The majority of Americans appear
in a facial recognition database,
potentially accessible by their local
police department and federal
government agencies like ICE
or the FBI.
It's not something you
likely opted into.
But as of now, there's no way to
be sure exactly who has access to your
likeness. Over the past 10 years
or so face recognition, face surveillance
has moved from the realm of science
fiction to the realm of science
reality. But in light of recent
protests for racial justice, facial
recognition technologies have come under scrutiny
for the way in which
they're deployed by police
departments around the country.
Protesters worry they're being tracked, and
communities of color say this
tech will exacerbate bias.
Nobody can get clear answers about
who is using facial recognition and
how. These technologies do not work
the same across different groups of
people. And oftentimes the people that they
fail most on are those who are
already marginalized in society.
In response, IBM, Amazon, and Microsoft
have all stated that they'll either
stop developing this tech or stop
selling it to law enforcement until
regulations are in place.
And in late June, Democratic members
of Congress sought to make these
pledges permanent, introducing a bill
banning government use of facial
recognition technologies.
But lesser known companies like Clearview AI,
NEC, and Rank One plan to
pursue business as usual, and say this
tech has an important role to play
in the justice system.
If somebody violently harms somebody else,
that is an ongoing threat to
public safety and tools that can
be used safely should be available.
Whether or not they support a
ban, researchers and activists across the
political spectrum are increasingly speaking
out about privacy concerns,
algorithmic bias and the lack of
transparency and regulation around this
tech. I don't think we should take
an approach that a technology is
inherently good or bad.
But I'm not comfortable at the moment
with the lack of regulation, having
this technology being used
among law enforcement.
This is a type of technology that
has profound implications for the future
of human society. And we need to
have a real conversation about whether we
can have it in our society at all.
Facial recognition technologies use biometric
information, that is body
measurements specific to each individual, to match
a face from a photo or
a video to a database of known faces.
This database could be composed of
mug shots, driver's license photos, or
even photos uploaded to social media.
It's likely that you already use this
tech in your daily life, as advances
in artificial intelligence over the past
decade have greatly improved its
capabilities. Every time you use your
face to unlock your smartphone,
accept Facebook's photo tagging suggestions,
or sort through a Google
Photos album by person, you're
seeing facial recognition at work.
This isn't really the type of thing
that lawmakers are seeking to ban, and
some are definitely eager to
see the everyday users expand.
I think there are a lot
of applications that are potentially quite
exciting. You know, going to a grocery
store and being able just to walk
out of the store without having to
pay, you know the store just identifies
you and automatically done it to you.
But whether you're tagging photos or
searching through a vast government
database, it's the same
technology at work.
And that has others concerned.
We're worried that people are going
to start to normalize this technology
and that could bleed into acceptance
on the government side, which is
extremely concerning.
Real-time surveillance of video footage
is often considered the most
worrisome use case. Right now, the tech
is far from 100 percent accurate.
But in theory, using facial recognition
on video feeds would make it
possible to alert police when a suspect
shows their face in public or
track where anybody is going
and who they're associating with.
China and Russia already do
this, and some U.S.
cities, like Detroit and Chicago, have
acquired tech that would make it
possible. Detroit's video surveillance program
started in 2016, when
security cameras replaced at
eight gas stations.
In 2017, the department bought
facial recognition software, giving them
the capability to scan
these cameras video feeds.
Over the last, under three years,
i t has rapidly expanded.
They have surveillance helicopters, access
to drones, traffic lights with
surveillance capabilities.
After heated debate, Detroit banned the
use of facial recognition on live
video, so the city cannot
track people in real-time.
Chicago promises that it
doesn't do this either.
But throughout the U.S., using facial
recognition on photographs is still
common, though San Francisco, Boston and
a number of other cities have
outlawed all government use
of this tech.
So we should not forget, right, San
Francisco was the first city to ban
face recognition.
The place where the sausage is being
made did not want the sausage, right?
Private companies like Walmart, Lowe's and
Target have also trialed facial
recognition systems to catch shoplifters,
though they say they're not
currently using it. And U.S.
airports are starting to roll out face
scanners at the gate, so passengers
need not show their passport.
