Three Lessons for and from Algorithmic Discrimination.
Algorithmic discrimination has rapidly become a topic of intense public and academic interest. This article explores three issues raised by algorithmic discrimination: (1) the distinction between direct and indirect discrimination, (2) the notion of disadvantageous treatment, and (3) the moral badne...
| Publicado en: | Res Publica (13564765) Vol. 29; no. 2; pp. 213 - 236 |
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| Formato: | Artículo |
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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=163852954&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 163852954 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 13564765 NMV jtl: Res Publica (13564765) issn: 13564765 maglogo: N pubinfo: dt: Jun2023 vid: 29 iid: 2 pid: 237 pub: Springer Nature artinfo: ui: 163852954 10.1007/s11158-023-09579-2 ppf: 213 ppct: 23 formats: fmt: – @attributes: type: T – @attributes: type: P size: 778KB tig: atl: Three Lessons for and from Algorithmic Discrimination. aug: au: Thomsen, Frej Klem affil: Danish National Centre for Ethics, Copenhagen, Denmark su: Discrimination (Sociology) Fairness Algorithms Artificial intelligence Prejudices Decision making sug: subj: Discrimination (Sociology) Fairness Algorithms Artificial intelligence Prejudices Decision making keyword: AI Algorithm Bias Discrimination Indirect discrimination ab: Algorithmic discrimination has rapidly become a topic of intense public and academic interest. This article explores three issues raised by algorithmic discrimination: (1) the distinction between direct and indirect discrimination, (2) the notion of disadvantageous treatment, and (3) the moral badness of discriminatory automated decision-making. It argues that some conventional distinctions between direct and indirect discrimination appear not to apply to algorithmic discrimination, that algorithmic discrimination may often be discrimination between groups, as opposed to against groups, and that it is not necessarily the case that morally bad algorithmic discrimination gives us reason to not use automated decision-making. For each of the three issues, the article explores implications for algorithmic discrimination, suggests some alternative answers, and clarifies how we may want to think of discrimination more broadly in light of lessons drawn from the context of algorithmic discrimination. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Res Publica (13564765) is a copyright of Springer, 2023. All Rights Reserved. item: Res Publica (13564765) holder: Springer Nature dt: @attributes: year: 2023 holdings: @attributes: islocal: N |
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