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Facial Recognition and the Fourth Amendment

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Facial Recognition and the Fourth Amendment University of Minnesota Law School Scholarship Repository Minnesota Law Review 2021 Facial Recognition and the Fourth Amendment Andrew Guthrie Ferguson Follow this and additional works at: https://scholarship.law.umn.edu/mlr Part of the Law Commons Recommended Citation Ferguson, Andrew Guthrie, "Facial Recognition and the Fourth Amendment" (2021). Minnesota Law Review. 3204. https://scholarship.law.umn.edu/mlr/3204 This Article is brought to you for free and open access by the University of Minnesota Law School. It has been accepted for inclusion in Minnesota Law Review collection by an authorized administrator of the Scholarship Repository. For more information, please contact [email protected]. Article Facial Recognition and the Fourth Amendment Andrew Guthrie Ferguson† Introduction ......................................................................................................... 1106 I. Facial Recognition Technology ............................................................... 1109 A. The Technology ..................................................................................... 1110 B. Police Use of Facial Recognition Technology ........................... 1115 1. Face Surveillance .......................................................................... 1116 2. Face Identification ....................................................................... 1119 3. Face Tracking ................................................................................. 1122 4. Non-Law Enforcement Purposes ........................................... 1124 II. The Fourth Amendment and the Privacy Problem of Facial Recognition .................................................................................................... 1126 A. Pre-Digital Face Searches ................................................................ 1127 B. Future-Proofing the Fourth Amendment: A Theory ........... 1129 1. Anti-Equivalence Principle .................................................... 1132 2. Anti-Aggregation Principle .................................................... 1134 3. Anti-Permanence Principle .................................................... 1135 4. Anti-Tracking Principle ........................................................... 1136 5. Anti-Arbitrariness Principle .................................................. 1137 6. Anti-Permeating Surveillance Principle ........................... 1139 7. Systems of Surveillance ........................................................... 1140 C. Analysis: How the Fourth Amendment Fits Facial Recognition Surveillance Technology ....................................... 1141 1. Face Surveillance ........................................................................ 1142 2. Face Identification ..................................................................... 1150 3. Face Tracking ............................................................................... 1152 † Professor of Law, American University Washington College of Law. Thank you to Professors Richard Re, Elizabeth Joh, Megan Thorn Stevenson, Stephen Henderson, Kiel Brennan-Marquez, Manon Jendly, Elana Zeide, Alicia Solow-Niederman, Barry Friedman, Kate Weisburd, Avlana Eisenberg, Chad Flanders, Lewis Grossman, and Daniela Kraiem. Thank you to Professor Andrew Selbst for providing the insight about how Carpenter forces a conversation about broad versus deep surveillance technolo- gies. Thank you also to the ABA/AALS Criminal Justice Scholars workshop for terrific feedback. Copyright © 2021 by Andrew Guthrie Ferguson. 1105 1106 MINNESOTA LAW REVIEW [105:1105 4. Non-Law Enforcement Purposes ...................................... 1161 D. Conclusion: Facial Recognition and a Continuum of Systemic Searches ............................................................................ 1164 III. The Fourth Amendment and the Legitimacy Problem of Facial Recognition .................................................................................... 1164 A. Ethical AI and Concerns About Error, Bias, Fairness, and Transparency ............................................................................ 1167 B. The Fourth Amendment and Error, Bias, Transparency, and Fairness ......................................................... 1173 1. Error and Policing .................................................................... 1173 2. Bias ................................................................................................. 1181 3. Fairness ........................................................................................ 1185 4. Transparency ............................................................................. 