There's also potential to use
similar tech in targeted advertising,
something that Walmart is experimenting with
in partnership with a startup
called Cooler Screens, which infers a shopper's
age and gender in order to
show more relevant ads.
While the screens don't identify individuals,
it's not hard to imagine a
system that could, a thought
that puts many on edge.
I think many people will be concerned
and creeped out, but will eventually
suck it up and get used to it.
If someone can come up with a way,
in the private sector, to ensure that
this is not easy for criminals or
the government just to take advantage
of, then I can see people
becoming quite comfortable with it.
The global facial recognition market was
valued at 3.4 billion dollars in
2019, and it's projected to grow
steadily over the coming years.
However, in the wake of George
Floyd's death and protests against racism
and police brutality, Amazon, Microsoft,
and IBM made headlines for
pulling back on police access
to facial recognition technology.
But while these tech giants certainly
have clout, as well as other
significant ties to law enforcement,
they're not actually the most
important companies in
this specific market.
First off, IBM did not have
a real product in this space.
Microsoft and Amazon, neither of them
were big players in the law
enforcement space. They did not have
a large line of business there.
So one could call it
a bit of virtue signalling.
After announcing a yearlong moratorium on
police use of its facial
recognition software, called Rekognition, Amazon
says it doesn't know how
many police departments
actually use it.
Rekognition is widely used in the
private sector, but previously only one
law enforcement customer was
listed on its website.
For its part, Microsoft says it
does not currently sell its facial
recognition software to police and that it
promises not to until there are
federal regulations in place.
IBM took the boldest stance of the
three, promising to stop research and
development on facial
recognition altogether.
But this tech wasn't really generating
much revenue for the company
anyway. But many lesser-known companies
are providing this technology to
the police on a large scale, and
they've made no such promises to stop,
upsetting privacy advocates.
My view is that it's fundamentally
incompatible with democracy and with
basic human rights to have technology
like facial recognition in the hands
of law enforcement. Clearview AI is
a huge player in this space.
Founded in 2017, Clearview has amassed
a database of over three billion
images, scraped from millions of websites
and social media platforms from
Venmo to Facebook. Its catalog is
far more comprehensive than anything
that came before it, and the company
says it's used by over 2,400 law
enforcement agencies in the U.S.
at the local, state,
and federal levels.
Because we're like the largest provider in
the space and we've had so much
experience, we feel that it would be a
shame and a really big mistake to
take it away, because all
these crimes would go unsolved.
The way Clearview works is simple.
You just upload a picture and
the system searches its database for
matches. So Katie, do you mind if I
show you how it works on your photo
that you supplied earlier?
Go for it. So it just
takes a matter of seconds.
You pick the photo that you want
to search, which is that one.
And as you can
see, it's uploading it.
It's finding photos. And here there's
eight photos out of over three
billion that match.
And you can see they all come
with a link to the original.
I see a picture from my personal
website, an old news article, CNBC's
website. All things I knew were out there,
but not things I knew were a
part of a facial recognition database,
accessible to thousands of police
departments. The Clearview system itself does
not reveal my name, but the
links point to websites that do.
So we don't actually identify someone,
we help you identify someone if
you're an investigator. While Google,
YouTube, Twitter, and Facebook have
all sent cease-and-desist letters to
Clearview, the company says that
because these images are public, it
has a right to compile them.
At the end of the day, it's
a search engine just like Google.
So we think it's a little bit
hypocritical of them to then send a
cease-and-desist. But fundamentally, it
is publicly available information.
Other players include NEC, the
1 21-year-old information technology and
electronics giant that sells its
software to about 20 U.S.
law enforcement agencies, and Rank One,
which says it supports about 25
different law enforcement agencies.
We think face recognition is a
tool that empowers people when used
correctly. If it wasn't our technology,
it absolutely would be somebody
else's technology.
Advocates have raised the alarm on
facial recognition for years, and now
their concerns are gaining momentum.
One of the most oft-cited issues is
the general lack of transparency when
it comes to exactly who is using
facial recognition and for what ends.
