The epistemological foundations of data science: a critical review.
The modern abundance and prominence of data have led to the development of “data science” as a new field of enquiry, along with a body of epistemological reflections upon its foundations, methods, and consequences. This article provides a systematic analysis and critical review of significant open p...
| Publicado en: | Synthese Vol. 200; no. 6; pp. 1 - 26 |
|---|---|
| Autores principales: | , , , , |
| Formato: | Artículo |
| Publicado: |
Springer Nature
Dec2022
|
| 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=160059213&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 160059213 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00397857 4LI jtl: Synthese issn: 00397857 maglogo: N pubinfo: dt: Dec2022 vid: 200 iid: 6 pid: 237 pub: Springer Nature artinfo: ui: 160059213 10.1007/s11229-022-03933-2 ppf: 1 ppct: 25 formats: fmt: – @attributes: type: T – @attributes: type: P size: 663KB tig: atl: The epistemological foundations of data science: a critical review. aug: au: Desai, Jules Watson, David Wang, Vincent Taddeo, Mariarosaria Floridi, Luciano affil: Faculty of Philosophy, University of Oxford, Radcliffe Humanities, Woodstock Road, OX2 6GG, Oxford, UK Department of Informatics, King's College London, Bush House, 30 Aldwych, WC2B 4BG, London, UK Department of Computer Science, University of Oxford, Wolfson Building, Parks Road, OX1 3QD, Oxford, UK Oxford Internet Institute, University of Oxford, 1 St Giles', OX1 3JS, Oxford, UK The Alan Turing Institute, British Library, 96 Euston Rd, NW1 2DB, London, UK Department of Legal Studies, University of Bologna, Via Zamboni, 27, 40126, Bologna, Italy sug: keyword: Black box Data science Data-driven science Epistemology Foundationalism Philosophy of science ab: The modern abundance and prominence of data have led to the development of “data science” as a new field of enquiry, along with a body of epistemological reflections upon its foundations, methods, and consequences. This article provides a systematic analysis and critical review of significant open problems and debates in the epistemology of data science. We propose a partition of the epistemology of data science into the following five domains: (i) the constitution of data science; (ii) the kind of enquiry that it identifies; (iii) the kinds of knowledge that data science generates; (iv) the nature and epistemological significance of “black box” problems; and (v) the relationship between data science and the philosophy of science more generally. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Synthese is a copyright of Springer, 2022. All Rights Reserved. item: Synthese holder: Springer Nature dt: @attributes: year: 2022 holdings: @attributes: islocal: N |
|---|