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- Title
THE DANGERS OF FACIAL RECOGNITION TECHNOLOGY IN SUBSIDIZED HOUSING.
- Authors
Ewert, Michelle Y.
- Abstract
The use of facial recognition technology (FRT) in subsidized housing makes life more difficult for subsidized tenants, who are disproportionately women, seniors, and people of color. Conditioning building access on facial recognition is problematic because flaws in the technology make it hard for systems to recognize people with darker skin, women, children, trans and non-binary individuals, and seniors. As a result, tenants are often stranded outside and unable to enter their homes. Perhaps more chilling is the gross invasion of privacy this technology presents, especially when data from facial recognition and surveillance systems are shared with the police. Tenants must surrender their biometric data to third parties with no assurance of its security. Further, landlords and police can use this data to track tenants' movements and activities. Finally, this technology interferes with tenants' personal relationships as it surveils their family and friends and puts tenants at risk of eviction if the systems misidentify visitors as people on ban lists or those with outstanding arrest warrants. This intrusion into subsidized tenants' privacy is yet another example of the hyper-surveillance of means-tested public benefits recipients and of the over-policing in Black and Brown communities. With limited resources and few alternatives for affordable housing, subsidized tenants have no choice but to accept this invasion into their privacy. Because the harms that low-income tenants experience through facial recognition technology and surveillance far outweigh the benefits to the community, this Article calls for the abolition of facial recognition technology in the subsidized housing context, or, at a minimum, heavy regulation on its use. The Article presents workable solutions to protect tenants' privacy, including proposed legislation, agency rules and guidance, contracts with housing providers, and community advisory boards.
- Subjects
HUMAN facial recognition software; LANDLORD-tenant relations; HOUSING subsidies; FACE perception; SURVEILLANCE detection
- Publication
New York University Journal of Legislation & Public Policy, 2023, Vol 25, Issue 3, p665
- ISSN
1094-513X
- Publication type
Article