls me up on my phone. He said, oh, hey, I

11:00

heard that you're working on a story

11:02

about Clearview AI, I'd be happy to talk to

11:04

you about it. It's a great tool. It's

11:07

amazing. And he said he would be the

11:09

spokesperson for the company if they wanted. So he

11:11

told him, he's just like, this is great. He

11:13

loved it. He said he had a stack of unsolved

11:16

cases on his desk where he had a photo of

11:18

the person he was looking for, like a fraudster,

11:21

and he'd run it through the state facial recognition system,

11:23

not gone to anything. And he said he ran it

11:25

through Clearview AI, and he got hit after hit. And

11:28

he just said it was this really powerful tool.

11:30

It worked like no facial recognition he'd used before.

11:33

The person could be wearing a hat, glasses, looking

11:35

away from the camera, and he was still getting

11:38

these results. And this is sort of the positive

11:40

case for any of this, which is that if

11:43

a dangerous person who has committed violent

11:45

crimes is out in the world, and

11:47

there's some photo of them where maybe

11:49

they were like robbing a bank, and their mouth was

11:51

covered, and there's a hat low over their head, and

11:53

if a cop can take that surveillance

11:56

cell, plug it into a big machine, and

11:58

find this person's name. we live in

12:00

a safer world. Right. This is the

12:02

ideal use case. Yeah. Solving crimes, finding

12:04

people who committed crimes, bringing them to

12:07

justice. Yeah. And so Nick Ferrara,

12:09

this detective, said, yeah, it works incredibly well. And I

12:11

said, well, I'd love to see what the results look

12:13

like. I've never kind of seen a search like this

12:15

before. And he said, well, I can't

12:17

send you something from one of my investigations, but

12:19

why don't you send me your photo, and I'll

12:21

run you through Clearview, and I'll send you the

12:24

results. So I do that. I send some photos

12:26

of myself. How do you pick the photos? I

12:28

tried to choose hard photos. So I had

12:31

one where my eyes were closed, one

12:33

where I was wearing a hat and sunglasses, and

12:36

another that was kind of like an easy photo, in case

12:38

those other two didn't work. And

12:40

then I waited to hear how it went, and

12:43

see for myself how well this software works. And

12:46

Nick Ferrara ghost me. He

12:49

just totally disappears. Disappears. Won't

12:52

pick up when I call him. Doesn't respond

12:54

to my email. Cashmere

12:56

says she tried this again with a

12:58

different police officer in a different department,

13:01

and the same thing happened. They were friendly at first.

13:04

Cashmere asked them to run a search on her

13:06

face. They agreed. And then they were

13:09

gone. And so eventually,

13:11

I kind of recruited a

13:14

detective in

13:16

Texas, a police detective, who

13:19

was kind of a friend of

13:21

a friend at the Times, and said, oh,

13:23

you're looking at this company. I'm happy to download the

13:26

tool, tell you what it's like. And

13:28

so he requests a trial of Clearview.

13:30

And at this point, Clearview was just

13:32

giving out free trials to any police

13:34

officer, as long as they had an

13:36

email address associated with the department. And

13:39

so- It's what Facebook did when they first

13:41

opened up with College Campuses. Yeah, exactly. It

13:45

was exclusive, just for government workers. And

13:48

so he goes to their website, where

13:50

he can request a trial. Within 30

13:52

minutes, he's got Clearview on his phone. And

13:55

he starts testing it, running it on

13:57

some suspects whose identity he knows. And

13:59

it works. He tried it on himself,

14:01

and he kind of had purposely not put

14:03

a lot of photos of himself online because

14:06

he was worried about exposure and people coming

14:08

after him who he had been

14:10

involved in catching, sending to jail.

14:13

And it worked for him. It found this

14:15

photo of him on Twitter, where he was

14:17

in the background of someone else's photo, and

14:19

he had been on patrol, so it actually had

14:21

his name tag on it. So it would have been

14:24

a way to get from his face to his name.

14:27

And he immediately thought, wow, this is

14:29

so powerful for investigators, but it's going to

14:31

be a huge problem for undercover officers. If

14:34

they have any photos online, it's going to be a way to

14:36

figure out who they are. And

14:39

so I told him about my experience with other

14:41

officers running my photo, and he ran my

14:44

photo. And there weren't

14:46

any results, which was weird because I have a lot of

14:48

photos online. Like, it just came up like nothing.

14:52

Nothing. And then within

14:54

minutes, he gets a call from

14:56

an unknown

14:58

number, and when he picks up, the person says, this

15:00

is Marco with Clearview AI

15:03

tech support, and we have some questions

15:05

about a search that you just did. Oh, my God.

15:08

And he says, why are you running photos of this

15:10

lady from the New York Times? And

15:12

the detective kind of plays it cool. And

15:14

he's like, oh, I'm just testing out the

15:16

software. How would I know somebody in New

15:18

York? I'm in Texas. And anyways, his account

15:21

gets suspended. Oh, wow. And this

15:23

is how I realized that even though Clearview

15:25

is not talking to me, they have put

15:27

an alert on my face. And

15:29

every time an officer has run my

15:32

photo, they've gotten a call

15:34

from Clearview telling them not to talk to me. Just

15:41

to spell out what Kashmir believed was

15:43

going on here, these police officers may

15:45

have thought they were using a normal

15:47

search engine like Google. But

15:50

what they hadn't counted on was that someone

15:52

on the other end of that search engine

15:54

seemed to be watching their searches, surveilling

15:57

the cops who were using the surveillance

15:59

technology. It was

16:01

a moment where Kashmir saw clearly how this

16:03

mysterious company, by being the first to build

16:06

this tool no one else would, had granted

16:08

itself immense power to monitor

16:10

Kashmir, to monitor these cops. This

16:13

company, whose product would reduce the average

16:15

American's privacy, was keeping quite a

16:18

lot of privacy for itself. Of

16:20

course, Kashmir is fortunately for us a

16:22

nosy reporter, so all this cloak and

16:24

dagger behavior just made her more curious.