1188 C. Conclusion on Error, Bias, Transparency, and Fairness in Facial Recognition and the Fourth Amendment ............ 1191 1. Human v. Programmatic Error/Bias ................................ 1191 2. Isolated v. Recurring Error/Bias ....................................... 1193 3. A Fourth Amendment Framework for Surveillance Systems ......................................................................................... 1195 IV. A Legislative Framework for Facial Recognition ......................... 1197 A. Facial Recognition & Privacy: Legislative Principles ........ 1197 1. Ban Generalized Face Surveillance ................................... 1197 2. Require a Probable Cause Warrant for Face Identification .............................................................................. 1199 3. Ban or Require a Probable Cause-Plus Standard (akin to the Wiretap Act) for Face Tracking ................. 1202 4. Limit Face Verification to International Border Crossings ...................................................................................... 1205 5. Require Accountability Around Error, Bias, Fairness, and Transparency ................................................ 1207 Conclusion ............................................................................................................ 1210 INTRODUCTION Artificial intelligence systems are edging into policing.1 Massive troves of sensor data, unstructured video surveillance feeds, and many other digital clues allow artificial intelligence to make sense of 1. Andrew D. Selbst, Disparate Impact in Big Data Policing, 52 GA. L. REV. 109, 113 (2017). See generally Sarah Brayne, The Criminal Law and Law Enforcement Impli- cations of Big Data, 14 ANN. REV. L. & SOC. SCI. 293, 294 (2018); Elizabeth E. Joh, The New Surveillance Discretion: Automated Suspicion, Big Data, and Policing, 10 HARV. L. & POL’Y REV. 15, 15–16 (2016). 2021] FACIAL RECOGNITION 1107 otherwise overwhelming amounts of information.2 The ability to har- ness artificial intelligence for police surveillance and investigation portends an era-defining shift of power and capabilities. Leading the charge of game-changing new surveillance technolo- gies is facial recognition—namely the ability to identify faces among crowds, in videos, in photo datasets, and almost everywhere else.3 From scanning Super Bowl crowds and public streets, to searching stored arrestee mugshots, police are beginning to experiment with fa- cial recognition technology.4 This development is also causing great public concern, because the scope and scale of these new surveillance systems threatens to upend the existing power relationship between police and the people.5 This Article explores the constitutional design problem at the heart of facial recognition surveillance systems. One might hope that the Fourth Amendment6—designed to restrain police power and en- acted to limit governmental overreach—would have something to say about this powerful and overreaching generalized surveillance 2. See generally ANDREW GUTHRIE FERGUSON, THE RISE OF BIG DATA POLICING: SUR- VEILLANCE, RACE, AND THE FUTURE OF LAW ENFORCEMENT (2017). 3. CLARE GARVIE, ALVARO M. BEDOYA & JONATHAN FRANKLE, GEORGETOWN L. CTR. ON PRIV. & TECH., THE PERPETUAL LINE-UP: UNREGULATED POLICE FACE RECOGNITION IN AMERICA 1 (2016), https://www.perpetuallineup.org/sites/default/files/2016-12/The%20 Perpetual%20Line-Up%20-%20Center%20on%20Privacy%20and%20Technology% 20at%20Georgetown%20Law%20-%20121616.pdf [https://perma.cc/S48P-PL53]. 4. See, e.g., Declan McCullagh, Call It Super Bowl Face Scan I, WIRED (Feb. 2, 2001), https://www.wired.com/politics/law/news/2001/02/41571 [https://perma.cc/ BS67-UJVA]; Dakin Andone, Police Used Facial Recognition To Identify the Capital Ga- zette Shooter. Here’s How It Works, CNN (June 29, 2018, 6:22 PM), https://www.cnn .com/2018/06/29/us/facial-recognition-technology-law-enforcement/index.html [https://perma.cc/7GHK-UDZH]; Benjamin Powers, Eyes over Baltimore: How Police Use Military Technology To Secretly Track You, ROLLING STONE (Jan. 6, 2017), https:// www.rollingstone.com/culture/culture-features/eyes-over-baltimore-how-police -use-military-technology-to-secretly-track-you-126885 [https://perma.cc/F3RK -CDCK]. 5. John D. Woodward, Biometric Scanning, Law & Policy: Identifying the Con- cerns—Drafting the Biometric Blueprint, 59 U. PITT. L. REV. 97, 134 (1997) (“Any high- integrity identifier [such as biometric scanning] represents a threat to civil liberties, because it represents the basis for a ubiquitous identification scheme, and such a scheme provides enormous power over the populace. All human behavior would be- come transparent to the state, and the scope for non-conformism and dissent would be muted to the point envisaged by the anti-Utopian novelists.” (quoting Roger Clarke, Human Identification in
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