Introducing a four-fold way to conceptualize artificial agency.

Recent developments in AI-research suggest that an AI-driven science might not be that far off. The research of for Melnikov et al. (2018) and that of Evans et al. (2018) show that automated systems can already have a distinctive role in the design of experiments and in directing future research. Co...

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Publicado en:Synthese Vol. 201; no. 3; pp. 1 - 29
Autor principal: van Lier, Maud
Formato: Artículo
Publicado: Springer Nature Mar2023
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Introducing a four-fold way to conceptualize artificial agency.
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        au: van Lier, Maud
        affil: Department of Philosophy, University of Konstanz, Universitätsstraße 10, 78464, Konstanz, Baden-Württemberg, Germany
      sug:
      keyword:
        AI-driven science
        Artificial agency
        Basic research
        Intentional agency
        Modeling
      ab: Recent developments in AI-research suggest that an AI-driven science might not be that far off. The research of for Melnikov et al. (2018) and that of Evans et al. (2018) show that automated systems can already have a distinctive role in the design of experiments and in directing future research. Common practice in many of the papers devoted to the automation of basic research is to refer to these automated systems as ‘agents’. What is this attribution of agency based on and to what extent is this an important notion in the broader context of an AI-driven science? In an attempt to answer these questions, this paper proposes a new methodological framework, introduced as the Four-Fold Framework, that can be used to conceptualize artificial agency in basic research. It consists of four modeling strategies, three of which were already identified and used by Sarkia (2021) to conceptualize ‘intentional agency’. The novelty of the framework is the inclusion of a fourth strategy, introduced as conceptual modeling, that adds a semantic dimension to the overall conceptualization. The strategy connects to the other strategies by modeling both the actual use of ‘artificial agency’ in basic research as well as what is meant by it in each of the other three strategies. This enables researchers to bridge the gap between theory and practice by comparing the meaning of artificial agency in both an academic as well as in a practical context.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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