2021
DOI: 10.1145/3479010
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Archives and AI: An Overview of Current Debates and Future Perspectives

Abstract: The digital transformation is turning archives, both old and new, into data. As a consequence, automation in the form of artificial intelligence techniques is increasingly applied both to scale traditional recordkeeping activities, and to experiment with novel ways to capture, organise, and access records. We survey recent developments at the intersection of Artificial Intelligence and archival thinking and practice. Our overview of this growing body of literature is organised through the lenses of the Records… Show more

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Cited by 55 publications
(25 citation statements)
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“…Chabin (2020) uses case study to highlight a point also found by Bunn (2020) and Colavizza et al. (2022) – that other archival and recordkeeping principles may be of use to the AI field, specifically authenticity.…”
Section: Literature Reviewmentioning
confidence: 98%
See 3 more Smart Citations
“…Chabin (2020) uses case study to highlight a point also found by Bunn (2020) and Colavizza et al. (2022) – that other archival and recordkeeping principles may be of use to the AI field, specifically authenticity.…”
Section: Literature Reviewmentioning
confidence: 98%
“…Other scholars have also highlighted the colonialist overtones of provenance and original order, explaining that they can conflict with diversity and inclusion goals (Punzalan and Caswell, 2016;Steinmeier, 2020). Chabin (2020) uses case study to highlight a point also found by Bunn (2020) and Colavizza (2022)-that other archival and recordkeeping principles may be of use to the AI field, specifically authenticity. Chabin (2019) uses the case of the data processing associated with the great debate in France to explain how diplomatic analysis can be used to enrich a dataset that is used in ML or CV.…”
Section: Social and Ethical Concernsmentioning
confidence: 99%
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“…Ci vuole magari l'accortezza di non lasciarsi travolgere dal tecnicamente possibile, per evitare che le fascinazioni digitali spacchino in due la realtà, ma detto questo è chiaro che le filosofie alla base del machine learning hanno ormai un loro senso profondo in questo contesto e le reti neuronali dei computer non sembrano più così disumane. Machine learning e deep learning non sono fantascienza ma pratica quotidiana e le intelligenze artificiali ci chiedono a gran voce di essere utilizzate (Colavizza et al 2021).…”
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