Dark Net (2016) s02e05 Episode Script
My Identity
[Talley.]
I've been told that I look like an average person.
But some of the characteristics that somewhat stick out are, I would say, I have a big nose.
It's not very symmetrical.
My eyes are spaced apart.
I do have distinct moles on my right side of my face.
I think a lot of people probably look like that.
[narrator.]
The face it's the way we recognize each other.
But to machines, we are code.
We are being transformed into a face print, a unique set of points that converts our very humanity into data, traceable, trackable, forever, online or on the streets.
Will you ever be a face in the crowd again? [Shipp.]
On September 5th, we opened the bank at 9:00.
We had a line, probably five or six people in line.
The next client that came to the window handed me a piece of paper.
It was enclosed in a plastic envelope.
And I'm going, "Oh, my gosh," you know.
And it's like my heart just sunk.
[narrator.]
On September 5, 2014, Bonita Shipp came face-to-face with a bank robber.
[Shipp.]
As I was getting the money ready, I studied his face.
I tried to recognize any markings at all.
He had sunglasses on.
And he had a cap on.
So I couldn't see anything from his eyes up.
But I looked at his nose.
He had thin lips.
He had no tattoos, no scars, nothing.
So I took all of the money out of my drawer, put it all in an envelope.
And I handed it to him.
And then he left.
He got away with just a little under $3,000.
[Atick.]
One of the most prominent things about humans is that they use their vision to do many things.
We recognize friends from foe.
We recognize familiar faces.
We recognize objects.
We use our vision in a way that's very, very essential to our survival.
[narrator.]
Could computers one day recognize faces? That's the question that haunted face recognition pioneer Joseph Atick.
[Atick.]
I grew up in Jerusalem, where it was necessary to always travel with an I.
D.
, to present it two or three times a day to go from one town to the other.
I believed that we needed something that was more effective in securing the world.
So I applied mathematical techniques to the study of the human brain.
There are four elements in a facial-recognition technology.
One is the algorithm, which is inspired by the human brain.
Second was the need to have a camera in order to allow the vision, like the eye.
You needed to also have the database.
You needed to have the memory of people who are known.
Humans, for example, we remember about 2,000 people.
That's our database.
And in order to run the algorithm, we need processing power.
We do it effortlessly because we don't think of it.
But, in fact, when I look at your face, many, many calculations happen in my brain.
It is so innate that we don't even think about it.
Three or four years of mathematical took us to develop the first facial-recognition algorithm.
[narrator.]
This is FaceIt, the first commercial product using face-recognition technology developed by Atick and his team in 1995.
It opened a new window to our digital world.
The genie's now out of the bottle.
And any attempt to put it back, technologically, is doomed because I started getting a lot of calls from intelligence agencies around the world who thought this would be quite useful for their mission.
Facial recognition is simply the ability for law enforcement to electronically search against millions of photo images.
[narrator.]
Next-generation identification, the FBI's biometric network, overseen by assistant director Stephen Morris.
[Morris.]
The system is looking for key features of a face.
It'll measure the distance between the eyes the distance between the ears, the ears in relation to the mouth.
And then it's looking for other images in that repository that have those same measurements.
Our database consists of around 30 million mug-shot photos.
There are also repositories of photographs that have been lawfully collected, such as visa photos, travel documents and driver's license photo files.
So we're talking about more than just 30 million photos that can be searched using facial-recognition technology.
The potential is unlimited.
[narrator.]
About half of American adults are in a law-enforcement database.
Most don't even know it.
To store the world's largest biometrics database is a 100,000-square-foot data center, about the size of a lower Manhattan block.
[Dispatcher.]
Just be advised, there was an RP accident at 112 precinct.
I've been working in the 6-7 for about 2 1/2, going on 3 years.
We have the pictures of people who were involved in a shooting.
So when you come into contact with that person, they know who we are.
But now we have a step up because we know who you are.
[narrator.]
About 35,000 officers patrol the streets of New York City.
But even the nation's largest police force can use an extra pair of eyes or 10,000 of them.
These cameras aren't just watching.
With the help of live analytics, they can detect what the human eye cannot, a shot fired, a suspicious package or a suspect running from a crime.
