How to Conceptual Engineer 'Entropy' and 'Information'.

In this paper I discuss how to conceptual engineer 'entropy' and 'information' as they are used in information theory and statistical mechanics. Initially, I evaluate the extent to which the all-pervasive entangled use of entropy and information notions can be somehow defective in these domains, suc...

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Publicado en:Erkenntnis Vol. 91; no. 2; pp. 897 - 922
Autor principal: Anta, Javier
Formato: Artículo
Publicado: Springer Nature Feb2026
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        atl: How to Conceptual Engineer 'Entropy' and 'Information'.
      aug:
        au: Anta, Javier
        affil:
          https://ror.org/05591te55 Munich Center for Mathematical Philosophy, Ludwig-Maximilians-Universität München, Ludwigstr. 31, Munich, Germany
          https://ror.org/02msb5n36 Department of Logic, History and Philosophy of Science, UNED, Madrid, Spain
      su:
        Entropy
        Information theory
        Statistical mechanics
        Conceptual design
        Philosophy of science
        Scientific method
        Metadata
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        subj:
          Entropy
          Information theory
          Statistical mechanics
          Conceptual design
          Philosophy of science
          Scientific method
          Metadata
      ab: In this paper I discuss how to conceptual engineer 'entropy' and 'information' as they are used in information theory and statistical mechanics. Initially, I evaluate the extent to which the all-pervasive entangled use of entropy and information notions can be somehow defective in these domains, such as being meaningless or generating confusion. Then, I assess the main ameliorative strategies to improve this defective conceptual practice. The first strategy is to substitute the terms 'entropy' and 'information' by non-loaded terms, as it was first argued by Bar-Hillel in the 1950s. A second strategy is to prescribe how these terms should be correctly used to be meaningful, as it was pioneered by Carnap (Two essays on entropy, University of California Press, 1977) in Two Essays on Entropy. However, the actual implementation of these two ameliorative strategies has been historically unsuccessful due to the low credentials that philosophers as conceptual prescribers have among scientists. Finally, to try to solve these obstacles, I propose a third strategy based on leveraging evidence from the contribution of philosophy as a complementary science or the so-called 'Philosophy in Science' (à la Pradeu et al. in Brit J Philos Sci 75:(2):375–416, 2024) to integrate conceptual prescriptions and analyses of entropy and information as part of the scientific practices in which these notions are used.
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    language: English
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