Elinor Bell-Clark elinor.s.clark@durham.ac.uk
PGR Student Doctor of Philosophy
Decentring the discoverer: how AI helps us rethink scientific discovery
Clark, Elinor; Khosrowi, Donal
Authors
Donal Khosrowi
Abstract
This paper investigates how intuitions about scientific discovery using artificial intelligence (AI) can be used to improve our understanding of scientific discovery more generally. Traditional accounts of discovery have been agent-centred: they place emphasis on identifying a specific agent who is responsible for conducting all, or at least the important part, of a discovery process. We argue that these accounts experience difficulties capturing scientific discovery involving AI and that similar issues arise for human discovery. We propose an alternative, collective-centred view as superior for understanding discovery, with and without AI. This view maintains that discovery is performed by a collective of agents and entities, each making contributions that differ in significance and character, and that attributing credit for discovery depends on various finer-grained properties of the contributions made. Detailing its conceptual resources, we argue that this view is considerably more compelling than its agent-centred alternative. Considering and responding to several theoretical and practical challenges, we point to concrete avenues for further developing the view we propose.
Citation
Clark, E., & Khosrowi, D. (2022). Decentring the discoverer: how AI helps us rethink scientific discovery. Synthese, 200(6), Article 463. https://doi.org/10.1007/s11229-022-03902-9
Journal Article Type | Article |
---|---|
Acceptance Date | Sep 22, 2022 |
Online Publication Date | Nov 3, 2022 |
Publication Date | Nov 3, 2022 |
Deposit Date | Sep 9, 2024 |
Journal | Synthese |
Print ISSN | 0039-7857 |
Electronic ISSN | 1573-0964 |
Publisher | Springer |
Peer Reviewed | Peer Reviewed |
Volume | 200 |
Issue | 6 |
Article Number | 463 |
DOI | https://doi.org/10.1007/s11229-022-03902-9 |
Public URL | https://durham-repository.worktribe.com/output/2851263 |
Additional Information | This article is Open Access at: https://doi.org/10.1007/s11229-022-03902-9 |
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