And they transmit this data directly to the real-time crime center.
[man.]
The main purpose of this unit is to help identify anybody who's unknown in a criminal investigation.
[narrator.]
The software enhances surveillance footage.
We're able to convert a 2D image to a 3D image.
And it's going to convert that image to a more proper pose that we're going to need, similar to a driver's license or a mug shot.
Facial recognition has tremendous potential when you're looking for the proverbial needle in a haystack.
It provides you a lead, particularly in an instance where you don't know who it is you're looking for.
[Talley.]
My name is Steve Talley.
I lived in Colorado.
I had a beautiful family.
I was a loving father.
I have two kids.
I have a daughter who is 12 this February.
I have a son who had just turned 9 last week.
We lived in a very nice, family-oriented community.
And I had a great career in financial services.
And I was, at that time, excited about my life and my prospects and the future.
I was living the American dream or so I thought.
My life changed dramatically.
I got divorced from my ex-wife.
And then I got laid off due to corporate restructuring.
I had financial obligations.
I still had child-support payments of about $2,000 a month.
But I considered myself to still be an average, law-abiding citizen.
[narrator.]
But the authorities thought he was living a double life as a serial bank robber.
And even local news joined in the hunt.
[reporter.]
Do you recognize this man? Denver police are looking for him tonight.
They say he robbed the U.
S.
Bank on South Colorado Boulevard near East Mississippi and Glendale last week.
Have a look at his picture taken by surveillance cameras in the bank.
Police say he may be armed with a gun.
[Talley.]
One day, there was a pounding at my door.
All of a sudden, I see a gentleman with the FBI jacket.
He handcuffed me behind my back.
He said, "Do you know why we're arresting you?" He said, "We're arresting you for two armed bank robberies and assaulting a police officer.
" I was driven to the detention center.
I was in prison in a maximum-security pod because they had very strong facial recognition that proved that I was the guy.
But I always said I was innocent.
I had an air-tight alibi.
I shared it with everyone.
I had my own witnesses for the alibi come in and prove I was there.
But my only crime is I, apparently, look like someone else.
I really have nothing to hide.
[narrator.]
Nothing to hide, nothing to fear, right? Face rec gets the bad guys off the streets.
So what's the harm? I grew up in a world where identity was part of our daily experience at a time when the world was in conflict.
In societies where there was an oppressive regime, there was a chilling factor.
People did not express themselves freely because there was a fear that they would be persecuted.
Now we have a different kind of chilling factor.
And it is driven not by governments, necessarily, but by the surveillance camera.
And that chilling factor, it means we're going to change our behavior.
And we no longer live in a free society.
Will that be a society that we will accept? [man.]
Zoom in.
Try to get as close up as you can.
Take a quick snapshot.
[Wade.]
By walking in to a casino, you have effectively given up your privacy because, in a casino, you really want to know your customer.
So facial recognition dramatically improved the ability to actively track card counters, high net-worth individuals, cheaters and all sorts of other individuals that the casinos are interested in tracking.
[narrator.]
The man behind this technology is Wyly Wade, who provides it to 200 casinos across the country.
[Wade.]
Facial recognition is contactless.
It is noninvasive.
And it is the link from your digital environment to your physical environment.
Part of this is a very personal issue to me.
I've got a daughter with special needs.
She's deaf.
She's autistic.
My daughter loves to climb.
She flips.
She twirls.
I'm the human jungle gym.
Oh, now you're going to run away, huh? She laughs.
She plays.
She runs.
She hides.
But she doesn't have this filter on what is good and what is bad.
So we need an extra level of security to re-create some of that filter for her.
We have cameras that automatically rotate, pan, tilt, zoom, all based off of either sound or motion.
If that camera detects that there's a face there, then what it does is it drops it down to our security system and then compares that to the people that I don't want into our house so that that way you can be prewarned or preconfirm whether or not that person is a rapist or sex offender because we have hundreds of thousands of registered sex offenders in the United States.
So if the UPS driver happens to be a registered sex offender, yeah, I'd like to be notified about that.
Facial recognition gives us peace of mind.
