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Facial Recognition Facial Recognition Portland Police Bureau Assistant Chief Ryan Lee Challenges • Law enforcement agencies who have failed to follow Department of Justice recommendations for Facial Recognition programs have consistently jeopardized public trust. 1 • Media has not shared complete information from recent National Institute of Science Technology (NIST) reports, and overemphasized studies where old algorithms2 and outdated science were used. 1. Face Recognition Police Development Template. Washington, DC: Bureau of Justice Assistance. Retrieved from https://bja.ojp.gov/sites/g/files/xyckuh186/files/Publications/Face- Recognition-Policy-Development-Template-508-compliant.pdf 2 Face Recognition Vendor Test Part 3: Demographic Effects. Retrieved from https://nvlpubs.nist.gov/nistpubs/ir/2019/NIST.IR.8280.pdf Analysis • NIST research (2019) revealed the accuracy of facial recognition algorithms have improved more than 20x since 2014. NIST found that 0.2% of searches, in a database of 26.6 million photos, failed to match the correct image, compared with a 4% failure rate in 2014, 1which is a 20x improvement over four years. • NIST highlighted Georgetown and MIT studies used 2014 algorithms, which produced high errors and were not reproduced with modern technology. 1 1. NIST Evaluation Shows Advance in Face Recognition Software’s Capabilities. Retrieved: https://www.nist.gov/news-events/news/2018/11/nist-evaluation-shows-advance-face- recognition-softwares-capabilities Potentials with Proper Oversight • Success or failure rests on policies and practices. • With more than 80 nodal points, a face is a unique blueprint distinguishing individual’s biometrics. As neural scientists suggest that no two faces are identical, with a clear photo FR can be more than 99% accurate.1 • Countless testimonials confirm FR systems have led to the arrests of dangerous perpetrators and missing endangered individuals. 2 3 4 1. Castro, D., & McLaughlin, D. (2018). Banning Police Use of Facial Recognition Would Undercut Public Safety. Retrieved from Information Technology & Innovation Foundation: https://itif.org/publications/2018/07/30/banning-police-use-facial-recognition-would-undercut-public-safety 2. O'Neill. (2019, June 9). How Facial Recognition Makes You Safer. The New York Times. Retrieved from https://www.nytimes.com/2019/06/09/opinion/facial-recognition-police-new-york-city.html 3. Newberg, K. (2020, January 19). Las Vegas Police Use Facial Recognition to Arrest Assault Suspect. Las Vegas Review-Journal. Retrieved from https://www.reviewjournal.com/crime/las-vegas-police-use- facial-recognition-to-arrest-assault-suspect-1938801/ 4. Wenger, Y. (2018, June 29). Police Used Facial Recognition Technology to Help Identify Uncooperative Suspect in Capital Gazette Shooting. The Baltimore Sun. Retrieved from http://www.baltimoresun.com/news/crime/bs-md-facial-recognition-suspect-identity-20180629-story.html Benefits • Ability to dispel or bring clarity to those who have been wrongly convicted. • As technology continues to improve it has the ability to mitigate and limit human bias. According to the Innocence Project, 71% of its documented instances of false convictions are tied to mistaken witness identifications. 1 • Efficiency gains - Allow law enforcement to better manage resources/time; days spent otherwise searching through files for possible suspect photo in databases. 1. Eyewitness Identification Reform. Retrieved from: https://www.innocenceproject.org/eyewitness-identification-reform/ Limited Use • Post Analysis – If deemed appropriate for use by council: • Public input and oversight from onset. • Facial recognition must be managed through stringent procedures which avoid impropriety, privacy issues and liability and build public trust. • Limited use only with highly regarded and vetted algorithms recognized through third party testing (such as by NIST). 1 • If approved for use, the Police Bureau would only recommend using Facial Recognition in a limited fashion for Violent person crimes. • Any additional uses would require further approval. 