Machine Learning and the Re‐Enchantment of the Administrative State.
Machine learning algorithms present substantial promise for more effective decision‐making by administrative agencies. However, some of these algorithms are inscrutable, namely, they produce predictions that humans cannot understand or explain. This trait is in tension with the emphasis on reason‐gi...
| Publicado en: | Modern Law Review Vol. 87; no. 2; pp. 371 - 398 |
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| Autores principales: | , |
| Formato: | Artículo |
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Wiley-Blackwell
Mar2024
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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=175502820&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 175502820 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00267961 D8H jtl: Modern Law Review issn: 00267961 maglogo: Y pubinfo: dt: Mar2024 vid: 87 iid: 2 pid: 480 pub: Wiley-Blackwell artinfo: ui: 175502820 10.1111/1468-2230.12843 ppf: 371 ppct: 27 formats: fmt: – @attributes: type: T – @attributes: type: P size: 289KB tig: atl: Machine Learning and the Re‐Enchantment of the Administrative State. aug: au: Sarid, Eden Ben‐Zvi, Omri su: Machine learning Administrative law Computers in public administration Decision making Government agencies sug: subj: Machine learning Administrative law Computers in public administration Decision making Government agencies ab: Machine learning algorithms present substantial promise for more effective decision‐making by administrative agencies. However, some of these algorithms are inscrutable, namely, they produce predictions that humans cannot understand or explain. This trait is in tension with the emphasis on reason‐giving in administrative law. The article explores this tension, advancing two interrelated arguments. First, providing adequate reasons is a significant facet of respecting individuals' agency. Incorporating inscrutable algorithmic predictions into administrative decision‐making compromises this normative ideal. Second, as a long‐term concern, the use of inscrutable algorithms by administrative agencies may generate systemic effects by gradually reducing the realm of the humanly explainable in public life, a phenomenon Max Weber termed 're‐enchantment'. As a result, the use of inscrutable machine learning algorithms might trigger a special kind of re‐enchantment, making us comprehend less rather than more of shared human experience, and consequently altering the way we understand the administrative state and experience public life. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Copyright of Modern Law Review is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. item: Modern Law Review holder: Wiley-Blackwell dt: @attributes: year: 2024 holdings: @attributes: islocal: N |
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