16:27

She tries to crack into the company a bunch of different

16:29

ways. She's reaching out to

16:31

anybody online who might have links to the company. She

16:34

finds an address listed on Clearview AI's

16:37

website. It's in Manhattan. But

16:39

when she goes there in person, there's

16:42

no such address. The building

16:44

itself does not exist. It's a real

16:46

Harry Potter moment. Finally,

16:48

she tries something that does work. On

16:51

the website Pitchbook, she can see two

16:53

of Clearview AI's investors. Peter

16:55

Thiel. No luck there. But

16:58

also an investment firm based in New York.

17:05

They're north of the city, and

17:07

they weren't responding to emails or phone calls. So

17:10

I got on the Metro North and went up

17:12

to their office to see if they had a

17:14

real office. And it was

17:16

kind of an adventure being there. The office was

17:18

empty. All their neighbors said they never came in.

17:21

I kind of hung out in the hallway for

17:23

about an hour. A FedEx guy came. He dropped

17:25

off the box. He says, oh, they're never here. And I

17:27

thought, oh, my gosh, this is a waste of a

17:29

trip. But then I'm walking out

17:32

of the building. And it was on

17:34

the second floor. And I'm coming down the stairs. And these two

17:36

guys walk in. And they

17:38

were wearing lavender and pink. And they

17:40

just looked like moneyed. They

17:43

stood out. And I said, oh, are

17:45

you with Kiranaga Partners, which is the name of

17:47

this investment firm? And they look up and

17:49

they smile at me. And they say, yeah, we are. Who are

17:51

you? And I said, I'm Kashmir Hill. I'm

17:53

a New York Times reporter who's been trying to get in touch

17:55

with you. And

17:58

their faces just fall. I said, I

18:00

want to talk to you about Clearview AI. And

18:02

they said, well, Clearview AI's lawyer said that we're not supposed

18:04

to talk to you. And

18:08

I was around seven months pregnant at this time. And

18:10

so I kind of opened my jacket

18:12

and just clearly just lay my

18:15

enormous belly. And I was like, oh, I've

18:17

come so far. It was cold. It was raining

18:19

out. And David

18:21

Scalzo, who's the main guy, main investor

18:23

in Clearview at Kiranaga, he says, OK. So

18:28

Cashmere and the two investors go inside the

18:30

office. Cashmere tells them all

18:33

this not talking. It's making

18:35

Clearview AI look pretty nefarious. She

18:39

has a point. And so one

18:41

of them agrees to go on the record and starts

18:43

talking about his vision for the company that he has

18:45

invested in. David Scalzo

18:47

said, right now, they're just selling

18:49

this to kind of like retailers

18:52

and police departments. But

18:55

our hope is that one day, everybody

18:57

has access to Clearview. And

18:59

the same way that you Google someone,

19:01

you'll Clearview their face and be able to see

19:04

all the photos of them online. He says, yeah, I

19:06

think we think this company is going to be huge.

19:09

And now they give Cashmere the information

19:12

that she'd really been looking for, the

19:14

names of the people who are actually

19:16

responsible for this tool. And

19:19

they said, oh, yeah, we're really excited

19:21

about the founders. And they

19:23

say it's this guy, Richard Schwartz, who's

19:25

kind of a media politics guy, worked

19:28

for Rudy Giuliani when he was mayor.

19:30

And then there's this tech genius, real

19:33

mastermind, young guy. And

19:35

his name's Juan Tontat. And

19:38

we're in a conference room. So I'm like,

19:40

can you write that up on a whiteboard

19:42

for me? How do you spell Juan Tontat?

19:44

And so he writes it out. And

19:46

this is the first time I figure out who

19:49

the people are behind this. After

19:53

the break, the story of how Juan

19:56

Tontat and his engineers got your face

19:58

and my face and 3

20:00

billion photos worth of faces into

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and conditions apply. Night

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search on turned out to learn

22:41

to find had an internet trail.

22:43

This guitar you're hearing part of

22:45

the trail one had a habit

22:48

in one chapter Recife opposing you

22:50

tube videos of himself pretty capably

22:52

playing guitar solos in the videos.

22:54

He doesn't speak but his cm

22:57

tall and slender with long black

22:59

hair fashionable one has the admins

23:01

roots. Raised in Australia, he moved

23:04

to San Francisco in two thousand

23:06

seven. His internet breadcrumbs. Suggest a

23:08

strange cause if a person a

23:10

Bay Area tech guy who presents

23:12

add slightly gender fluid way has

23:14

photos from Burning Man but I'm

23:16

also seems like a bit of

23:18

a troll in a Twitter bio

23:20

he claims to be a quote

23:23

Anarcho Transsexual Afro to Cano American

23:25

Feminists Studies major. What?

23:27

Is clear is that Wanna come to America

23:29

with big dreams of getting rich on the

23:31

internet? He

23:35

started in the Farm Bill era of

23:37

a spec ops when you could make

23:39

money building the right stupid thing online.

23:41

Nothing he tried really took off. so

23:43

not apps like friend quiz or romantic

23:45

guess not later efforts like an app

23:47

the took an image of you and

23:49

photo shopped Trump's hair on your head.

23:52

In twenty six seen one would move to

23:54

New York at some point you delete my

23:57

service or some yes, a cashmere and an

23:59

old artifact as. who he was on

24:01

the internet back then. I found

24:03

an archived page of his from

24:05

Twitter on the way back machine.

24:08

And it was mostly him kind

24:10

of retweeting like

24:12

Breitbart reporters and

24:15

kind of saying, why are all the big cities

24:17

so liberal? Yeah. He doesn't have a Twitter

24:19

account. He doesn't have a Facebook account. It

24:21

seemed like, wow, this is weird. Like this guy

24:24

is in his 20s, I think. But he doesn't

24:26

have a social media presence beyond

24:28

like a Spotify account with some songs

24:31

that he apparently had done. It was

24:33

a strange portrait. But it came away

24:35

thinking, wow, this person is a character.

