Machine Learning, Misinformation, and Citizen Science

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

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Adrian K. Yee
Lingnan University

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