You don't know where the real danger lies.
You don't know who the hooligans are.
You probably don't even know your neighbors.
Facial recognition is not positive identification.
If you're looking for an individual, and you submit a search, and you get 14 back in your gallery, there could be 14 wrong people in there.
And that is where it's up to the investigator to take the information that comes with that picture.
After the robbery, the police and the FBI came, and they interviewed me, and they wanted me to identify the person and do a photo lineup.
There were six people on that page.
You know, I said, "Well, this kind of looks like the guy.
" And they asked me like, "What percentage do you think?" And I said, "Well, probably maybe 85%, but I'm not 100% sure.
" [Talley.]
Instead of using my mug shot in this photo lineup, which they typically do because it's the most recent picture, they actually used the picture where I got my DUI in 2011.
They're using this picture from 5 years ago where I look younger.
[narrator.]
That same DUI mug shot is what the FBI used to compare Talley to the robber.
I didn't think he looked like me.
But I could see some similarities.
And I think he probably looked like a gazillion people.
[narrator.]
But in court, the eyewitness faces the suspect not in pixels but in the flesh.
[Shipp.]
I insisted I would have to see Mr.
Talley in person because I want to make sure that my decision is right.
The robber had no markings, no moles.
And when you see this Mr.
Talley, he has a mole on his cheek.
Also, Mr.
Talley had a long nose.
The other guy's nose was shorter.
And Mr.
Talley is a big man.
And the robber was not.
And I told the judge, I said, "If you're asking me if this was the guy that was the robber," I said, "I am absolutely, 100% positive it is not.
" Talley: The FBI and local police said it was me based on the similar features.
But they totally ignored features that would exclude me as being a suspect.
Finally, they wanted to do a height analysis.
The bank robber was 6 foot.
And they determined I was 6'3 1/2".
So I was 3 inches too tall.
That proved I couldn't possibly be the guy.
[narrator.]
His face got him arrested.
But his height set him free.
I did get dismissed.
But they seemed to be trying to build a case where there really wasn't a case there.
They didn't have any, not even a shred, of evidence, except for I looked like the bank robber.
This is really scary stuff, this technology.
It could be a great shortcut to help with investigations but at the expense of possibly, you know, targeting the wrong people.
[narrator.]
It could happen to you.
As the database of faces grows larger, so does your chance of having a doppelganger.
[Atick.]
There are more cameras now than humans in the world.
With people having cameras in their pocket, cameras in the street, there are billions of cameras in the world.
That is a natural progression.
And we saw some of it happening.
But one thing we did not see, nor anyone saw or counted on, was the emergence of social media.
If, in the '90s, I told you that, one day, there was going to be a database where people voluntarily add their faces and the faces of their friends and the faces of their children, and that database could be used to identify every single one of those billion people, I would be laughed at back then.
But now Facebook is essentially a database that is the dream of a big brother.
[narrator.]
1.
8 billion users, 350 million pictures uploaded every day, we are the ones training Facebook's facial recognition.
How? By tagging ourselves and our friends.
Their algorithm is so strong, Facebook can I.
D.
you even if your face is hidden.
There is money to be made from the recognition of your face.
Imagine if you walked around, and on top of your head it said your name, how much money you have, what you like, what are your preferences in life, and machines that run algorithms will start to make decisions for us.
And as a consequence, we may lose the battle of privacy.
[Wade.]
I think privacy is a misnomer at this point.
We have to get over the idea that you own your data and your identity.
We gave up our right to most of our data when every time we signed up to Google or to Facebook because it was convenient.
It improved your life in a lot of ways.
But it also broke down a lot of barriers to where that data that you claim is your identity is no longer your data.
You don't own it.
We've almost gone to a post-privacy era.
[narrator.]
What does post privacy look like? Just ask the Russians.
[woman.]
Findface, an app that allows you to find any person in the largest Russian social network.
[narrator.]
It lets a user photograph a stranger, upload that picture and compare it to social media profiles to unmask the person's identity.
[woman.]
The service allows you to not only find the desired user but also to send them messages and other information.
[narrator.]
In other words, it's a dream come true for stalkers.