24:38

And I really want to meet him. At

24:40

this point, it seemed like the company understood that

24:42

Cashmere Hill was not going to go away. A

24:46

crisis communications consultant reached out and

24:48

eventually offered to arrange an interview with

24:51

Juan Tontet. When I met

24:53

him, he was not what I expected him to be, which

24:55

was he still had the long black hair.

24:58

But now he had these glasses that

25:00

felt very like office worker glasses. And

25:02

he was wearing this blue suit. And he just looked

25:04

like a security startup CEO. OK.

25:08

Which just, again, wasn't what I

25:10

expected based on everything else I saw about him.

25:12

We met at a WeWork because

25:14

they didn't have an office. I would find

25:16

out that he mostly kind of worked remotely,

25:19

did a lot of the building of Clearview AI. At

25:21

the time, he lives in the East Village. And he

25:23

kind of just did it in cafes, like places with

25:25

free Wi-Fi. So they

25:28

booked a room at WeWork for our

25:30

meeting. The crisis communications consultant was there.

25:32

She'd brought cookies. What type of

25:34

cookies? Chocolate chip. And

25:37

I feel like they were Nantucket or

25:39

like Sausalito cookies. I can't remember the brand.

25:42

But yeah, we had lattes at

25:44

the WeWork cafe. And we sat down. And

25:47

I just started asking my questions. And for

25:50

the most part, he's answering them. And

25:52

we had a couple of hours

25:55

to talk. And he

25:57

really was telling me a lot. And so it was

25:59

just a lot. The complete one eighty.

26:04

In person is very charismatic,

26:06

very open, And would

26:08

be evasive about some things. Wouldn't

26:10

describe any one else involved as

26:12

the company besides Richer Schwartz is

26:14

cofounder be I avenues open and

26:16

I was like you have built

26:18

this astounding technology like how did

26:21

you do this. How did you go

26:23

from what you're telling me about this book?

26:25

apps and. I phone games

26:27

to building this they said well. So

26:30

standing on the shoulders of Giants. And

26:33

he said to spend this

26:35

real revolution in Ai and

26:37

neural networks. Ah a lot

26:39

of research that have the

26:41

most brilliant minds in the

26:43

world have done these open.

26:45

Sourced know they've put it on the

26:47

internet. Want old cashmere? That in Twenty

26:50

Six team in the early days of

26:52

building what would become the Clear View

26:54

I facial search engine. He taught himself

26:56

the rudiments of a i assisted facial

26:59

recognition by just essentially googling them. He's

27:01

on Get Hub and I didn't face

27:03

recognition to read papers by experts in

27:06

the field. He told her quote.

27:08

Is gonna sound like I googled flying car

27:10

and and sound instructions on it. Which

27:13

wasn't too far off until pretty

27:16

recently. Facial recognition existed, but was

27:18

somewhat crude, What

27:20

one was learning on the Internet

27:22

was at machine learning. Neural networks

27:24

have just changed all that now.

27:27

computers could teach themselves dressing as

27:29

face, even at an odd angle.

27:31

Even with a beard provided to

27:33

the computer was given enough images

27:35

of faces training data to learn

27:37

on. We reached out

27:39

to Clear View Ai for the story. We didn't get

27:41

a response. But in the years since. His interview

27:43

a cashmere quarters and plenty of interviews with

27:46

the press. One

27:48

thing I do respect as a fact that you decided to

27:50

come here are like for an interview cyprus his supporters of

27:52

its on. and thanks path for having

27:54

me on awarded for here's one with the

27:57

you tube show valued payments fine stress as

27:59

us of kashmir in a suit, looking again

28:01

like a standard tech exact, just with unusually

28:03

long hair. Here he

28:05

describes what his research process for this search

28:07

engine was like. I was looking at

28:09

the advances in AI. So I

28:11

saw ImageNet, which is a competition for recognizing

28:14

things in images. Is this a computer? Is

28:16

this a plant? Is this a dog or

28:18

a cat? And the results got really good.

28:20

And then I looked at facial recognition, and

28:22

we'd read papers. So Google had Facebook

28:25

both had deep learning papers on

28:27

facial recognition. And then, hey, can I

28:29

get this working on my computer? And we

28:31

ended up getting it working. And what

28:33

we realized was getting more data to

28:35

train the algorithm, to make it accurate

28:37

across all ethnicities, Iranian people, black people,

28:39

white people, brown people. That was really

28:42

key to improving performance. This

28:44

would be Juan's real innovation, a somewhat

28:47

dark one. His advantage was

28:49

how he would find the training data he

28:51

needed. He built a scraper,

28:53

a tool that would take, without asking, photos

28:56

of human faces pretty much anywhere on the public

28:58

internet they could be nabbed. He

29:00

also hired people who built their own

29:02

scrapers to hoover up even more photos.

29:05

He said part of our magic here

29:07

is that we collected so many photos. And he

29:09

built the scraper. He hired people

29:11

from around the world to help him

29:13

collect photos. And so it's

29:16

similar to, like when people talk about

29:18

large language models right now and companies

29:20

like OpenAI, some of what

29:22

they're doing is tuning their neural networks. But a lot

29:24

of what they're doing is feeding their neural networks. It's

29:26

like they have to find every text that's ever been

29:28

published in every library and then they run out of

29:30

all the library text and they have to find transcripts

29:34

of YouTube videos which maybe they shouldn't be

29:36

loading in there. It's part of what he

29:38

had done correctly to get his product ahead

29:40

of where the other ones were. It's

29:42

just like he was not a genius at making

29:44

the underlying AI. That was

29:47

mostly open source. He was passionate about finding

29:49

faces on the internet to put into it.

