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The Fictional Archetypes of AI: For a Qualitative-Quantitative Analysis of Representations in Films

Author

Listed:
  • Mickael Peiro

    (IUT Paul Sabatier - Institut Universitaire de Technologie - Paul Sabatier - UT3 - Université Toulouse III - Paul Sabatier - UT - Université de Toulouse)

  • Pierre Loup

    (IUT Montpellier – Sète - Institut Universitaire de Technologie - Montpellier - UM - Université de Montpellier)

  • Jeremy Aroles

    (University of York [York, UK])

Abstract

MOS research on films has tended to focus on individual cases or series. In this article, we are proposing an approach that mobilizes background analysis, computational text analysis, and hermeneutics in order to provide a systematic, critically inclined analysis of a large corpus. We illustrate this approach by exploring the political and symbolical representations of artificial intelligence (AI) in the film industry. Using the Internet Movie Database, we identified all the films dealing with AI (113 in total), compiled their synopses, and recorded 11 characteristics for each. Highlighting the spatial, temporal, and gendered polarization of films depicting AI, our article proposes four representations of AI and critically reflects upon the role of these representations and their influence in shaping societal perceptions of AI. Our article makes two main contributions to the literature. First, it demonstrates the potential of combining quantitative-based, lexical forms of analysis with hermeneutic interpretations in the study of cultural representations. Second, it develops a nuanced, in-depth, and critical analysis of the symbolical and political representations of AI in cinematic productions, thus enhancing our understanding of this industry.

Suggested Citation

  • Mickael Peiro & Pierre Loup & Jeremy Aroles, 2024. "The Fictional Archetypes of AI: For a Qualitative-Quantitative Analysis of Representations in Films," Post-Print hal-04801279, HAL.
  • Handle: RePEc:hal:journl:hal-04801279
    DOI: 10.37725/mgmt.2024.9763
    as

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