[Atick.]
To see a face recognition being abused in a certain way, it means that we no longer live in a free society.
But face recognition can be good as long as there's oversight to make sure no innocent individuals are accused.
[Talley.]
Now I'll wake up in the middle of the night, and I won't know where I'm at.
All of a sudden, it dawns on me.
This nightmare is my life.
Here I am.
I'm actually in a shelter right now.
Even though they had no case, it dragged on.
It's two years after, and I am still struggling.
Because of this incident, I lost my housing.
And even just being associated with bank robberies has, basically, effectively, black-balled me or destroyed my career in financial services.
No one's going to touch me.
The biggest thing is my custody situation.
I haven't been able to see my kids in two years.
I've missed the Christmases, the birthdays, the Thanksgivings, all the memories of them growing up.
I'm always concerned about them, what they're feeling, what their thoughts are about me.
Do they feel that they've been abandoned, that their father doesn't love them? Being homeless is extremely hard.
You know, I feel isolated.
I feel like I'm invisible, too, because a lot of people don't like to look at homeless.
I'm in a pretty big hole right now that I have to dig myself out of.
I'm fighting for my life back.
That's really what this is about is fighting to get my life back to where it was, to fight for myself, for my family.
[Wade.]
There's a lot of good that's used of this technology.
I use this to protect my family.
Are there bad uses of facial recognition? Absolutely, because we don't live in a perfect world.
Facial recognition is going to create problems.
There's going to be some collateral damage.
I guess I was collateral damage.
My family was collateral damage.
It happened to me.
Why couldn't it happen to other people? [narrator.]
Chances are your face can be used against you.
We all feed the network.
The more data we upload, the more powerful it becomes, entangling our physical selves into a digital web.
We, as technologists, have to be responsible for the creations that we've made.
And we have to explain to the world the inherent danger.
And that is the missing link between our online persona and our offline persona.
The offline persona is our only persona.
It's unique.
It's us, makes us human.
And the ability to protect that will depend on the ability to stop face recognition from recognizing us without consent.
And I don't believe we can afford to lose control over the most precious thing which is our identity.
I've been told that I look like an average person.
But some of the characteristics that somewhat stick out are, I would say, I have a big nose.
It's not very symmetrical.
My eyes are spaced apart.
I do have distinct moles on my right side of my face.
I think a lot of people probably look like that.
[narrator.]
The face it's the way we recognize each other.
But to machines, we are code.
We are being transformed into a face print, a unique set of points that converts our very humanity into data, traceable, trackable, forever, online or on the streets.
Will you ever be a face in the crowd again? [Shipp.]
On September 5th, we opened the bank at 9:00.
We had a line, probably five or six people in line.
The next client that came to the window handed me a piece of paper.
It was enclosed in a plastic envelope.
And I'm going, "Oh, my gosh," you know.
And it's like my heart just sunk.
[narrator.]
On September 5, 2014, Bonita Shipp came face-to-face with a bank robber.
[Shipp.]
As I was getting the money ready, I studied his face.
I tried to recognize any markings at all.
He had sunglasses on.
And he had a cap on.
So I couldn't see anything from his eyes up.
But I looked at his nose.
He had thin lips.
He had no tattoos, no scars, nothing.
So I took all of the money out of my drawer, put it all in an envelope.
And I handed it to him.
And then he left.
He got away with just a little under $3,000.
[Atick.]
One of the most prominent things about humans is that they use their vision to do many things.
We recognize friends from foe.
We recognize familiar faces.
We recognize objects.
We use our vision in a way that's very, very essential to our survival.
[narrator.]
Could computers one day recognize faces? That's the question that haunted face recognition pioneer Joseph Atick.
[Atick.]
I grew up in Jerusalem, where it was necessary to always travel with an I.
D.
, to present it two or three times a day to go from one town to the other.
I believed that we needed something that was more effective in securing the world.
So I applied mathematical techniques to the study of the human brain.
There are four elements in a facial-recognition technology.
One is the algorithm, which is inspired by the human brain.
Second was the need to have a camera in order to allow the vision, like the eye.
You needed to also have the database.