1. NIST Evaluation Shows Advance in Face Recognition Software’s Capabilities. Retrieved: https://www.nist.gov/news-events/news/2018/11/nist-evaluation-shows-advance-face- recognition-softwares-capabilities Potential Policy Restrictions • Investigators would not use facial recognition software as stand-alone probable cause or sole determinant when seeking probable cause. • Officers would use confidence thresholds of 99% or higher and not make decisions based solely on the predictions returned from facial recognition software. • At least two investigators would manually conduct confirmation through additional independent review. Potential Policy Restrictions • Authorized and trained Portland Police Bureau members would only perform a face recognition search during the course of lawful duties when, in accordance with applicable law, the individual’s image was captured in a place where the individual has no reasonable expectation of privacy. • Oversight committee with public input and accountability would be established • Annual report submitted to Auditor’s Office to ensure proper review/public trust • PPB would not use live monitoring; only lawfully obtained images of suspects, pursuant to authorized criminal investigations, which would otherwise be disseminated by a detective in a flyer. Portland Police Bureau Recommendations • Moratorium: As research improves we need to be able to evaluate the benefits of technology and place a ban because other agencies have mismanaged the technology. • An Exemption for “Derivative Products” of Facial Recognition Technology • Exemption for “Lab” Analysis – PPB would like to test facial recognition on post-adjudication (cases already through the court). • Seek Input from Facial Recognition Technology Developers and Neutral Researchers References • 18 USC 2265. (n.d.). Full Faith and Credit Given to Protection Orders. Retrieved from https://uscode.house.gov/view.xhtml?req=granuleid:USC-prelim-title18- section2265&num=0&edition=prelim • Castro, D. (2019, May 22). Statement to the House Committee on Oversight and Reform Regarding Facial Recognition and Civil Liberties. Retrieved from Information Technology & Innovation Foundation: https://itif.org/publications/2019/05/22/statement-house-committee-oversight-and-reform-regarding-facial-recognition • Castro, D. (2019, January 27). Note to Press: Facial Analysis Is Not Facial Recognition. Retrieved from Information Technology & Innovation Foundation: https://itif.org/publications/2019/01/27/note-press-facial-analysis-not-facial-recognition • Castro, D., & McLaughlin, D. (2018). Banning Police Use of Facial Recognition Would Undercut Public Safety. Retrieved from Information Technology & Innovation Foundation: https://itif.org/publications/2018/07/30/banning-police-use-facial-recognition-would-undercut-public-safety • Eyewitness Identification Reform. (n.d.). Retrieved January 15, 2020, from Innocence Project: https://www.innocenceproject.org/eyewitness-identification-reform/ • (2017). Face Recognition Police Development Template. Washington, DC: Bureau of Justice Assistance. Retrieved from https://bja.ojp.gov/sites/g/files/xyckuh186/files/Publications/Face-Recognition-Policy-Development-Template-508-compliant.pdf • Grother, P., Mei, N., & Hanaoka, K. (2019). Face Recognition Vendor Test Part 3: Demographic Effects. Washington, DC: National Institute of Standards and Technology. Retrieved from https://nvlpubs.nist.gov/nistpubs/ir/2019/NIST.IR.8280.pdf • Newberg, K. (2020, January 19). Las Vegas Police Use Facial Recognition to Arrest Assault Suspect. Las Vegas Review-Journal. Retrieved from https://www.reviewjournal.com/crime/las-vegas-police-use-facial-recognition-to-arrest-assault-suspect-1938801/ • NIST Evaluation Shows Advance in Face Recognition Software’s Capabilities. (2018, November 30). Retrieved from National Institute of Standards and Technology: https://www.nist.gov/news-events/news/2018/11/nist-evaluation-shows-advance-face-recognition-softwares-capabilities • O'Neill. (2019, June 9). How Facial Recognition Makes You Safer. The New York Times. Retrieved from https://www.nytimes.com/2019/06/09/opinion/facial- recognition-police-new-york-city.html • ORS 133.055 (2) (a). (n.d.). Criminal Citation - domestic violence . Retrieved from https://www.oregonlaws.org/ors/133.055 • ORS 133.310. (n.d.). Authority of Peace Officer to Arrest Without Warrant. Retrieved from https://www.oregonlaws.org/ors/133.310 • ORS 807.026. (n.d.). Management of Biometric Data. Retrieved from https://www.oregonlaws.org/ors/807.026 • Wenger, Y. (2018, June 29). Police Used Facial Recognition Technology to Help Identify Uncooperative Suspect in Capital Gazette Shooting. The Baltimore Sun. Retrieved from http://www.baltimoresun.com/news/crime/bs-md-facial-recognition-suspect-identity-20180629-story.html.
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