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1 Civil Rights Concerns regarding Law Enforcement Use of Face Recognition Technology 1 (2021)

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June 3, 2021
Civil Rights Concerns Regarding Law Enforcement Use of Face Recognition Technology
Across the country, local, state, and federal law enforcement and immigration agencies use face
recognition systems to identify, track, and target individuals. More than half of all U.S. adults are
already in face recognition databases used for criminal investigations.' This technology
dramatically expands law enforcement's power and poses severe threats to everyone's safety,
wellbeing, and freedoms of expression and association-but especially for Black and Brown
communities, Muslim communities, immigrant communities, Indigenous communities, and other
people historically and currently marginalized and targeted by policing.
Much of the public debate has focused on the alarming inaccuracy of face recognition systems,
particularly on women and people with darker skin.2 In at least three cases that are publicly
known, police have relied on erroneous face recognition identifications to make wrongful arrests
of Black men, underscoring the dangerous nature of this technology in the hands of law
enforcement.3
But improvements in the technology's accuracy will not address the fundamental problem: face
recognition expands the scope and power of law enforcement, an institution that has a long and
documented history of racial discrimination and racial violence that continues to this day. In the
context of policing, face recognition is always dangerous-no matter its accuracy. Throughout
our nation's history, law enforcement has used surveillance to silence dissent and to maintain
white supremacy, from slave patrols4 to the FBI's COINTELPRO program. Face recognition and
other modern surveillance technologies promise to continue a history that has shown itself to be
incompatible with the freedoms and rights of Black and Brown communities.
1 Clare Garvie, Alvaro Bedoya, and Jonathan Frankle, The Perpetual Line-Up: Unregulated Police Face Recognition
in America, Geo. L. Ctr. on Privacy & Tech. 42 (Oct. 18, 2016), available athtt2s:/Iwwwoerietuallineu .orol.
2 Joy Buolamwini and Timnit Gebru, Gender Shades: Intersectional Accuracy Disparities in Commercial Gender
Classification (2018), available at htto://proceedin s.mlr press/v$1/buolamwinil8a/buolamwini18a.odf; Patrick
Grother, Mei Ngan, Kayee Hanaoka, Face Recognition Vendor Test (FRVT) Part 3: Demographic Effects, NISTIR
8280, Nat'l Inst. of Standards and Technology (December 2019), available at
https://nvlpubs.nist.gov/nistpubs/ir/2019/NIST.IR.8280.pdf.
3 Kashmir Hill, Another Arrest, and Jail Time, Due to a Bad Facial Recognition Match, N.Y. Times (Dec. 29, 2020),
htgs://www. nytimes. com/2020/1 2/29/tech nologv/facial-recog nition-misidentif-jai I.htm.
4 Hassett-Walker, Connie, The Racist Roots of American Policing: From Slave Patrols to Traffic Stops, The
Conversation (June 2, 2020), available at
https://theconversation c                                                   12816.

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