You needed to have the memory of people who are known.
Humans, for example, we remember about 2,000 people.
That's our database.
And in order to run the algorithm, we need processing power.
We do it effortlessly because we don't think of it.
But, in fact, when I look at your face, many, many calculations happen in my brain.
It is so innate that we don't even think about it.
Three or four years of mathematical took us to develop the first facial-recognition algorithm.
[narrator.]
This is FaceIt, the first commercial product using face-recognition technology developed by Atick and his team in 1995.
It opened a new window to our digital world.
The genie's now out of the bottle.
And any attempt to put it back, technologically, is doomed because I started getting a lot of calls from intelligence agencies around the world who thought this would be quite useful for their mission.
Facial recognition is simply the ability for law enforcement to electronically search against millions of photo images.
[narrator.]
Next-generation identification, the FBI's biometric network, overseen by assistant director Stephen Morris.
[Morris.]
The system is looking for key features of a face.
It'll measure the distance between the eyes the distance between the ears, the ears in relation to the mouth.
And then it's looking for other images in that repository that have those same measurements.
Our database consists of around 30 million mug-shot photos.
There are also repositories of photographs that have been lawfully collected, such as visa photos, travel documents and driver's license photo files.
So we're talking about more than just 30 million photos that can be searched using facial-recognition technology.
The potential is unlimited.
[narrator.]
About half of American adults are in a law-enforcement database.
Most don't even know it.
To store the world's largest biometrics database is a 100,000-square-foot data center, about the size of a lower Manhattan block.
[Dispatcher.]
Just be advised, there was an RP accident at 112 precinct.
I've been working in the 6-7 for about 2 1/2, going on 3 years.
We have the pictures of people who were involved in a shooting.
So when you come into contact with that person, they know who we are.
But now we have a step up because we know who you are.
[narrator.]
About 35,000 officers patrol the streets of New York City.
But even the nation's largest police force can use an extra pair of eyes or 10,000 of them.
These cameras aren't just watching.
With the help of live analytics, they can detect what the human eye cannot, a shot fired, a suspicious package or a suspect running from a crime.
And they transmit this data directly to the real-time crime center.
[man.]
The main purpose of this unit is to help identify anybody who's unknown in a criminal investigation.
[narrator.]
The software enhances surveillance footage.
We're able to convert a 2D image to a 3D image.
And it's going to convert that image to a more proper pose that we're going to need, similar to a driver's license or a mug shot.
Facial recognition has tremendous potential when you're looking for the proverbial needle in a haystack.
It provides you a lead, particularly in an instance where you don't know who it is you're looking for.
[Talley.]
My name is Steve Talley.
I lived in Colorado.
I had a beautiful family.
I was a loving father.
I have two kids.
I have a daughter who is 12 this February.
I have a son who had just turned 9 last week.
We lived in a very nice, family-oriented community.
And I had a great career in financial services.
And I was, at that time, excited about my life and my prospects and the future.
I was living the American dream or so I thought.
My life changed dramatically.
I got divorced from my ex-wife.
And then I got laid off due to corporate restructuring.
I had financial obligations.
I still had child-support payments of about $2,000 a month.
But I considered myself to still be an average, law-abiding citizen.
[narrator.]
But the authorities thought he was living a double life as a serial bank robber.
And even local news joined in the hunt.
[reporter.]
Do you recognize this man? Denver police are looking for him tonight.
They say he robbed the U.
S.
Bank on South Colorado Boulevard near East Mississippi and Glendale last week.
Have a look at his picture taken by surveillance cameras in the bank.
Police say he may be armed with a gun.
[Talley.]
One day, there was a pounding at my door.
All of a sudden, I see a gentleman with the FBI jacket.
He handcuffed me behind my back.
He said, "Do you know why we're arresting you?" He said, "We're arresting you for two armed bank robberies and assaulting a police officer.
" I was driven to the detention center.
I was in prison in a maximum-security pod because they had very strong facial recognition that proved that I was the guy.
But I always said I was innocent.
I had an air-tight alibi.
I shared it with everyone.
I had my own witnesses for the alibi come in and prove I was there.
