- Imagine you're on a sidewalk
and you wanna cross the street
but the crosswalk is just a little too far away.
So you look left, you look right
and you dart across the road.
A week later, you get a ticket in the mail for jaywalking.
The camera on the streetlight
above you was equipped with facial recognition software
and law enforcement matched your face
with your license photo and found your address.
A few days later, you walk into a concert
and security flags your expression as menacing or dangerous.
You're escorted out.
It's a dystopian future that's actually already a reality
and places across the world.
So here's the question.
Is constant mass surveillance
like this inevitable here in the U.S.?
- My fear is that if we don't win
in this moment where the technology is still
new enough to be shocking, where the outrageous
and abuses still are salient and it hasn't yet
become completely normalized as a facet of life,
I worry that if we don't win this fight now
that it will just become accepted the way a lot
of problematic invasions of our privacy already have.
- I'm Sinead Bovell, and this is Far Out.
[upbeat music]
Most of us recognize and even shrug
at the fact that every move we make online is being tracked.
But what about the real world?
Whatever that means.
How much do we really know
about how we're being tracked in public?
Here in the U.S. the number
of surveillance cameras grew nearly 50% between the years
of 2015 and 2018, ballooning from 47 million to 70 million,
those cameras can all be equipped
with facial recognition systems.
And in the last decade, these systems have gotten way better
and cheaper, mostly because of, yep, you guessed it, AI.
- We see CTTV everywhere.
We see both government owned systems and private systems.
But increasingly there isn't much
of a distinction between the two.
As you know, local police departments
federal agencies and everything in between will contract
with individual companies and service providers
to transform those private surveillance systems
into a public policing tool.
It's an opportunity to add all
of these layers of surveillance software on top
of that building an ever more intricate and invasive web
of tracking that can at this point look
at nearly every moment of how we spend the day.
- So you can't exactly avoid surveillance technology
unless you never leave the house
but you can wear something like this or this or this.
These are all examples of what's called adversarial fashion,
clothing and accessories designed to trick
facial recognition software into mislabeling a person
as something else like a giraffe or a zebra.
Activists sometimes use umbrellas
or all black clothing to remain anonymous during a protest.
But these designs specifically target the software
that powers facial recognition technology.
But to understand how adversarial fashion works
we first need to understand how facial recognition works.
The way humans see is actually a decent metaphor
for how machines see.
You see someone, your brain interprets their features
and then you recall their name from your memory.
Machines do something similar.
The camera captures an image.
That image is fed into an artificial neural network
and the image passes through layers in that network
that separate features like edges, textures, and shapes.
We've trained neural networks to find patterns
by giving them massive data sets with labeled images.
And this is creepy.
It's likely all of our faces in all of those data sets.
The ethics of which could be an episode all on its own.
Yes, academics might train their systems using
publicly available images, but private companies
are scraping the data we've all put on social media.
The network compares all that data
to the original photo and comes up with a match.
And that's a very basic explanation
of how machine learning works.
And scientists actually don't understand the finer details.
For example, understanding why the algorithms
that power these systems make certain choices.
Like how did it know that this nose matches that nose?
That's where our knowledge ends.
We don't know how the algorithm knows about noses.
We just gave them this massive data set and a goal,
match these faces, how they do it is still a mystery.
Neural networks were inspired by the human brain,
layers of neural networks working together
to transform inputs into information we can use.
But at this point in human history, both human brains
and artificial brains are still mystifying to us.
That uncertainty is very unsettling
especially when AI is used to conduct surveillance
which brings us all the way back to adversarial fashion.
Adversarial clothing confuses the part
of the neural network that categorizes objects.
So these exaggerated ears and noses make it harder
for the machine to say with confidence,
"Yep, that's a human."
Researchers have also designed attacks
on neural networks that make photos unrecognizable.
This one looks like static to us, but when you layer it
over a panda, the system tags it as a gibbon,
which is a type of small ape, if like me, you didn't know
but it's not easy to make these images.
You often need access to the neural network itself
in order to design and attack on it.
And they may not work on every system.
It's also not a solution that scales well.
If everyone is wearing adversarial fashion,
then the networks will eventually get better
at detecting them.
- The real solutions come from policy solutions,
enacting a privacy law, enacting limits on law enforcement,
enacting laws like Illinois BIPA, and before that
BIPA is the biometric privacy law
in Illinois and other laws to just stop, you know
people from being able to use this stuff.
I mean, we've kind of, it's interesting.
I think we've reached a kind of a moment
in our society where we actually
don't think law could ever be on our side.
And I understand
as somebody who works really hard to change policy and law
you know why some people might, you know, feel this
you know, privacy nihilism, but,
individual solutions are not gonna get us there.
- So what will get us there?
And do we all agree
that this kind of surveillance is a problem?
How you feel about surveillance might depend
on how you feel about the people being surveilled.
For example, the FBI used facial recognition
to identify January 6th insurrectionists,
but it's also been used to surveil
and track down protestors after Black Lives Matter protests.
- Lots of people say, well, if you're doing nothing wrong
then why are you worried?
But I've yet to meet a person who actually stands
by that argument in every context.
You know, maybe they think that's no big deal
if the police have that information.
But what happens when the IRS has it?
We may trust different institutions to wield this power
but none of us trust every institution
that's wielding it to do so unchecked
- We know from research on U.S. surveillance of Muslims
after 9/11, that constant surveillance changes
people's behavior.
They're less likely to participate in free speech activities
like protests.
In fact, they're less likely to participate
in any social activity like going to a mosque,
or seeing friends.
So it's easy to imagine how these tools
can become oppressive over time.
- We built these systems on the argument
that we will never have any bad rulers who will use it
for bad purposes.
I think that's a bad bet.
They're especially problematic
for the people who've always been
over-surveilled in our society.
People from marginalized groups
or people who are trying to make change
in the law or in our world.
- Some facial recognition systems are far more likely to
misidentify racial minorities, which may have been due
to too many white faces in too many data sets.
The technology is improving all the time
but that's cold comfort to privacy advocates who say
we don't have any evidence showing that surveillance
makes us safer.
A 2020 meta-analysis of surveillance research found
that the presence of CCTV cameras led to a 13% reduction
in theft, but had no effect on violent crime.
And that study focused just on crime prevention.
We don't know if facial recognition technology
is helping solve more crimes
because it hasn't been rigorously studied.
- The police really don't have any regular requirement
that they figure out whether what they're doing is working
and that's a good place to start.
Things like transparency ordinances
and accountability measures that we can agree on about
for questions like, you know, did putting cameras
up all over our public spaces actually help us reduce crime
in the way that we would like to.
- Just because the technology is available
it doesn't always mean we should use it.
I don't think constant mass surveillance by the private
or public sector is a society we wanna move towards.
The European Union has created some specific guidelines
for facial recognition technology that I think
are the right approach.
For example, it can only be used
as a tool to investigate serious crimes
and not to constantly surveil the public.
But the U.S. is still lacking in clear federal policy
that guides how we use this technology here.
And until that's solved, there will likely be a hodgepodge
of rules that vary depending on where you live.
It might feel like mass surveillance isn't slowing down
but how we respond to it, still an open question.
How do you feel about mass surveillance?
Is there a way to use it responsibly?
Where do you see this technology going in the future?
Let us know in the comments.
[suspenseful music]