Predictive policing and algorithmic fairness.
This paper examines racial discrimination and algorithmic bias in predictive policing algorithms (PPAs), an emerging technology designed to predict threats and suggest solutions in law enforcement. We first describe what discrimination is in a case study of Chicago’s PPA. We then explain their cause...
| Publicado en: | Synthese Vol. 201; no. 6; pp. 1 - 30 |
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| Autores principales: | , |
| Formato: | Artículo |
| Publicado: |
Springer Nature
Jun2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=164121743&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 164121743 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00397857 4LI jtl: Synthese issn: 00397857 maglogo: N pubinfo: dt: Jun2023 vid: 201 iid: 6 pid: 237 pub: Springer Nature artinfo: ui: 164121743 10.1007/s11229-023-04189-0 ppf: 1 ppct: 29 formats: fmt: – @attributes: type: T – @attributes: type: P size: 548KB tig: atl: Predictive policing and algorithmic fairness. aug: au: Hung, Tzu-Wei Yen, Chun-Ping affil: Institute of European and American Studies, Academia Sinica, No. 128, Sec. 2, Academia Rd., Nankang District, 115, Taipei, Taiwan Center for Advanced Study in the Behavioral Sciences at Stanford University, 75 Alta Road, 94305, Stanford, CA, USA Department of Philosophy, Soochow University, 111-02 No. 70, Linxi Rd., Shilin Dist., Taipei, Taiwan sug: keyword: Algorithmic bias Discrimination Fairness Predictive policing Social safety net ab: This paper examines racial discrimination and algorithmic bias in predictive policing algorithms (PPAs), an emerging technology designed to predict threats and suggest solutions in law enforcement. We first describe what discrimination is in a case study of Chicago’s PPA. We then explain their causes with Broadbent’s contrastive model of causation and causal diagrams. Based on the cognitive science literature, we also explain why fairness is not an objective truth discoverable in laboratories but has context-sensitive social meanings that need to be negotiated through democratic processes. With the above analysis, we next predict why some recommendations given in the bias reduction literature are not as effective as expected. Unlike the cliché highlighting equal participation for all stakeholders in predictive policing, we emphasize power structures to avoid hermeneutical lacunae. Finally, we aim to control PPA discrimination by proposing a governance solution—a framework of a social safety net. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Synthese is a copyright of Springer, 2023. All Rights Reserved. item: Synthese holder: Springer Nature dt: @attributes: year: 2023 holdings: @attributes: islocal: N |
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