Machine Learning, Misinformation, and Citizen Science

European Journal for Philosophy of Science 13 (56):1-24 (2023)
  Copy   BIBTEX


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.

Author's Profile

Adrian K. Yee
Lingnan University


Added to PP

255 (#53,412)

6 months
229 (#7,865)

Historical graph of downloads since first upload
This graph includes both downloads from PhilArchive and clicks on external links on PhilPapers.
How can I increase my downloads?