I wish I could tell you how
many police departments are using this
technology. Researchers at Georgetown discovered
that Detroit was one of
the cities using facial recognition.
They had been using that technology for
over a year before the community
got wind of it. So because we
don't have this transparency, I'm not able
to answer this question of
house widespread this technology is.
That lack of transparency ma
y be by design.
The concern here I think from the police
is, we don't want to show our hand
to criminals. The idea is, well if
we have to be more transparent about
what technology we use, then
people will adapt their behavior.
And I think in a functioning
democracy that takes civil liberties
seriously, that's a price sometimes
we have to pay.
What's more though, the tech
just isn't always accurate.
And when it's wrong, it reveals bias.
A 2018 study by the ACLU tested
Amazon's Rekognition software on members of
Congress, running their images
through a mugshot database.
It incorrectly identified 28
of them as criminals.
And while only 20 percent of Congress
members are people of color, they
comprised 39 percent of
the false matches.
This report came on the heels of
a 2018 study by Buolamwini and her
co-author, Timnit Gebru, which demonstrated
that software by Microsoft,
IBM, and Chinese company Face++ frequently
misgendered women and people of
color. I was working on an
art installation that used face-tracking
technology. It didn't work that well on my
face until I put on a white
mask, and so that
led to some questions.
Others that did de tect
my face labeled me male.
I am not a man. B uolamwini and
Gebru found that the systems they tested
were nearly 100 percent accurate when
identifying the gender of white men.
But when identifying gender in
darker skinned woman, Microsoft's system
failed about 20 percent of the time
and IBM's system failed about a third
of the time. After the study came
out, Microsoft and IBM trained their
algorithms on a more diverse set of
faces and improved their error rates.
But when B uolamwini conducted a
follow-up study using Amazon Rekognition,
it still m isgendered dark-skinned woman
nearly a third of the time.
Amazon, unlike Microsoft or IBM,
actually actively attempted to discredit
our research. And we were really
fortunate that more than 70 A.I.
researchers and practitioners came to
say no, this is rigorous,
peer-reviewed, in fact even
award winning work.
The issues that are being pointed
out are core to our field.
Like Amazon noted in their critique
of B uolamwini's study, Brendan Klare,
CEO of Rank One, says that
gender identification is a different technology
than matching a face to
a database of faces.
Obviously gender estimation is sort of
a different type of application, but
there never should be
errors like that.
And the errors they showed were
egregious and those are not representative
of the technology.
Our technology is about 99 percent
accurate on gender estimation across
all races. He says that claims
of algorithmic racism and sexism are
misleading. It's an important topic.
It's one that has been susceptible
to a lot of misinformation.
Both Rank One and NEC recently
made the news after their algorithms
misidentified a black man in Detroit as
a suspect in a shoplifting case.
The man, Robert Williams, spent
30 hours in jail.
Klare says that Rank One's technology was
misused in this case, because a
match is not probable
cause for arrest.
The investigating officers did
not collect independent evidence.
If the case of Mr.
Williams is not an isolated incident, if
there is a pattern that emerges,
we will get out of this market.
Clear view says a recent test showed
its system is 99.6 percent accurate
and exhibits no
racial bias whatsoever.
Previously, the ACLU has called
Clearview's accuracy assertions absurd and
challenged the company's
testing methodology.
The Detroit police chief, facing scrutiny
over Williams' arrest, said that
if the department relied solely on
its facial recognition software, it
would misidentify suspects about 96
percent of the time.
The huge difference in
stated accuracy rates vs.
actual accuracy rates could be because
these systems are tested using
relatively high quality images.
But when they're deployed in the
real world, security camera footage can
be too low quality
to yield accurate results.
But just for context, the most important
thing, this is much more accurate
than the human eye. And I think
there's only beneficial things that can
happen once you get to
this level of accuracy.
But even if a system could achieve
perfection, others can think of a whole
host of not
so beneficial consequences.
It's dangerous when it works
and when it doesn't.
