Collaborative Research: Standard Grant: Artificial Intelligence and Predictive Policing: An Ethical Analysis

合作研究：标准拨款：人工智能和预测性警务：伦理分析

• 批准号: 1917712
• 负责人: Duncan Purves
• 金额: $ 26.96万
• 依托单位: University of Florida
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1917712&HistoricalAwards=false
• 关键词: Collaborative; Research; Standard; Grant; Artificial

This project is a study of the use of artificial intelligence to assist police on patrol by using massive troves of historical crime data to train machine learning algorithms to anticipate the timing and location of criminal activity. Predictive policing has come under intense criticisms from civil rights groups, academics, and communities that have been subject to predictive policing. These criticisms include its recapitulation of racially biased patterns of policing, its further burdening of marginalized communities, and its infringement on the liberties of targeted communities. The researchers propose to examine these claims and to develop best practices for the development and deployment of algorithmic policing programs. The results of this project promise to benefit police departments, communities patrolled based on algorithmic crime predictions, and public understanding of the societal and ethical implications of predictive policing. The aims of this grant are to examine and develop viable ethical frameworks for the assessment of predictive policing practices. In doing so, the researchers will propose and evaluate novel considerations that might bear on the ethics of predictive policing. They will also develop empirically grounded recommendations for the ethically sensitive and effective development and use of predictive policing. The results of this project promise to advance understanding and illuminate fertile new areas of research in moral philosophy, technology ethics, sociology, and criminology. They also will have clear relevance for other algorithmic technologies with similar implications for justice including algorithms that predict criminal sentences, make healthcare diagnoses, and serve as gatekeepers to government benefits (all of which are currently in use).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目是对使用人工智能使用大量历史犯罪数据来训练机器学习算法来预测犯罪活动的时机和位置的研究。预测性警务受到了受到预测警务的民权团体，学者和社区的强烈批评。这些批评包括其对种族偏见的警务模式的概括，对边缘化社区的进一步负担以及侵犯了目标社区的自由。研究人员建议研究这些主张，并为制定和部署算法警务计划开发最佳实践。该项目的结果有望使警察部门受益，社区根据算法犯罪预测进行巡逻，以及公众对预测性警务的社会和道德含义的理解。这笔赠款的目的是检查和开发可行的道德框架，以评估预测性警务实践。通过这样做，研究人员将提出和评估可能遵循预测性警务伦理的新颖考虑因素。他们还将为伦理敏感有效的发展以及预测性警务的使用方面提出基础的建议。该项目的结果有望提高理解并阐明道德哲学，技术伦理，社会学和犯罪学研究的新研究领域。他们还将与其他算法技术具有明确的相关性，对正义的影响有类似的影响，包括预测刑事刑期，做出医疗保健诊断并充当政府福利的守门人（所有这些目前正在使用）。本奖项奖反映了NSF的立法使命，并通过对基金会的智力效果进行评估，并值得通过评估来进行评估。

项目成果

Public Trust, Institutional Legitimacy, and the Use of Algorithms in Criminal Justice

公众信任、机构合法性以及刑事司法中算法的使用

• DOI: 10.5406/21520542.36.2.03
• 发表时间: 2022
• 期刊: Public Affairs Quarterly
• 作者: Purves, Duncan;Davis, Jeremy
• 通讯作者: Davis, Jeremy

Should Algorithms that Predict Recidivism Have Access to Race?

预测累犯的算法是否应该考虑种族问题？

• DOI: 10.5406/21521123.60.2.07
• 发表时间: 2023
• 期刊: American Philosophical Quarterly
• 影响因子: 0.8
• 作者: Purves, Duncan;Davis, Jeremy
• 通讯作者: Davis, Jeremy

A Machine Learning Evaluation Framework for Place-based Algorithmic Patrol Management

基于地点的算法巡逻管理的机器学习评估框架

• DOI: 10.2139/ssrn.4549861
• 发表时间: 2023
• 期刊: SSRN Electronic Journal
• 作者: Purves, Duncan;Jenkins, Ryan
• 通讯作者: Jenkins, Ryan

A review of predictive policing from the perspective of fairness

• DOI: 10.1007/s10506-021-09286-4
• 发表时间: 2021-04-15
• 期刊: ARTIFICIAL INTELLIGENCE AND LAW
• 影响因子: 4.1
• 作者: Alikhademi, Kiana;Drobina, Emma;Gilbert, Juan E.
• 通讯作者: Gilbert, Juan E.

Fairness in Algorithmic Policing

算法监管的公平性

• DOI: 10.1017/apa.2021.39
• 发表时间: 2022
• 期刊: Journal of the American Philosophical Association
• 影响因子: 1
• 作者: Purves, Duncan