Evidence, computation and AI : why evidence is not just in the head

Darrell P. ROWBOTTOM*, André CURTIS-TRUDEL, William PEDEN

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review

1 Citation (Scopus)

Abstract

Can scientific evidence outstretch what scientists have mentally entertained, or could ever entertain? This article focuses on the plausibility and consequences of an affirmative answer in a special case. Specifically, it discusses how we may treat automated scientific data-gathering systems - especially AI systems used to make predictions or to generate novel theories - from the point of view of confirmation theory. It uses AlphaFold2 as a case study.
Original languageEnglish
Article number11
Number of pages17
JournalAsian Journal of Philosophy
Volume2
Issue number1
Early online date4 Apr 2023
DOIs
Publication statusPublished - Jun 2023

Bibliographical note

Publisher Copyright:
© 2023, The Author(s), under exclusive licence to Springer Nature B.V.

Funding

The work described in this paper was fully supported by a Senior Research Fellowship award from the Research Grants Council of the Hong Kong SAR, China (‘Philosophy of Contemporary and Future Science’, Project no. SRFS2122-3H01).

Keywords

  • AlphaFold2
  • Artificial intelligence
  • Confirmation
  • Deep neural networks
  • Evidence
  • Machine learning

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