Details
| Original language | English |
|---|---|
| Article number | 463 |
| Journal | SYNTHESE |
| Volume | 200 |
| Issue number | 6 |
| Early online date | 3 Nov 2022 |
| Publication status | Published - Dec 2022 |
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.
Keywords
- Agent-centred view, AI, AlphaFold, Collective-centred view, Scientific discovery
ASJC Scopus subject areas
- Arts and Humanities(all)
- Philosophy
- Social Sciences(all)
- General Social Sciences
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In: SYNTHESE, Vol. 200, No. 6, 463, 12.2022.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Decentring the discoverer
T2 - how AI helps us rethink scientific discovery
AU - Clark, Elinor
AU - Khosrowi Djen-Gheschlaghi, Donal
N1 - Funding Information: Open Access funding enabled and organized by Projekt DEAL. This study was funded by Deutscher Akademischer Austauschdienst (Grant No. 91814091).
PY - 2022/12
Y1 - 2022/12
N2 - 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.
AB - 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.
KW - Agent-centred view
KW - AI
KW - AlphaFold
KW - Collective-centred view
KW - Scientific discovery
UR - http://www.scopus.com/inward/record.url?scp=85141190469&partnerID=8YFLogxK
U2 - 10.1007/s11229-022-03902-9
DO - 10.1007/s11229-022-03902-9
M3 - Article
AN - SCOPUS:85141190469
VL - 200
JO - SYNTHESE
JF - SYNTHESE
SN - 0039-7857
IS - 6
M1 - 463
ER -