Machine learning, misinformation, and citizen science

Adrian K. YEE*

*Corresponding author for this work

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

1 Citation (Scopus)

Abstract

Current methods of operationalizing concepts of misinformation in machine learning are often problematic given idiosyncrasies in their success conditions compared to other models employed in the natural and social sciences. The intrinsic value-ladenness of misinformation and the dynamic relationship between citizens’ and social scientists’ concepts of misinformation jointly suggest that both the construct legitimacy and the construct validity of these models needs to be assessed via more democratic criteria than has previously been recognized.
Original languageEnglish
Article number56
Number of pages24
JournalEuropean Journal for Philosophy of Science
Volume13
Issue number4
Early online date22 Nov 2023
DOIs
Publication statusPublished - Dec 2023

Bibliographical note

Publisher Copyright:
© 2023, Springer Nature B.V.

Keywords

  • Citizen science
  • Construct validity
  • Machine learning
  • Measurement
  • Misinformation
  • Social Epistemology

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