29:51

Yes. And so where was he

29:53

looking? Oh man. So the first place

29:55

he got faces was Venmo. This is funny to

29:57

me because as a privacy journalist, I really love

30:00

it. remembered people being upset

30:02

at Vemo's approach to privacy, which at

30:04

the time was, if you signed up

30:06

for Vemo, your account was public by

30:08

default. And your profile photo

30:10

was public by default. And so he built

30:13

this scraper, you know, this

30:15

bot that would just visit vemo.com every

30:17

few seconds. And Vemo

30:19

at the time had a real-time feed

30:21

of all the transactions that were happening

30:24

on the network. And so he would

30:26

just hit Vemo every few seconds and

30:28

download the profile photo, the link to

30:30

the Vemo profile. And he got

30:32

just millions of photos this way from Vemo

30:34

alone. And this is essentially

30:36

what he was doing, but with, I

30:39

mean, thousands, millions of

30:41

sites on the internet, Facebook, LinkedIn,

30:43

Instagram, employment sites, yeah, just anywhere

30:45

they could think of where there

30:47

might be photos. I

30:52

just want to butt in here to say all of

30:54

this is completely astonishing. I

30:57

know people at the dawn of social media

30:59

who just didn't want to join Facebook or

31:01

didn't understand why you would voluntarily offer your

31:04

private life to the public, but

31:06

I don't think anyone, or at least anyone

31:09

I knew, had an imagination

31:11

sufficiently tuned to Dystopia to know

31:13

that if you had the

31:15

brazenness to upload your photo to Vemo or

31:18

to LinkedIn, you could one day

31:20

be feeding your face into a machine. A

31:22

machine that today, if you go to a protest,

31:25

is capable of using a photo of

31:27

your face to find your name, your

31:30

email, your employer, even your physical address.

31:33

Who knew this was the future we were fumbling our

31:35

way towards? I asked Kashmir

31:37

about all this. I

31:40

use Venmo, I use Facebook. I'm

31:43

barely sure that when I signed up, I signed in

31:45

terms of service. I did not read it carefully. I

31:47

don't think there was a section in there, like, okaying

31:49

that my face could be used in photo-scraping software. Is

31:52

what he did legal? So

31:54

Venmo and Facebook both sent

31:56

Clearview AI cease and desist

31:59

letters saying... stop scraping our sites

32:01

and erase the photos that you took, delete the

32:03

photos that you took, but they

32:05

never sued. So this hasn't been tested in court,

32:07

whether it's illegal or not. So it's still a

32:10

bit of a gray area and it

32:12

hasn't been tested with Clearview because none

32:14

of these companies have sued them. In

32:18

one interview, shot just a month after his

32:20

conversation with Cashmere, Juan sat down with a

32:23

CNN reporter who asked about this, the legality

32:25

of his project. Is everything

32:27

you're doing legal? Yes, it is. So

32:30

we've gone through and have

32:32

some of the best legal counsel from Paul Clement,

32:34

who used to be the Solicitor General of the

32:36

United States. He's done over 100

32:39

cases in front of the Supreme Court.

32:41

And he did a study independently saying

32:44

this is not, the way it's used

32:46

is in compliance with the Fourth

32:48

Amendment. All the information we get is publicly

32:50

available, and we have a First Amendment right

32:52

to have public information on the internet. And

32:55

you have to understand what it's also being

32:57

used for. We're not just taking your information

32:59

and selling ads with it or trying to

33:01

get more. We're actually

33:03

helping solve crimes with this. So

33:06

your counsel is making the argument

33:08

that there's a First Amendment right

33:10

to information that is publicly on

33:12

the internet? Yes. And so

33:15

if you take something like Google, Google

33:17

crawls the internet, collects all these web pages,

33:19

and you search it with keyword terms, we're the

33:21

same thing. You take all this information on public

33:23

web pages that search it with a face. Juan's

33:27

making a pretty radical argument here, even though

33:29

his tone doesn't suggest it. He's

33:31

saying that someone being able to take your

33:33

face and use it to make a search

33:35

that will pull up your name, possibly your

33:37

address and more, is nothing new. It's

33:40

just like Google. His

33:43

point is that Google collects every instance of your

33:45

name on the internet. Clearview AI is

33:47

just doing that, but with your face. And

33:49

you know, attaching it to your name. Whether

33:53

you agree with this idea or not, it

33:55

has happened and it has fundamentally

33:57

changed how privacy works. Kazmir

34:00

says that most of us are just not prepared for

34:02

this brave new world. I just

34:04

don't think that most people anticipated

34:07

that the whole internet was

34:09

going to be reorganized around your face.

34:12

Right. And so a lot of people

34:14

haven't been that careful about the kind of photos they're in

34:16

or the kind of photos they've put up of themselves

34:18

or the kind of photos they've allowed to be put

34:20

up of themselves. And Juan

34:23

actually did a clear view search of me there.

34:26

And I said, oh, well, last time this happened, there were

34:28

no results for me. And he said, oh, there must have

34:31

been some kind of bug. He wouldn't

34:33

admit that they had put this alert on my face,

34:35

that they had changed my results. But

34:37

he ran my face and there were just tons

34:39

of photos, like lots of photos I knew about.

34:43

But in one case, there was a photo of me at an

34:45

event with a source. And I was like,

34:47

wow, I didn't realize. I hadn't thought that through

34:49

now that if I'm out in public with a

34:51

sensitive source and somebody takes a photo and puts

34:53

that on the internet, that could be a way

34:55

of exposing who my sources are. And

34:59

it was really stunning how

35:01

powerful it was. For me, there were

35:03

dozens, if not hundreds of photos. Me

35:06

kind of in the background of other people's photos.

35:08

I remember there were, I used to live in

35:10

Washington, D.C. and there were photos of me at

35:12

the Black Cat, which is a concert venue, just

35:14

in the crowd at the show. It

35:17

was incredibly powerful. And

35:19

I remember asking him, I was like,

35:21

you've taken this software somewhere no one

35:23

has before. You have created this really

35:26

powerful tool that can

35:29

identify anybody. All these photos of them,

35:32

you're just selling it to law enforcement. But now that

35:34

you've built this and you've described to me the

35:36

accessibility of building this, there's going to be

35:39

copycats. And this is going

35:41

to change anonymity, privacy as we know

35:43

it. What do you think about that? And

35:47

I remember he kind of was silent for a little

35:49

bit and he said, that's a really good question. I'll

35:51

have to think about it. And it was just

35:54

this stunning moment of seeing in

35:56

action people that are making these

35:58

really powerful technologies who really just. are

36:00

not thinking about the implications, who are just

36:02

thinking, how do I build this? How do

36:04

I sell this? How do I make this

36:06

a success? Since

36:10

Ron's interview with Cashmere, it

36:12

seems like maybe he's had more time to think

36:14

through better answers to hard questions. We've

36:16

watched a lot of these subsequent interviews. What

36:19

you notice is that now, he'll say

36:21

that as long as he's CEO, he'll make sure

36:23

his tool is only ever in the hands of

36:25

law enforcement, and in some cases, banks. And

36:28

he'll point again and again to

36:30

the one strong reason why Clearview AI

36:32

does need to exist. Without Clearview AI,

36:34

there are so many cases of child

36:36

molesters that would have never been caught,

36:38

or children who wouldn't have been saved.

