Artificial Intelligence and Machine Learning at the Intersection of Privacy and Archives

As records are increasingly born digital – and thus, at least ostensibly, potentially much more accessible – archivists find themselves struggling to enable general access while providing appropriate privacy protections for the torrent of records being transferred to their care. In this article, the authors report the results of an integrative literature review study, examining the intersection of AI, archives, and privacy in terms of how archives are currently coping with these challenges and what role(s) AI might play in addressing privacy in archival records. The study revealed three major themes: 1) the challenges of – and possibilities beyond – defining “privacy” and “AI”; 2) the need for context-sensitive ways to manage privacy and access decisions; and 3) the lack of adequate “success measures” for ensuring the actual fitness for purpose of privacy AI solutions in the archival context.

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Publication Details

Journal
Archeion
Published
2024-12-03
DOI
https://doi.org/10.4467/26581264arc.24.006.20201
Citations
1
Primary Topic
Privacy-Preserving Technologies in Data
Type
article
Field-Weighted Citation Impact
0.35

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article

Artificial Intelligence and Machine Learning at the Intersection of Privacy and Archives

Darra Hofman, Jim Suderman, Iori Khuhro, Erin Gilmore
1 citations
Archeion
Privacy-Preserving Technologies in Data
0.35
article

Artificial Intelligence and Machine Learning at the Intersection of Privacy and Archives

Darra Hofman, Jim Suderman, Iori Khuhro, Erin Gilmore
article en
1 citations

Abstract

As records are increasingly born digital – and thus, at least ostensibly, potentially much more accessible – archivists find themselves struggling to enable general access while providing appropriate privacy protections for the torrent of records being transferred to their care. In this article, the authors report the results of an integrative literature review study, examining the intersection of AI, archives, and privacy in terms of how archives are currently coping with these challenges and what role(s) AI might play in addressing privacy in archival records. The study revealed three major themes: 1) the challenges of – and possibilities beyond – defining “privacy” and “AI”; 2) the need for context-sensitive ways to manage privacy and access decisions; and 3) the lack of adequate “success measures” for ensuring the actual fitness for purpose of privacy AI solutions in the archival context.

ArcheionVol. 125
University of British Columbia (CA), San Jose State University (US)
Social Sciences and Humanities Research Council of Canada
Peace, Justice and strong institutions
Openalex Percentile: Top 31%
Privacy-Preserving Technologies in Data
0.35
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