But my only crime is I, apparently, look like someone else.
I really have nothing to hide.
[narrator.]
Nothing to hide, nothing to fear, right? Face rec gets the bad guys off the streets.
So what's the harm? I grew up in a world where identity was part of our daily experience at a time when the world was in conflict.
In societies where there was an oppressive regime, there was a chilling factor.
People did not express themselves freely because there was a fear that they would be persecuted.
Now we have a different kind of chilling factor.
And it is driven not by governments, necessarily, but by the surveillance camera.
And that chilling factor, it means we're going to change our behavior.
And we no longer live in a free society.
Will that be a society that we will accept? [man.]
Zoom in.
Try to get as close up as you can.
Take a quick snapshot.
[Wade.]
By walking in to a casino, you have effectively given up your privacy because, in a casino, you really want to know your customer.
So facial recognition dramatically improved the ability to actively track card counters, high net-worth individuals, cheaters and all sorts of other individuals that the casinos are interested in tracking.
[narrator.]
The man behind this technology is Wyly Wade, who provides it to 200 casinos across the country.
[Wade.]
Facial recognition is contactless.
It is noninvasive.
And it is the link from your digital environment to your physical environment.
Part of this is a very personal issue to me.
I've got a daughter with special needs.
She's deaf.
She's autistic.
My daughter loves to climb.
She flips.
She twirls.
I'm the human jungle gym.
Oh, now you're going to run away, huh? She laughs.
She plays.
She runs.
She hides.
But she doesn't have this filter on what is good and what is bad.
So we need an extra level of security to re-create some of that filter for her.
We have cameras that automatically rotate, pan, tilt, zoom, all based off of either sound or motion.
If that camera detects that there's a face there, then what it does is it drops it down to our security system and then compares that to the people that I don't want into our house so that that way you can be prewarned or preconfirm whether or not that person is a rapist or sex offender because we have hundreds of thousands of registered sex offenders in the United States.
So if the UPS driver happens to be a registered sex offender, yeah, I'd like to be notified about that.
Facial recognition gives us peace of mind.
You don't know where the real danger lies.
You don't know who the hooligans are.
You probably don't even know your neighbors.
Facial recognition is not positive identification.
If you're looking for an individual, and you submit a search, and you get 14 back in your gallery, there could be 14 wrong people in there.
And that is where it's up to the investigator to take the information that comes with that picture.
After the robbery, the police and the FBI came, and they interviewed me, and they wanted me to identify the person and do a photo lineup.
There were six people on that page.
You know, I said, "Well, this kind of looks like the guy.
" And they asked me like, "What percentage do you think?" And I said, "Well, probably maybe 85%, but I'm not 100% sure.
" [Talley.]
Instead of using my mug shot in this photo lineup, which they typically do because it's the most recent picture, they actually used the picture where I got my DUI in 2011.
They're using this picture from 5 years ago where I look younger.
[narrator.]
That same DUI mug shot is what the FBI used to compare Talley to the robber.
I didn't think he looked like me.
But I could see some similarities.
And I think he probably looked like a gazillion people.
[narrator.]
But in court, the eyewitness faces the suspect not in pixels but in the flesh.
[Shipp.]
I insisted I would have to see Mr.
Talley in person because I want to make sure that my decision is right.
The robber had no markings, no moles.
And when you see this Mr.
Talley, he has a mole on his cheek.
Also, Mr.
Talley had a long nose.
The other guy's nose was shorter.
And Mr.
Talley is a big man.
And the robber was not.
And I told the judge, I said, "If you're asking me if this was the guy that was the robber," I said, "I am absolutely, 100% positive it is not.
" Talley: The FBI and local police said it was me based on the similar features.
But they totally ignored features that would exclude me as being a suspect.
Finally, they wanted to do a height analysis.
The bank robber was 6 foot.
And they determined I was 6'3 1/2".
So I was 3 inches too tall.
That proved I couldn't possibly be the guy.
[narrator.]
His face got him arrested.
But his height set him free.
I did get dismissed.
But they seemed to be trying to build a case where there really wasn't a case there.
They didn't have any, not even a shred, of evidence, except for I looked like the bank robber.