36:41

Child predator will be extorting children

36:43

online. You don't even know about it. Sex

36:45

torsion, child abuse, child abuser, crime crimes against

36:48

children, dark web, troves and troves of children's

36:50

faces. These are kids that would have been

36:52

identified. This is why our customers

36:54

are very passionate about keeping the technology and making

36:56

sure it's used properly.

37:00

It's hard to take the other side of

37:02

that argument, but of course, Clearview AI is

37:05

not just being marketed as an anti-child predator

37:07

tool. A Clearview AI investor told

37:09

Cashmere he hoped one day it would be in

37:11

the hands of regular people, and potential

37:13

investors in the company were given the tool

37:15

to use on their phones, like just

37:18

to use as a party trick. Will

37:20

Clearview AI actually ultimately roll this tool

37:22

out for wide use? Well,

37:25

it sort of doesn't matter whether they do or not. Because

37:32

remember, the copycats already have.

37:36

After the break, how people are using

37:38

and abusing this technology. Great.

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40:29

you leave that conversation at that point, do you

40:31

write your story? Yeah, I think

40:33

the story came out about a week after that

40:35

interview. And what was the response to the story?

40:37

Did people understand the size of the thing? Yeah,

40:40

so it was a front page Sunday story,

40:42

they call it a bulldog story when you're

40:44

Sunday A1. A bulldog

40:46

story? Yeah, a bulldog heave because you open the paper and

40:49

then it was the whole spread on the inside as well.

40:51

And it was a big deal. I remember

40:53

it landed and my phone was just blowing

40:56

up because I was being tagged. This is back

40:58

when Twitter was still a healthy

41:01

space for conversation. So my Twitter is blowing

41:03

up. I'm getting all these emails. People want

41:05

to book me to talk about it on

41:07

TV on the radio. Like it was just

41:09

this huge deal. People were stunned

41:12

that it existed, that it

41:14

was using their photos without

41:16

consent. Just the way Clavio

41:18

had gone about it, the fact that they had

41:20

surveilled me as a journalist tried to prevent

41:22

the reporting on the story. It was

41:25

a huge deal. I thought this is going to be one of

41:27

the biggest stories of the year. This

41:31

is January 2020. I

41:35

see. Shit.

41:37

So the pandemic happens and

41:40

does it just kind of

41:42

like... Yeah,

41:47

like I was hearing that there were

41:49

going to be hearings in DC.

41:52

They start getting cease and desist

41:54

letters, lawsuits happen, but then March

41:56

2020 COVID hits and it just

41:59

instantly changed the country. conversation in the U.S.

42:01

and around the world to

42:03

health concerns, safety concerns. And

42:06

then I started seeing people talking about, can

42:08

we use facial recognition technology to fight COVID?

42:10

Can we start tracking people's faces? See

42:13

where people were with other people,

42:15

if there's a known exposure. Can

42:18

we track people? And there's this

42:20

talk about, yeah, using facial recognition

42:22

technology. So it's like

42:24

we almost skipped the scared outrage phase

42:26

of the technology because the needle

42:30

kind of juttered on everything with COVID? Yeah,

42:32

we did a little bit. I mean, for certain

42:35

groups like European privacy regulators, they all

42:37

launched investigations into Clearview and they

42:39

essentially kicked Clearview out of their countries.

42:41

They said it was illegal. I mean, there were

42:43

repercussions for Clearview, but I feel like the

42:45

bigger conversation, what do we do about this

42:48

right now? It just it

42:50

got pushed aside by that larger concern around

42:52

COVID. Somehow our debate

42:54

about these search engines was just one

42:56

of the infinite strange casualties of COVID,

42:59

a conversation we never quite got to have. In

43:02

the meantime, Clearview AI's copycats have continued to

43:04

go further than the company itself, offering

43:07

their search engines online for the public to use at

43:09

a small cost. None of these

43:12

search engines is as powerful as Clearview, but

43:14

all of them are powerful enough to do

43:16

what privacy advocates were worried about back in

43:18

2011. The tool

43:20

I would end up finding online was one of those

43:22

copycats. I have been noticing

43:24

more and more people using them, mainly to

43:26

settle scores with strangers on social media. I

43:30

asked Kashmir where she has noticed people using

43:32

these search engines in the wild since she

43:34

published her book. I've

43:36

seen news organizations using it. One of

43:38

the more controversial uses was a news

43:41

organization that used it after October 7th

43:43

to try to identify the people who

43:45

were involved in the attacks on Israel.

43:47

Oh, wow. And I was a little

43:50

surprised to see it used that way.

43:52

Why were you surprised? I was

43:54

surprised just because it's still

43:57

controversial, whether we should be

44:00

using face recognition this way. And

44:02

the same site that was

44:04

using it had published stories about how controversial

44:06

it is. That there were these search

44:08

engines that have scraped the public web, and

44:11

that they invade privacy. Yeah, so

44:13

I think it's still complicated. It was

44:15

a news outlet that had done, maybe we shouldn't

44:17

have the stories, and then they were also using

44:19

the tech. Yeah, like maybe

44:21

this technology shouldn't exist, but also it's

44:23

there, so we're going to use it. Which sort of reveals

44:25

the story of every piece of technology we've ever had a

44:27

stomach ache about, which is, we say we don't want it

44:30

to exist. And then some contingent

44:32

circumstances arises in which at least some of us

44:34

feel like, well, it's OK for me to use

44:36

this here, and if I don't think it

44:38

should exist. Case by case basis.

