Engineering social concepts: Feasibility and causal models.

How feasible are conceptual engineering projects of social concepts that aim for the engineered concept to be deployed in people's ordinary conceptual practices? Predominant frameworks on the psychology of concepts that shape work on stereotyping, bias, and machine learning have grim implications fo...

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Publicado en:Philosophy & Phenomenological Research Vol. 109; no. 3; pp. 819 - 838
Autor principal: Neufeld, Eleonore
Formato: Artículo
Publicado: Wiley-Blackwell Nov2024
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Engineering social concepts: Feasibility and causal models.
      aug:
        au: Neufeld, Eleonore
        affil: Department of Philosophy, University of Massachusetts Amherst
      su:
        Social psychology
        Causal models
        Stereotypes
        Machine learning
        Engineers
      sug:
        subj:
          Social psychology
          Causal models
          Stereotypes
          Machine learning
          Engineers
      ab: How feasible are conceptual engineering projects of social concepts that aim for the engineered concept to be deployed in people's ordinary conceptual practices? Predominant frameworks on the psychology of concepts that shape work on stereotyping, bias, and machine learning have grim implications for the prospects of conceptual engineers: conceptual engineering efforts are ineffective in promoting certain social‐conceptual changes. Since conceptual components that give rise to problematic social stereotypes are sensitive to statistical structures of the environment, purely conceptual change won't be possible without corresponding world change. This tradition, however, tends to ignore that concepts don't only encode statistical, but also causal information. Paying attention to this feature of concepts, I argue, shows that conceptual engineering is not only possible. There is an imperative to conceptually‐engineer.
      pubtype: Academic Journal
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    language: English
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