AI in Archival Science -- A Systematic Review

• URL: http://arxiv.org/abs/2410.09086v1
• Date: Mon, 7 Oct 2024 14:39:12 GMT
• Title: AI in Archival Science -- A Systematic Review
• Authors: Gaurav Shinde, Tiana Kirstein, Souvick Ghosh, Patricia C. Franks,
• Abstract summary: This study underscores the benefits of integrating artificial intelligence (AI) within the broad realm of archival science. Our findings highlight key AI driven strategies that promise to streamline record-keeping processes and enhance data retrieval efficiency.
• Score: 0.9749638953163389
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The rapid expansion of records creates significant challenges in management, including retention and disposition, appraisal, and organization. Our study underscores the benefits of integrating artificial intelligence (AI) within the broad realm of archival science. In this work, we start by performing a thorough analysis to understand the current use of AI in this area and identify the techniques employed to address challenges. Subsequently, we document the results of our review according to specific criteria. Our findings highlight key AI driven strategies that promise to streamline record-keeping processes and enhance data retrieval efficiency. We also demonstrate our review process to ensure transparency regarding our methodology. Furthermore, this review not only outlines the current state of AI in archival science and records management but also lays the groundwork for integrating new techniques to transform archival practices. Our research emphasizes the necessity for enhanced collaboration between the disciplines of artificial intelligence and archival science.

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