But even if the technology worked 100
percent of the time, it would be
extremely dangerous because at its logical
conclusion, what it really does
is eliminate privacy and anonymity in
public space, which is something
that no free society
should ever tolerate.
Some are more optimistic about the
role that facial recognition could play
in society. Facial recognition technology
could be exculpatory evidence.
Like, look Your Honor, I know I'm
being accused by three witnesses, but
there is an image of me
at Walmart at this moment.
It cannot be me. What if there was
a facial recognition system and it only
included images of children that parents had
volunteered in the case of a
missing child? That's the kind of
situation where I imagine that people
see the value of it.
But still, others ask, are
the serious drawbacks worth it?
There is the scenario that we would hope
to be true, which is this flawless
system is used in a police force
that doesn't have a history of systemic
racism. But this is not
the world we live in.
And so I can understand wanting to
use whatever tools are available, but
we have to ask, are we bringing
the correct tool to the job?
And so it's one thing if oh,
it worked out how you thought.
But at what cost? How much
data did you have to collect?
We believe it's extremely dangerous,
in a predominantly black city
especially. It doesn't make any sense
to double down on something like
this at a time when the nation
is calling for some systemic changes within
policing and to undo systems
of brutality and racial violence.
What most experts agree on is that
at the very least, more regulation and
transparency is needed.
Many also say this tech should not
be used to help solve low-level crimes
like shoplifting or drug use, though
some concede that it may eventually
be appropriate to use facial recognition
on still photos to help solve
violent crimes or kidnappings.
But using it on video footage
is often considered a red line.
We believe strongly that the use
of facial recognition algorithms to
analyze video data either in real-time or
to look back at historic video
footage, that that ought to be
banned permanently in the United States,
that we should just never be
engaged in that type of surveillance.
In general, a federal moratorium on
this tech could garner significant
bipartisan support.
Last year, an ACLU poll in Massachusetts
revealed that nearly eight in 10
voters supported a statewide moratorium,
which included 84 percent of
Democrats, 82 percent of Independents
and 50 percent of Republicans.
We're kind of in this sweet spot
right now where the technology is not
quite good enough to really be able
to effectively achieve the goal of
cataloging every person's every public
movement, habit, and association.
But it's getting there. So this
is the perfect time, actually, for
lawmakers to step in and say, you know
what we're just going to draw a big
bright red line in the sand here and
say, we're not going to go any
further until we have a
deliberate conversation about this.
But some worry that Big Tech will
use this time to lobby for overly
permissive regulations.
We're going to be on the lookout
for legislation that is clearly backed or
sponsored by companies like Amazon and
Microsoft, where their lawyers and
lobbyists have gone over the text to
make sure that it's friendly to their
business model. In some form or
another, facial recognition is likely here
to stay. We'll probably continue using it
to unlock our phones and tag our
pictures. It may become commonplace to use
it to confirm our identity at
the airport or grocery
store checkout line.
Maybe we'll even come to accept
a world full of hyper-targeted advertising
screens. Name one technology
we've developed and stopped.
This genie is not going
back in the bottle.
It really is just going to be coming
down to how well do we manage it?
But to what extent governments and
police departments can access this
technology remains an open question.
And that's where the
real debate lies.
Some think the political environment right
now presents a real opportunity
to ban a ccess to this
tech at all levels of government.
I think in Congress we have a
real shot at getting strong legislation to
put at least an immediate moratorium on
local, state, and federal use of
facial recognition. And I'm optimistic that we
will get a ban on facial
recognition in the United States.
Others predict legislation will stop
short of a ban.
I think there will be many members
who take the view that the technology
has many worrying applications and civil
libertarian issues, but that it
also is ultimately useful with
the right guidelines in place.
And crafting these guidelines soon
will be essential, because technology
like facial recognition is advancing
at a rapid clip.
It may be too late to turn
back the clock altogether, but some privacy
advocates say that this debate is emblematic
of the idea that just because
we can build something doesn't
mean that we should.
Sometimes algorithmic justice means you don't
make it, you don't deploy it.
I think these technology companies need to
have a sit down and ask
themselves before they innovate, i s
this something that necessarily needs
to exist in the world?