44:41

I did ask Kashmir whether she'd seen these

44:43

search engines used in a clearly positive way.

44:47

I've heard of people using it on dating sites to

44:49

figure out if the person they're talking

44:51

to is legit. Make sure

44:54

they're not being catfished. Make sure this person

44:57

is who they say they are. I've heard

44:59

about it being used by

45:01

people who have compromising

45:03

material on the internet. Say they

45:05

have an OnlyFans or something

45:08

they don't want to exist on the internet, and

45:10

they've used these search engines to figure out how

45:12

exposed they are. And some of

45:14

the search engines do let you remove results.

45:16

And so they've done that. They've gotten rid

45:18

of the links to stuff

45:20

they don't want the world to know about. I've talked

45:22

to parents who have used these search

45:24

engines to figure out if there's photos

45:26

of their kids on the internet that

45:29

they don't want to be out there.

45:31

Oh, wow. So one woman I talked

45:33

to, she's an influencer. She gets a

45:35

lot of attention, and she didn't want

45:37

it blowing back on her kids. So

45:39

she stopped featuring them in any of her videos,

45:41

and she searched for them with one of these

45:43

search engines and found out that there was a

45:46

new photo of one of her kids. A summer

45:48

camp, I think, that one of the kids had

45:50

gone to had posted photos publicly. And

45:52

so she asked them to take it down. But

45:55

yeah, I mean, there are some positive use

45:57

cases for these engines. What

46:00

Cashmere is saying is that the most positive

46:02

use cases for these search engines might just

46:04

be finding compromising content on

46:06

the internet about yourself first before someone

46:08

else using one of these search engines

46:10

does, which seems like a

46:12

questionable upside. Cashmere has also seen

46:14

facial search engines used in a way that I have

46:17

to say was just breathtaking in

46:19

its pettiness. She recently

46:21

reported on how the owner of Madison Square

46:23

Garden was using facial recognition

46:25

and surveillance to ban from

46:28

the venue anyone who worked at

46:30

the law firm his venue was in litigation

46:32

with. Cashmere even tested

46:34

this. She tried to go see a

46:36

hockey game with a personal injury lawyer, something one used

46:38

to be able to do freely. So

46:40

I bought tickets to a Rangers game

46:43

and brought along this personal injury attorney whose

46:45

firm was on the ban list just because

46:47

I wanted to see this firm

46:49

myself. And yeah, so I met

46:52

her. I was meeting her for the first time that night. We

46:54

stood in line. Thank you. Just

46:56

the ticket? Yeah. Just, I

46:58

see the seat. There we go. We were

47:00

walking in. We put

47:03

our bags down on the conveyor belt

47:06

and just thousands of people streaming into Madison Square

47:08

Garden. But by the time we picked them up,

47:10

a security guard walked over to us. He

47:13

said, I need to see some ID from

47:15

her. She shows her driver's license. And he said, you're

47:17

going to have to wait here. Just give

47:19

me one moment. So I said that actually you stand

47:21

by. Management just has to come see you through. And

47:24

we appreciate your patience. Just hang out for me. Okay. A

47:27

couple minutes to go. We'll get someone down to talk

47:29

to. And Amanda came over and gave her this note

47:31

and told her she wasn't allowed to come in. Wow.

47:34

She had to leave. Where the firm is

47:36

involved with your family. Legal act,

47:38

here we go. You're from the

47:40

girl's line. It was insane to

47:42

see just how well

47:44

this works on people just in the real

47:47

world walking around. Yeah. It was

47:49

so fast. God, that's crazy. When

47:52

Kashmir reported this story, she actually

47:54

heard from facial recognition companies who said they

47:56

were upset that Madison Square and was doing

47:59

this. It was making their tools

48:01

look bad. It was not how they said they were

48:03

supposed to be used. But misuse

48:05

of any technology, it's almost a given.

48:08

And facial recognition is being misused

48:10

not just by corporations, but also

48:12

by individuals. So there

48:14

was a TikTok account where

48:17

the person who ran it, if somebody

48:19

kind of went a little viral on

48:21

TikTok, he would find out who they

48:23

were and expose them. The one video

48:26

that really struck me is during

48:28

the Canadian wildfires when New York City kind

48:30

of turned to orange. Somebody

48:33

had done a TikTok that

48:35

just showed Brooklyn and

48:38

what it looked like. It looked like something from

48:40

Blade Runner. And this

48:42

guy walks by and he became

48:44

the hot Brooklyn dad. And so

48:46

the TikTok account found out who

48:48

hot Brooklyn dad was, and

48:51

then found out who his son was.

48:53

Instead, if you want to date somebody

48:55

who's gonna look like hot Brooklyn dad

48:57

one day, here's his son's Instagram account.

49:00

That is wildly bad behavior. That's

49:02

crazy. Cause that person didn't even consent to being

49:04

in the first video, but I'm sure people sent

49:06

it to him and were like, hey, the internet

49:08

thinks you're hot. Don't worry, they don't know who

49:11

you are. And they

49:13

not only invaded his privacy further, but invaded his

49:15

kids' privacy. Yeah, just for fun. And

49:17

so that account was doing a lot of that. And

49:20

404 Media wrote about it and

49:22

eventually TikTok took the account down. I

49:27

mean, the thing that sort of hovers around all

49:29

of this is that prior to the invention of

49:31

these things, it was like the internet had taken

49:34

a lot of everyone's privacy, but the one thing

49:36

we had was the idea that if

49:39

people didn't know your name, or if you

49:42

did something under a pseudonym, there's a degree of

49:44

privacy. And now it's like your face follows you

49:46

in a way it wasn't supposed to. Or

49:49

the internet follows your face, is how I think about

49:51

it. It

49:53

feels like there's a world in which technology like this

49:55

would just be like fingerprint databases

49:57

where law enforcement would have it. that

50:00

the general public wouldn't have access to it.

