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Law Enforcement Use of Face Recognition Systems Threatens Civil Liberties, Disproportionately Affects People of Color: EFF Report
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Feb 17, 2018, 12:48:01 PM2/17/18
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https://www.eff.org/press/releases/law-enforcement-use-face-recognition-systems-threatens-civil-liberties
Law Enforcement Use of Face Recognition Systems Threatens Civil
Liberties, Disproportionately Affects People of Color: EFF Report
Independent Oversight, Privacy Protections Are Needed
San Francisco, California—Face recognition—fast becoming law
enforcement’s surveillance tool of choice—is being implemented with
little oversight or privacy protections, leading to faulty systems
that will disproportionately impact people of color and may implicate
innocent people for crimes they didn’t commit, says an Electronic
Frontier Foundation (EFF) report released today.
Face recognition is rapidly creeping into modern life, and face
recognition systems will one day be capable of capturing the faces of
people, often without their knowledge, walking down the street,
entering stores, standing in line at the airport, attending sporting
events, driving their cars, and utilizing public spaces. Researchers
at the Georgetown Law School estimated that one in every two American
adults—117 million people—are already in law enforcement face
recognition systems.
This kind of surveillance will have a chilling effect on Americans’
willingness to exercise their rights to speak out and be politically
engaged, the report says. Law enforcement has already used face
recognition at political protests, and may soon use face recognition
with body-worn cameras, to identify people in the dark, and to project
what someone might look like from a police sketch or even a small
sample of DNA.
Face recognition employs computer algorithms to pick out details about
a person’s face from a photo or video to form a template. As the
report explains, police use face recognition to identify unknown
suspects by comparing their photos to images stored in databases and
to scan public spaces to try to find specific pre-identified targets.
But no face recognition system is 100 percent accurate, and false
positives—when a person’s face is incorrectly matched to a template
image—are common. Research shows that face recognition misidentifies
African Americans and ethnic minorities, young people, and women at
higher rates than whites, older people, and men, respectively. And
because of well-documented racially biased police practices, all
criminal databases—including mugshot databases—include a
disproportionate number of African-Americans, Latinos, and immigrants.
For both reasons, inaccuracies in face recognition systems will
disproportionately affect people of color.
“The FBI, which has access to at least 400 million images and is the
central source for facial recognition identification for federal,
state, and local law enforcement agencies, has failed to address the
problem of false positives and inaccurate results,” said EFF Senior
Staff Attorney Jennifer Lynch, author of the report. “It has conducted
few tests to ensure accuracy and has done nothing to ensure its
external partners—federal and state agencies—are not using face
recognition in ways that allow innocent people to be identified as
criminal suspects.”
Lawmakers, regulators, and policy makers should take steps now to
limit face recognition collection and subject it to independent
oversight, the report says. Legislation is needed to place meaningful
checks on government use of face recognition, including rules limiting
retention and sharing, requiring notification when face prints are
collected, ensuring robust security procedures to prevent data
breaches, and establishing legal processes governing when law
enforcement may collect face images from the public without their
knowledge, the report concludes.
“People should not have to worry that they may be falsely accused of a
crime because an algorithm mistakenly matched their photo to a
suspect. They shouldn’t have to worry that their data will end up in
the hands of identify thieves because face recognition databases were
breached. They shouldn’t have to fear that their every move will be
tracked if face recognition is linked to the networks of surveillance
cameras that blanket many cities,” said Lynch. “Without meaningful
legal protections, this is where we may be headed.”
For the report:
Online version:
https://www.eff.org/wp/law-enforcement-use-face-recognition
PDF version:
https://www.eff.org/files/2018/02/15/face-off-report-1b.pdf
One pager on facial recognition:
https://www.eff.org/document/facial-recognition-one-pager
Law Enforcement Use of Face Recognition Systems Threatens Civil
Liberties, Disproportionately Affects People of Color: EFF Report
Independent Oversight, Privacy Protections Are Needed
San Francisco, California—Face recognition—fast becoming law
enforcement’s surveillance tool of choice—is being implemented with
little oversight or privacy protections, leading to faulty systems
that will disproportionately impact people of color and may implicate
innocent people for crimes they didn’t commit, says an Electronic
Frontier Foundation (EFF) report released today.
Face recognition is rapidly creeping into modern life, and face
recognition systems will one day be capable of capturing the faces of
people, often without their knowledge, walking down the street,
entering stores, standing in line at the airport, attending sporting
events, driving their cars, and utilizing public spaces. Researchers
at the Georgetown Law School estimated that one in every two American
adults—117 million people—are already in law enforcement face
recognition systems.
This kind of surveillance will have a chilling effect on Americans’
willingness to exercise their rights to speak out and be politically
engaged, the report says. Law enforcement has already used face
recognition at political protests, and may soon use face recognition
with body-worn cameras, to identify people in the dark, and to project
what someone might look like from a police sketch or even a small
sample of DNA.
Face recognition employs computer algorithms to pick out details about
a person’s face from a photo or video to form a template. As the
report explains, police use face recognition to identify unknown
suspects by comparing their photos to images stored in databases and
to scan public spaces to try to find specific pre-identified targets.
But no face recognition system is 100 percent accurate, and false
positives—when a person’s face is incorrectly matched to a template
image—are common. Research shows that face recognition misidentifies
African Americans and ethnic minorities, young people, and women at
higher rates than whites, older people, and men, respectively. And
because of well-documented racially biased police practices, all
criminal databases—including mugshot databases—include a
disproportionate number of African-Americans, Latinos, and immigrants.
For both reasons, inaccuracies in face recognition systems will
disproportionately affect people of color.
“The FBI, which has access to at least 400 million images and is the
central source for facial recognition identification for federal,
state, and local law enforcement agencies, has failed to address the
problem of false positives and inaccurate results,” said EFF Senior
Staff Attorney Jennifer Lynch, author of the report. “It has conducted
few tests to ensure accuracy and has done nothing to ensure its
external partners—federal and state agencies—are not using face
recognition in ways that allow innocent people to be identified as
criminal suspects.”
Lawmakers, regulators, and policy makers should take steps now to
limit face recognition collection and subject it to independent
oversight, the report says. Legislation is needed to place meaningful
checks on government use of face recognition, including rules limiting
retention and sharing, requiring notification when face prints are
collected, ensuring robust security procedures to prevent data
breaches, and establishing legal processes governing when law
enforcement may collect face images from the public without their
knowledge, the report concludes.
“People should not have to worry that they may be falsely accused of a
crime because an algorithm mistakenly matched their photo to a
suspect. They shouldn’t have to worry that their data will end up in
the hands of identify thieves because face recognition databases were
breached. They shouldn’t have to fear that their every move will be
tracked if face recognition is linked to the networks of surveillance
cameras that blanket many cities,” said Lynch. “Without meaningful
legal protections, this is where we may be headed.”
For the report:
Online version:
https://www.eff.org/wp/law-enforcement-use-face-recognition
PDF version:
https://www.eff.org/files/2018/02/15/face-off-report-1b.pdf
One pager on facial recognition:
https://www.eff.org/document/facial-recognition-one-pager
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