The epistemological foundations of data science: a critical review

Jules Desai; David Watson; Vincent Wang; Mariarosaria Taddeo; Luciano Floridi

doi:10.1007/s11229-022-03933-2

The epistemological foundations of data science: a critical review

Jules Desai, David Watson, Vincent Wang, Mariarosaria Taddeo, Luciano Floridi

Informatics

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7 Citations (Scopus)

Abstract

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.

Original language	English
Article number	469
Journal	SYNTHESE
Volume	200
Issue number	6
Early online date	6 Nov 2022
DOIs	https://doi.org/10.1007/s11229-022-03933-2
Publication status	Published - 8 Nov 2022

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The epistemological foundations of data science: a critical review

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