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Artificial Intelligence and Machine Learning Competencies for the Archival Professions Arias-Hernandez, Richard; Fewster, Kaila; Penniman, Sophie

Abstract

This article presents qualitative research aimed at deriving key competencies for archival students and professionals to leverage Artificial Intelligence (AI) and Machine Learning (ML) to support the ongoing availability and accessibility of trustworthy public records. This research project was conducted under InterPARES iTrust AI. Methodology and findings are presented. Our primary source of data are interviews conducted between January and July 2023 with 10 archivists, record managers, and digital archives researchers from the UK, Canada, USA, Australia, and New Zealand. All our interviewees had practical experience applying AI and Machine Learning to the processing of records in archives or record management offices.

Item Metadata

Title
Artificial Intelligence and Machine Learning Competencies for the Archival Professions
Creator
Arias-Hernandez, Richard; Fewster, Kaila; Penniman, Sophie
Date Issued
2024
Description
This article presents qualitative research aimed at deriving key competencies for archival students and professionals to leverage Artificial Intelligence (AI) and Machine Learning (ML) to support the ongoing availability and accessibility of trustworthy public records. This research project was conducted under InterPARES iTrust AI. Methodology and findings are presented. Our primary source of data are interviews conducted between January and July 2023 with 10 archivists, record managers, and digital archives researchers from the UK, Canada, USA, Australia, and New Zealand. All our interviewees had practical experience applying AI and Machine Learning to the processing of records in archives or record management offices.
Subject
Professional competencies; Archival processing of records
Genre
Conference Paper; Preprint
Type
Text
Language
eng
Date Available
2024-07-24
Provider
Vancouver : University of British Columbia Library
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International
DOI
10.14288/1.0444806
URI
http://hdl.handle.net/2429/88680
Affiliation
Arts, Faculty of; Other UBC; Information, School of
Citation
Arias-Hernandez, R., Fewster, K., & Penniman, S. (2024). Reimagining library and information science evaluation frameworks for relational knowledge-exchange work. Proceedings of the Annual Meeting of the Association for Information Science and Technology (ASIS&T), October 25-29, 2024. Calgary, AB.
Peer Review Status
Unreviewed
Scholarly Level
Faculty; Graduate
Rights URI
http://creativecommons.org/licenses/by-nc-nd/4.0/
Aggregated Source Repository
DSpace

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Attribution-NonCommercial-NoDerivatives 4.0 International