50:03

Isn't that one way this could be going

50:05

instead of the way it's happening? Yeah,

50:07

that is definitely a possible future outcome,

50:09

where we decide, okay, facial recognition technology

50:11

is incredibly invasive, kind of in the

50:14

same way that wiretapping is. So

50:16

let's only let the government and law

50:19

enforcement have access to this technology legally.

50:22

They're allowed to get a court order or a warrant

50:24

and run a face search in the same way

50:26

that they can tap your phone line with judicial

50:28

approval. And the rest of

50:30

us shouldn't have the right to do it. I think

50:32

that's one way this could go. Seems

50:36

preferable. It

50:39

seems good, but then you also think about governments

50:41

that can abuse that power. So recently

50:44

here in the US, Gaza

50:46

has been such a

50:48

controversial issue and you have people out

50:51

doing protests and there was a lot of

50:53

talk about, well, if you are on

50:55

this side of it, then you're aligned with terrorists and you

50:57

are not gonna get a job. We're

51:00

gonna rescind job offers to college students who are on

51:02

this side of the issue. And it's

51:04

very easy to act on that

51:06

information. Now you can take a photo of that

51:09

crowd of protesters and you can identify every single

51:11

person involved in a protest and then

51:13

you can take their job away. Or if you're

51:15

police and there's a Black Lives Matter protest against

51:17

police brutality, you can take a photo and you

51:19

can know who all those people are. But

51:21

I think you notice now when you see

51:23

photos from the protest, all these students

51:26

are wearing masks. They're wearing COVID masks or

51:28

they're wearing something covering their face and

51:30

it's because they're worried about this. They're

51:32

aware of how easily they can be identified.

51:35

And the thing is it might work,

51:37

but I have tested some of these search engines

51:40

and if the image is

51:42

high resolution enough, even wearing

51:44

a mask, somebody can be identified. Really?

51:47

So just from like nose and eyes

51:49

and forehead? Yes, I did

51:51

this consensually with a photo of

51:53

my colleague, Facilia Kong, who covers

51:56

tech policy in DC.

51:58

She sent me a photo of herself. with a medical mask

52:00

on. I ran it through one of the search engines

52:03

and it found a bunch of photos of her. There's

52:10

a world, you can imagine it, where someone passes

52:12

a law and these tools are no longer offered

52:14

to the public. They become like

52:16

wiretaps, something only the police are allowed

52:18

to use. We would get

52:20

some of our privacy back. But,

52:23

and this might not come as a surprise, there

52:25

have been problems when the police use these tools as well.

52:28

These search engines sometimes serve as doppelgangers, images

52:30

of people who look like you, but who

52:33

are not you, which can

52:35

have real consequences. Casimir reported

52:37

the story of a man who was arrested for a

52:39

crime he was completely innocent of. The

52:41

crime had taken place in Louisiana, the man

52:43

lives in Atlanta. The police department

52:46

had a $25,000 contract with

52:48

ClearVue AI, though the cops wouldn't

52:50

confirm or deny that they'd use ClearVue AI

52:52

to misidentify him. How

52:57

do these search engines deal with errors? Do

53:01

they like correct things? If they make a

53:03

mistake, is there a process? So

53:05

in the minds of the creators of

53:07

these systems, they don't make mistakes. They

53:10

aren't definitively identifying somebody. They are

53:13

ranking candidates in order of confidence.

53:15

And so when ClearVue AI talks

53:17

about their technology, they don't say

53:19

they're identifying anyone. They say that

53:22

they are surfacing candidates, and that

53:24

ultimately it's the human being who's

53:26

deciding which is a match. It's

53:28

the human making the mistake, not

53:31

the system. So if I were running

53:33

for local office somewhere, and there

53:35

was a video of someone who looks

53:37

like me doing something compromising, and

53:39

someone wrote a news story being like, hey, we put his face in

53:42

the thing and this is what we found, and

53:44

I went, hey, you're smearing me. They'd

53:47

be like, we're not smearing you. We're just pointing out that you look like

53:49

this guy doing something he's not supposed

53:51

to do in a video. Right, it's the

53:53

new service that covered it that smeared me,

53:55

not the facial recognition engine. But

53:57

for the person in jail, they know that they would not have been.

53:59

been in jail if this technology didn't

54:02

exist. Yes, exactly. So there's this

54:04

power of the government, right? Power of

54:06

corporations. And then just as individuals, I

54:08

think about this. Basically every

54:10

time I'm at dinner now at a

54:12

restaurant, and there's people sitting around me,

54:15

and I start having a juicy conversation,

54:17

whether it's personal or about work. And

54:19

I think, wow, I really need to

54:21

be careful here, because anybody sitting around

54:23

me could, if they got interested

54:25

in the conversation, snap a photo of your face. And

54:28

with these kinds of tools, find out who you are.

54:31

That's what I always think about. I was

54:33

at a restaurant recently, and it was outdoor

54:35

dining, and I was with a friend. And

54:37

in the next closed booth, there

54:40

was this person. They took a phone

54:42

call, and they were like, one sec. This is Kamala

54:44

Harris. And I think they were joking. But I could

54:46

hear them. And I was like, oh, I

54:49

could just hand their face. I could kind of

54:51

figure this out. I might be able to find

54:53

out privileged stuff about a conversation with a very,

54:55

very member of the US government. I

54:58

felt real nausea. I felt

55:00

nausea at the possibilities. Yeah,

55:02

I mean, I think there's just so many

55:04

moments in our daily lives where we just

55:06

rely on the fact that we're anonymous. Like,

55:09

you know, you're at dinner. You're having this

55:11

private conversation, and then creepy PJ is going

55:13

to be sitting there and looking up

55:15

your connection to the vice president. Does

55:18

it make you more, are you different in the

55:20

public now? Yeah, I mean, I

55:22

just think that is the risk of facial

55:24

recognition technology, the same way that we feel

55:26

this concern about what we put on the

55:29

internet, like the tweets you write, the emails

55:31

you write, the texts you send, just thinking,

55:33

am I OK with this existing

55:35

and possibly being tied back to me, being

55:37

seen in a different context? That

55:39

is going to be our real world experience. You have

55:41

to think all the time. It's something that I'm saying

55:43

right now that could be overheard by

55:46

a stranger, something that could get me in

55:48

trouble, or something that I would regret. And

55:50

I don't know. That just terrifies me. I don't want to

55:52

be on the record all the time,

55:55

every minute, anywhere I am

55:57

in public. I just kind of assume that these.

