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Author Yeung, Douglas, author

Title Face recognition technologies : designing systems that protect privacy and prevent bias / Douglas Yeung, Rebecca Balebako, Carlos Ignacio Gutierrez, Michael Chaykowsky
Published Santa Monica, Calif. : RAND Corporation, [2020]
©2020

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Description 1 online resource (xviii, 67 pages)
Contents Introduction -- Background on Face Recognition Technology: A Primer -- Selected Face Recognition Technology Policies in the United States -- Face Recognition Technologies in Action: Two Use Cases -- Study Overview and Areas for Future Research
Summary The objective of face recognition technologies (FRTs) is to efficiently detect and recognize people captured on camera. Although these technologies have many practical security-related purposes, advocacy groups and individuals have expressed apprehensions about their use. The research reported here was intended to highlight for policymakers the high-level privacy and bias implications of FRT systems. In the report, the authors describe privacy as a person's ability to control information about them. Undesirable bias consists of the inaccurate representation of a group of people based on characteristics, such as demographic attributes. Informed by a literature review, the authors propose a heuristic with two dimensions: consent status (with or without consent) and comparison type (one-to-one or some-to-many). This heuristic can help determine a proposed FRT's level of privacy and accuracy. The authors then use more in-depth case studies to identify "red flags" that could indicate privacy and bias concerns: complex FRTs with unexpected or secondary use of personal or identifying information; use cases in which the subject does not consent to image capture; lack of accessible redress when errors occur in image matching; the use of poor training data that can perpetuate human bias; and human interpretation of results that can introduce bias and require additional storage of full-face images or video. This report is based on an exploratory project and is not intended to comprehensively introduce privacy, bias, or FRTs. Future work in this area could include examinations of existing systems, reviews of their accuracy rates, and surveys of people's expectations of privacy in government use of FRTs
Bibliography Includes bibliographical references (pages 53-67)
Notes Print version record
Subject Human face recognition (Computer science)
Privacy, Right of.
Physical-appearance-based bias -- Prevention
Biometric Identification
Privacy, Right of
Human face recognition (Computer science)
Genre/Form Electronic books
Form Electronic book
Author Balebako, Rebecca, author
Gutierrez, Carlos Ignacio, author
Chavkowsky, Michael, author
Rand Corporation.
ISBN 9781977404596
1977404596