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Are users of digital archives ready for the AI era? Obstacles to the application of computational research methods and new opportunities

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journal contribution
posted on 2024-01-26, 15:45 authored by Lise JaillantLise Jaillant, Katherine Aske
Innovative technologies are improving the accessibility, preservation and searchability of born-digital and digitised records. In particular, Artificial Intelligence (AI) is opening new opportunities for archivists and researchers. However, the experience of scholars (particularly humanities scholars) and other users remain understudied. This article asks how and why researchers and general users are, or are not, using computational methods. This research is informed by an open-call survey, completed by 22 individuals, and semi-structured interviews with 33 professionals, including archivists, librarians, digital humanists, literary scholars, historians, and computer scientists. Drawing on these results, this article offers an analysis of user experiences of computational research methods applied to digitised and born-digital archives. With a focus on humanities and social science researchers, this article also discusses users who resist this kind of research, perhaps because they lack the skills necessary to engage with these materials at scale, or because they prefer to use more traditional methods, such as close reading and historical analysis. Here, we explore the uses of computational and more ‘traditional’ research methodologies applied to digital records. We also make a series of recommendations to elevate users’ computational skills but also to improve the digital infrastructure to make archives more accessible and usable.

Funding

AEOLIAN (Artificial intelligence for cultural organisations)

UK Research and Innovation

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History

School

  • Social Sciences and Humanities

Department

  • Communication and Media

Published in

ACM Journal on Computing and Cultural Heritage

Volume

16

Issue

4

Publisher

Association for Computing Machinery

Version

  • VoR (Version of Record)

Rights holder

© The owner/author(s).

Publisher statement

This is an Open Access article under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0).

Acceptance date

2023-07-15

Publication date

2024-01-24

Copyright date

2024

ISSN

1556-4673

Language

  • en

Depositor

Dr Lise Jaillant. Deposit date: 17 July 2023

Article number

87

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