Tarek R. Besold
Normative and Descriptive Rationality: From Nature to Artifice and Back
Besold, Tarek R.; Uckelman, Sara L.
Abstract
Rationality plays a key role in both the study of human reasoning and Artificial Intelligence (AI). Certain notions of rationality have been adopted in AI as guides for the development of intelligent machines and these notions have been given a normative function. The notions of rationality in AI are often taken to be closely related to conceptions of rationality in human contexts. In this paper, we argue that the normative role of rationality differs in the human and artificial contexts. While rationality in human-focused fields of study is normative, prescribing how humans ought to reason, the normative conception in AI is built on a notion of human rationality which is descriptive, not normative, in the human context, as AI aims at building agents which reason as humans do. In order to make this point, we review prominent notions of rationality used in psychology, cognitive science, and (the history of) philosophy, as well as in AI, and discuss some factors that contributed to rationality being assigned the differing normative statuses in the differing fields of study. We argue that while ‘rationality’ is a normative notion in both AI and in human reasoning, the normativity of the AI conception of ‘rationality’ is grounded in a descriptive account of human rationality.
Citation
Besold, T. R., & Uckelman, S. L. (2018). Normative and Descriptive Rationality: From Nature to Artifice and Back. Journal of Experimental and Theoretical Artificial Intelligence, 30(2), 331-344. https://doi.org/10.1080/0952813x.2018.1430860
Journal Article Type | Article |
---|---|
Acceptance Date | Dec 23, 2017 |
Online Publication Date | Feb 7, 2018 |
Publication Date | Mar 4, 2018 |
Deposit Date | Jan 10, 2018 |
Publicly Available Date | Feb 7, 2019 |
Journal | Journal of Experimental and Theoretical Artificial Intelligence |
Print ISSN | 0952-813X |
Electronic ISSN | 1362-3079 |
Publisher | Taylor and Francis Group |
Peer Reviewed | Peer Reviewed |
Volume | 30 |
Issue | 2 |
Pages | 331-344 |
DOI | https://doi.org/10.1080/0952813x.2018.1430860 |
Public URL | https://durham-repository.worktribe.com/output/1368762 |
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Copyright Statement
This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Experimental & Theoretical Artificial Intelligence on 07 Feb 2018, available online: http://www.tandfonline.com/10.1080/0952813x.2018.1430860.
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