{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T17:53:55Z","timestamp":1767635635290,"version":"3.48.0"},"reference-count":37,"publisher":"Emerald","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,8,14]]},"abstract":"<jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>The increased use of Artificial Intelligence (AI) has prompted governments internationally to provide guidance and legislation to maximize the benefits of AI while minimizing the risks to humans and organizations. This paper explores how published requirements for documentation in a sampling of authoritative texts address the challenges of creating, capturing and preserving records of the design, implementation and use of AI tools for accountability and transparency, and how the analytical concept of paradata can help to meet the recordkeeping challenges presented by the design, development and implementation of AI systems.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Design\/methodology\/approach<\/jats:title>\n                    <jats:p>Inductive reading and conceptual analysis of a set of AI laws, regulations and frameworks published by the EU, UK, USA, Canada and Singapore.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Findings<\/jats:title>\n                    <jats:p>The authoritative texts reviewed clearly describe activities which imply the necessity of records creation and preservation. Identifying specific documents necessary to comprise a sufficient body of records to provide evidence of accountable AI implementation and operation can be difficult. Literature on paradata in archival applications of AI may prove productive in identifying relevant information artifacts for preservation in the AI process. Paradata is produced by those designing and implementing AI systems and by AI systems themselves.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Practical implications<\/jats:title>\n                    <jats:p>Identifying relevant paradata produced by AI systems requires archivists to develop both the capacity to analyze and the vocabulary to discuss these systems in order to preserve evidence of their operation in compliance with legislation and international standards.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Originality\/value<\/jats:title>\n                    <jats:p>No comparable comparative analyses have been published in the archives and information field.<\/jats:p>\n                  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