56:00

things that you're doing aren't gonna

56:02

haunt you for the rest of your life or follow you for the rest

56:04

of your life or be tied to you. Unless

56:06

you're a celebrity with a very famous face. And

56:09

it's been funny because I've talked with various people

56:11

who do have famous faces and I talk about

56:13

this dystopia where it's like everything you

56:15

do in public will come back to haunt you. And

56:18

usually after the interview they'll say, that's my life.

56:21

And I'm like, yes, what this

56:23

technology does is it makes us all

56:26

like celebrities, like famous people. Minus

56:29

the upsides. Minus the upsides. What

56:34

do you do if you don't wanna be in

56:36

these databases? Don't have photos

56:38

of yourself on the public internet. It's hard

56:40

not to get into these databases.

56:43

These companies are scraping the

56:45

public web. So we can't

56:47

get out of Clearview's database. And

56:50

there's no federal law yet that gives us the

56:52

right to do that. European privacy

56:54

regulators have said that what Clearview I

56:56

did was illegal and that Clearview need

56:58

to delete their citizens. And

57:00

Clearview basically said, we can't tell who

57:02

lives in Italy or who lives in

57:05

the UK or who lives in

57:07

Greece. So there's not really much we can

57:09

do. It's

57:11

funny though, because I'm not a technology

57:13

CEO. And if you asked me to actually fix

57:15

that problem, I actually could fix that problem. Like

57:17

you could say, anybody can email us and ask

57:19

to be taken out if they prove that they

57:22

live in Greece. You would think they could actually

57:24

do something about it. Yeah, this work gets

57:26

so complicated. For a while, Clearview AI

57:28

was honoring requests from Europeans who wanted to

57:30

be deleted from the database. But

57:33

then at some point they just stopped and

57:35

said, actually, we don't feel like we

57:37

need to comply with European privacy laws

57:39

because we don't do business in Europe anymore.

57:41

God. Yeah. They're like

57:44

ungovernable. Yeah,

57:47

in some jurisdictions, you can get the

57:49

company to delete you. In the

57:51

US, there are a few states that have

57:53

laws that say you have the right to

57:55

access and delete information that the

57:57

company has about you. California is one of the...

58:00

those states. If you live in California, you

58:02

can go to Clearview AI and

58:04

give them your driver's license and a photo of you

58:06

and they'll show you what they have of you in

58:08

the database. And if you don't like it, you can

58:11

say delete me. But there are

58:13

only a few states that have such a

58:15

law for most of us, like here in New

58:17

York, we don't have that protection. So we can't

58:19

get out of Clearview's database. Facial

58:24

recognition is hard because these companies

58:26

are based in places that don't

58:28

have great privacy laws like the

58:31

United States. And they're making people

58:33

around the world searchable. It

58:36

really is a hard problem. And on a larger

58:38

sense, as a country society

58:41

world, if we were like, we

58:43

just don't want this technology to exist, I know

58:45

this is kind of like a child's question, but

58:47

what would it look like to put the genie

58:49

in the bottle? I mean, make it illegal, force

58:52

all companies to delete the algorithms. You have

58:54

to decide, are we talking about all facial

58:56

recognition, your iPhone opening when you look at

58:58

it? Or are we talking about

59:01

just these big databases that are searching for

59:03

your face among millions or billions of other

59:05

faces? I don't think that's going

59:07

to happen. I don't think it's going away. But

59:09

I do think we have this kind

59:12

of central question about facial recognition.

59:14

Should these companies have the right

59:16

to gather all these faces from the public internet

59:19

and make them searchable? I think that is

59:21

something that could be shut down

59:23

if we wanted it to be. Welcome

1:00:00

back. So

1:00:25

quickly before we go this week, we

1:00:28

are heading towards the end of season one

1:00:30

of Search Engine. Is

1:00:32

there going to be a season two of Search Engine? How

1:00:34

has season one gone? Great questions.

1:00:37

We will be answering them, all of them, and

1:00:40

whatever other questions you have about Search

1:00:42

Engine's present and future in

1:00:44

questionably transparent detail at our

1:00:46

upcoming board meeting. The

1:00:49

date is Friday, May 31st. We

1:00:51

will be sending out the details with the time and a

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Zoom link to join. This is

1:00:55

only for our paid subscribers, people who

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meeting, you've got to sign up. You can

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do so at searchengine.show. You get

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all the benefits on the website. Again,

1:01:10

that URL is searchengine.show. If you're a

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paid subscriber, look out for an email

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from us next week and mark your

1:01:17

calendar, May 31st, 2024. Search

1:01:27

Engine is a presentation of Odyssey and

1:01:29

Jigsaw Productions. Search Engine was created

1:01:31

by me, PJ Vogt, and Trudy Pinmaneni, and is

1:01:33

produced by Garrett Graham and Noah John. Fact-checking

1:01:36

this week by Holly Patton. Theme,

1:01:39

original composition, and mixing by Armin

1:01:41

Bazarian. Our executive producers

1:01:43

are Jenna Weiss-Berman and Leah Reiss-Dennis. Thanks

1:01:46

to the team at Jigsaw, Alex Gibney, Rich

1:01:48

Perrello, and John Schmidt, and

1:01:51

to the team at Odyssey. J.D. Crowley,

1:01:53

Rob Miranda, Craig Cox, Eric Donnelly,

1:01:55

Kate Hutchinson, Matt Casey, Maura Curran,

1:01:58

Beth Zunafranci, Kurt Courtney, and Hillary

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sheets. Our agent

1:02:02

is Oren Rosenbaum at UTA. Follow

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and listen to Search Engine with PJ Vot now

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for free on the Odyssey app or

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wherever you get your podcasts. Thank

1:02:12

you for listening. We will see you in two

1:02:14

weeks when...