This is really scary stuff, this technology.
It could be a great shortcut to help with investigations but at the expense of possibly, you know, targeting the wrong people.
[narrator.]
It could happen to you.
As the database of faces grows larger, so does your chance of having a doppelganger.
[Atick.]
There are more cameras now than humans in the world.
With people having cameras in their pocket, cameras in the street, there are billions of cameras in the world.
That is a natural progression.
And we saw some of it happening.
But one thing we did not see, nor anyone saw or counted on, was the emergence of social media.
If, in the '90s, I told you that, one day, there was going to be a database where people voluntarily add their faces and the faces of their friends and the faces of their children, and that database could be used to identify every single one of those billion people, I would be laughed at back then.
But now Facebook is essentially a database that is the dream of a big brother.
[narrator.]
1.
8 billion users, 350 million pictures uploaded every day, we are the ones training Facebook's facial recognition.
How? By tagging ourselves and our friends.
Their algorithm is so strong, Facebook can I.
D.
you even if your face is hidden.
There is money to be made from the recognition of your face.
Imagine if you walked around, and on top of your head it said your name, how much money you have, what you like, what are your preferences in life, and machines that run algorithms will start to make decisions for us.
And as a consequence, we may lose the battle of privacy.
[Wade.]
I think privacy is a misnomer at this point.
We have to get over the idea that you own your data and your identity.
We gave up our right to most of our data when every time we signed up to Google or to Facebook because it was convenient.
It improved your life in a lot of ways.
But it also broke down a lot of barriers to where that data that you claim is your identity is no longer your data.
You don't own it.
We've almost gone to a post-privacy era.
[narrator.]
What does post privacy look like? Just ask the Russians.
[woman.]
Findface, an app that allows you to find any person in the largest Russian social network.
[narrator.]
It lets a user photograph a stranger, upload that picture and compare it to social media profiles to unmask the person's identity.
[woman.]
The service allows you to not only find the desired user but also to send them messages and other information.
[narrator.]
In other words, it's a dream come true for stalkers.
[Atick.]
To see a face recognition being abused in a certain way, it means that we no longer live in a free society.
But face recognition can be good as long as there's oversight to make sure no innocent individuals are accused.
[Talley.]
Now I'll wake up in the middle of the night, and I won't know where I'm at.
All of a sudden, it dawns on me.
This nightmare is my life.
Here I am.
I'm actually in a shelter right now.
Even though they had no case, it dragged on.
It's two years after, and I am still struggling.
Because of this incident, I lost my housing.
And even just being associated with bank robberies has, basically, effectively, black-balled me or destroyed my career in financial services.
No one's going to touch me.
The biggest thing is my custody situation.
I haven't been able to see my kids in two years.
I've missed the Christmases, the birthdays, the Thanksgivings, all the memories of them growing up.
I'm always concerned about them, what they're feeling, what their thoughts are about me.
Do they feel that they've been abandoned, that their father doesn't love them? Being homeless is extremely hard.
You know, I feel isolated.
I feel like I'm invisible, too, because a lot of people don't like to look at homeless.
I'm in a pretty big hole right now that I have to dig myself out of.
I'm fighting for my life back.
That's really what this is about is fighting to get my life back to where it was, to fight for myself, for my family.
[Wade.]
There's a lot of good that's used of this technology.
I use this to protect my family.
Are there bad uses of facial recognition? Absolutely, because we don't live in a perfect world.
Facial recognition is going to create problems.
There's going to be some collateral damage.
I guess I was collateral damage.
My family was collateral damage.
It happened to me.
Why couldn't it happen to other people? [narrator.]
Chances are your face can be used against you.
We all feed the network.
The more data we upload, the more powerful it becomes, entangling our physical selves into a digital web.
We, as technologists, have to be responsible for the creations that we've made.
And we have to explain to the world the inherent danger.
And that is the missing link between our online persona and our offline persona.
The offline persona is our only persona.
It's unique.
It's us, makes us human.
And the ability to protect that will depend on the ability to stop face recognition from recognizing us without consent.
And I don't believe we can afford to lose control over the most precious thing which is our identity.