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Museums and Archives in the Age of Artificial Intelligence and Post-representation

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Sight as Site in the Digital Age

Part of the book series: Digital Culture and Humanities ((DICUHU,volume 5))

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Abstract

Analog archives and collections management practices used by museums in their traditional forms are currently being replaced by digital technologies. These technologies redefine the relationship between the collection and the archive as well as the ways in which concepts such as representation, interpretation, truth, and objectivity are perceived within the museum context. As a result, the museum archive is being considered not only as a storage space but as a knowledge generator and as an arena of cultural discourse and interpretive space for the content it preserves. Based on contemporary archival theories, this study argues that the changes in archival practices presented by digital platforms impact curatorial conceptions in museums as the museum archive becomes a potential space for curatorial practices. It further claims that the new archival practices have the potential not only to change how knowledge is represented, stored, and retrieved but also to generate a self-reflexive examination of the way in which meanings are being created in the museum. Special attention will be given to exploring how AI (artificial intelligence) applications influence the ways in which knowledge is documented and organised in the museum’s archives: It addresses the methods by which AI applications take place in the digitisation processes of museum collections, imposing “machine intelligence” on cultural analyses. In addition, it will refer to potential future implications of AI on curatorial practices and on the visitor’s experience and refer to the societal and political consequences of the use of AI-driven self-customisation practices.

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Notes

  1. 1.

    See the approved definition at: “ICOM Approves a New Museum Definition.” ICOM, 24 August 2022. Accessed 9 September 2022. https://icom.museum/en/news/icom-announces-the-alternative-museum-definition-that-will-be-subject-to-a-vote/.

  2. 2.

    Foster refers to art museums, but his analyses can be implemented on other types of museum as well.

  3. 3.

    This can be compared to Thibodeau’s analysis of digital images which possess three levels—the physical the logical and the conceptual—and can be significantly different at each of them (Thibodeau, 2002, p. 6).

  4. 4.

    However, despite the great contribution of such models to the streamlining of collections, their use did not always suit museums whose collections did not conceptually require taxonomic divisions as in the natural sciences. Applying these methodologies did not suit the needs of these museums and did, in some cases, create some disruptions for the curators.

  5. 5.

    In Europe, which has invested extensive resources in digitising its collection, only 43.6% of their collections are digitised (Final report, 2020).

  6. 6.

    In my discussion of the digital object I will refer to the additional meanings that an object can acquire while being transformed into digital form.

  7. 7.

    As you can see, for example, in Gallery One in Cleveland and Kunsthalle Mannheim in which the digital archives are part of the display and function as potential curatorial space for the visitors.

  8. 8.

    An example of an archive on display that contains documents which have never been exhibited in the exhibition halls is the Churchill War Room Timeline at the Imperial War Museum in London.

  9. 9.

    The records continuum model was developed at Monash University already in the 1990s.

  10. 10.

    Soares, Bruno Brulon and Kerstin Smeds (2016). “Museology exploring the concept of MLA (Museums-Libraries-Archives) and probing its interdisciplinarity.” 44, pp. 29–33. Museology exploring the concept of MLA (Museums-Libraries-Archives). https://journals.openedition.org/iss/654.

  11. 11.

    The Art Explorer, The Cleveland Museum of Art, Microsoft Corporation. https://www.clevelandart.org/microsoft-corporation.

  12. 12.

    This is a research project based at the German Ludwig Forum for International Art Aachen and the Hartware MedienKunstVerein (HMKV) in Dortmund, Germany. https://github.com/DominikBoenisch/Training-the-Archive.

  13. 13.

    See the project’s website: “Dust and Data: The Art of Curating in the Age of Artificial Intelligence,” Dust and Data Exhibition at Volkskundemuseum announced March 12, 2021. http://www.dustanddata.at/author/abkadmin.

  14. 14.

    See, for example: Art Selfie project as part of Google Art & Culture project. https://artsandculture.google.com/camera/selfie.

  15. 15.

    See, for example: Recognition, winner of IK Prize 2016 for digital innovation, which is an artificial intelligence program that compares up-to-the-minute photojournalism with British art from the Tate collection. https://www.tate.org.uk/whats-on/tate-britain/exhibition/ik-prize-2016-recognition.

  16. 16.

    This issue has been discussed in a large number of conferences and lectures held during the corona period in relation to the transformation that museums have undergone as a result of their closure during the lockdown periods. See, for example, ICOM Europe Seminar 30 March 2021, https://www.youtube.com/watch?v=wsHUyTnB1Gk.

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Van Essen, Y.E. (2023). Museums and Archives in the Age of Artificial Intelligence and Post-representation. In: Tam, Kk. (eds) Sight as Site in the Digital Age . Digital Culture and Humanities, vol 5. Springer, Singapore. https://doi.org/10.1007/978-981-19-9209-4_5

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  • DOI: https://doi.org/10.1007/978-981-19-9209-4_5

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-9208-7

  • Online ISBN: 978-981-19-9209-4

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