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公众对自动面部识别技术在全球刑事司法系统中应用的态度。

Public attitudes towards the use of automatic facial recognition technology in criminal justice systems around the world.

机构信息

School of Psychology, University of Lincoln, Lincoln, Lincolnshire, United Kingdom.

School of Psychology, University of New South Wales, Sydney, New South Wales, Australia.

出版信息

PLoS One. 2021 Oct 13;16(10):e0258241. doi: 10.1371/journal.pone.0258241. eCollection 2021.

DOI:10.1371/journal.pone.0258241
PMID:34644306
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8513835/
Abstract

Automatic facial recognition technology (AFR) is increasingly used in criminal justice systems around the world, yet to date there has not been an international survey of public attitudes toward its use. In Study 1, we ran focus groups in the UK, Australia and China (countries at different stages of adopting AFR) and in Study 2 we collected data from over 3,000 participants in the UK, Australia and the USA using a questionnaire investigating attitudes towards AFR use in criminal justice systems. Our results showed that although overall participants were aligned in their attitudes and reasoning behind them, there were some key differences across countries. People in the USA were more accepting of tracking citizens, more accepting of private companies' use of AFR, and less trusting of the police using AFR than people in the UK and Australia. Our results showed that support for the use of AFR depends greatly on what the technology is used for and who it is used by. We recommend vendors and users do more to explain AFR use, including details around accuracy and data protection. We also recommend that governments should set legal boundaries around the use of AFR in investigative and criminal justice settings.

摘要

自动人脸识别技术(AFR)在全球刑事司法系统中被越来越多地使用,但迄今为止,尚未有国际调查公众对其使用的态度。在研究 1 中,我们在英国、澳大利亚和中国(处于采用 AFR 不同阶段的国家)进行了焦点小组讨论,在研究 2 中,我们通过一项问卷调查收集了来自英国、澳大利亚和美国的 3000 多名参与者的数据,调查他们对刑事司法系统中使用 AFR 的态度。我们的研究结果表明,尽管参与者总体上的态度和背后的推理一致,但各国之间仍存在一些关键差异。与英国和澳大利亚相比,美国人更能接受跟踪公民、更能接受私营公司使用 AFR,对警察使用 AFR 的信任度更低。我们的研究结果表明,对 AFR 使用的支持在很大程度上取决于技术的用途和使用者。我们建议供应商和用户更详细地解释 AFR 的使用情况,包括准确性和数据保护方面的细节。我们还建议政府在调查和刑事司法环境中对 AFR 的使用设定法律界限。

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1
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2
Human-algorithm teaming in face recognition: How algorithm outcomes cognitively bias human decision-making.人脸识别中的人机协作:算法结果如何认知地影响人类决策。
PLoS One. 2020 Aug 21;15(8):e0237855. doi: 10.1371/journal.pone.0237855. eCollection 2020.
3
Forensic science evidence: Naive estimates of false positive error rates and reliability.
在欧洲人工智能法案和可信系统发展的背景下,面部处理应用的前景。
Sci Rep. 2022 Jun 23;12(1):10688. doi: 10.1038/s41598-022-14981-6.
法庭科学证据:错误阳性率和可靠性的天真估计。
Forensic Sci Int. 2019 Sep;302:109877. doi: 10.1016/j.forsciint.2019.109877. Epub 2019 Jul 26.
4
Human-Computer Interaction in Face Matching.面部匹配中的人机交互
Cogn Sci. 2018 Jun 28;42(5):1714-32. doi: 10.1111/cogs.12633.
5
Face recognition accuracy of forensic examiners, superrecognizers, and face recognition algorithms.法医鉴定人、超级识别者和人脸识别算法的人脸识别准确率。
Proc Natl Acad Sci U S A. 2018 Jun 12;115(24):6171-6176. doi: 10.1073/pnas.1721355115. Epub 2018 May 29.
6
Amazon's Mechanical Turk: A New Source of Inexpensive, Yet High-Quality, Data?亚马逊土耳其机器人:一种新的廉价、高质量数据来源?
Perspect Psychol Sci. 2011 Jan;6(1):3-5. doi: 10.1177/1745691610393980. Epub 2011 Feb 3.
7
Deep learning.深度学习。
Nature. 2015 May 28;521(7553):436-44. doi: 10.1038/nature14539.
8
Biometrics, identification and surveillance.生物识别技术、身份识别与监视。
Bioethics. 2008 Nov;22(9):499-508. doi: 10.1111/j.1467-8519.2008.00697.x.