Facial recognition may be coming to a police body camera near you
Facial recognition may be coming to a police body camera
near you
By Drew Harwell, The Washington Post Published 10:52 am,
Thursday, April 26, 2018
The country's biggest seller of police body cameras on
Thursday convened a corporate board devoted to the ethics and expansion of
artificial intelligence, a major new step toward offering controversial
facial-recognition technology to police forces nationwide.
Axon, the maker of Taser electroshock weapons and the
wearable body cameras now used by most major American city police departments,
has voiced interest in pursuing face recognition for its body-worn cameras. The
technology could allow officers to scan and recognize the faces of potentially
everyone they see while on patrol. A growing number of surveillance firms and
tech start-ups are racing to integrate face recognition and other AI
capabilities into real-time video.
The board's first meeting will likely presage an imminent
showdown over the rapidly developing technology. Shortly after the board was
announced, a group of 30 civil rights, technology and privacy groups, including
the American Civil Liberties Union and the NAACP, sent members a letter voicing
"serious concerns with the current direction of Axon's product
development."
The letter urged an outright ban on face recognition,
which it called "categorically unethical to deploy" because of the
technology's privacy implications, technical imperfections and potentially
life-threatening biases. Most facial-recognition systems, recent research
found, perform far less accurately when assessing people with darker skin,
opening the potential to an AI-enabled officer misidentifying an innocent
person as a dangerous fugitive.
Axon's founder and chief executive, Rick Smith, said the
company is not currently building facial-recognition systems but said the
technology is "under active consideration." He acknowledged the
potential for "bias and misuse" in face recognition but said the
potential benefits are too promising to ignore.
"I don't think it's an optimal solution, the world
we're in today, that catching dangerous people should just be left up to random
chance, or expecting police officers to remember who they're looking for,"
Smith said. "It would be both naive and counterproductive to say law
enforcement shouldn't have these new technologies. They're going to, and I
think they're going to need them. We can't have police in the 2020s policing with
technologies from the 1990s."
Axon held the board's first meeting Thursday morning at
its Arizona headquarters with eight company-selected experts in AI, civil
liberties and criminal justice. The board, whose members are paid volunteers
and have no official veto power, will be asked to advise the company on
"future capabilities Axon's AI Research team is working on to help
increase police efficiency and efficacy," the company said in a statement.
Face recognition has long had major appeal for law
enforcement and government surveillance, and recent advances in AI development
and declining camera and hardware costs have spurred developers to suggest it
could be applied for broader use. Roughly 117 million American adults, or about
half the country, can be found in the vast facial-recognition databases used by
local, state and federal law enforcement, Georgetown Law School researchers
estimated in 2016.
Faces are regarded as a quick, reliable way to identify
someone from video or afar - and, in some cases, seen as easier to acquire than
other "biometric identifiers," such as fingerprints, that demand
close proximity and physical contact. The Department of Homeland Security scans
the faces of international travelers at many of the country's biggest airports,
and plans to expand to every traveler flying overseas.
But critics say facial-recognition systems are still
unproven in their ability to uniquely identify someone. Faces age over time and
change because of circumstance, and they aren't always that unique. Identical
twins, for instance, have been shown to be able to fool the facial-recognition
systems used to unlock Apple's iPhone X.
"Real-time face recognition would chill the
constitutional freedoms of speech and association, especially at political
protests," the letter from the dissenting groups states. It "could
also prime officers to perceive individuals as more dangerous than they really
are and to use more force than the situation requires. No policy or safeguard
can mitigate these risks sufficiently well for real-time face recognition ever
to be marketable."
Axon has moved aggressively to corner the market on
police technologies, offering free one-year trials for its body cameras and
online storage to police departments nationwide. The company said in February
that more than half of the major city law-enforcement agencies in the United
States have bought Axon body cameras or software, including Los Angeles,
Chicago and Washington.
The company, which changed its name last year from Taser
International, also advertises itself as "the largest custodian of public
safety data in the U.S.," saying more than 20 petabytes - or 20 million
gigabytes - of police photos, body-camera video and other
criminal-investigation documents have been uploaded to its cloud-storage service,
Evidence.com.
Police video is seen as a major growth market for
AI-development firms, both for real-time surveillance and after-crime review:
One company, BriefCam, allows city officials and police investigators to narrow
hours of video down into seconds by filtering only the footage of, for
instance, red trucks or men with suitcases.
Axon's long-established contracts with nationwide police
forces could push the technology's real-world deployment rapidly forward.
Instead of signing new deals with tech firms, police departments with Axon body
cameras could push facial-recognition features to its officers in potentially
the same way they apply a software update.
Face recognition is one of the most competitive and hotly
debated subsets of AI in today's consumer tech, with Apple, Facebook and Google
all devoting teams to expanding its use in security, photo tagging and search.
Most facial-recognition systems today depend on
"deep-learning" algorithms that analyze facial photos and scan for
similarities across a huge data set of similar images. Supporters of body
cameras say the upgraded systems could help alert officers to a passing
criminal suspect or spot a missing child in a crowd.
But the technology does not always deliver perfect
results and instead suggests the probability of a possible match, with an
accuracy rate that can vary wildly based on the photo's quality, the person's
skin color or other factors. Privacy advocates worry that the systems could
instill a false confidence and lead to police misidentifying innocent people as
suspects or wanted criminals, with potentially fatal results.
"There's always going to be a possibility of error
and, in a real-time scenario where a police officer is likely armed, the risks
associated with potential misidentification are always going to exceed any
possible benefits," said Laura Moy, the deputy director of Georgetown
Law's Center on Privacy & Technology. "There's a real concern that it
could exacerbate the risk of police use of force."
Today's facial-recognition systems also show troubling
implicit biases, often due to the lack of diversity in images its systems have
been trained on. Researchers from the Massachusetts Institute of Technology's
Media Lab said earlier this year that the three leading facial-recognition
systems - from IBM, Face++ and Microsoft - performed consistently better at
identifying the gender of people with lighter skin, averaging 99 percent
accuracy for lighter-skinned men and 70 percent accuracy for darker-skinned
women.
Body cameras, which gained popularity in recent years as
tools for checking police misconduct, have been criticized for contributing to
pervasive surveillance and potentially worsening the problems in heavily
policed neighborhoods. Police also largely decide the rules of use. Sacramento
police officers last month muted their body cameras after fatally shooting
Stephon Clark, an unarmed black man, in his grandmother's back yard.
Critics have questioned how effective the volunteer
ethics board, meeting twice a year, will be in steering the decisions of a
private company. But Smith said he saw some parallels between face recognition
and Tasers, which saw initial resistance but have rapidly proliferated into one
of law enforcement's most commonly used weapons.
"We'll probably see some missteps along the way. As
I look back on the Taser journey, when you introduce things with this much of a
change, it's rarely a smooth process," he said. But "getting this
wrong is not just a bad thing for society. Companies that get these things
wrong pay a big price. ... We don't want to create an Orwellian state just to
make a buck."
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