AI-assisted predictive appraisal and preservation prioritisation in television audiovisual archives: a theoretical framework integrating human oversight
DOI:
https://doi.org/10.47989/ir31363394Keywords:
Predictive preservation, Artificial intelligence, Audiovisual archives, Television heritageAbstract
Introduction. The article addresses the challenge of examining the possible future archival significance of televised audiovisual documents in television archives. It introduces Artificial Intelligence (AI)-assisted predictive appraisal and preservation prioritisation to support archival decision-making in contexts of audiovisual overproduction and future-oriented archival judgment, responding to resource, storage, and preservation constraints.
Method. The study develops a theoretical and conceptual model integrating AI into archival appraisal processes. It draws on a critical review of specialised literature in archival science, heritage preservation, and computational cultural analysis, with particular attention to content features, contextual information, and production metadata. This is a critical conceptual literature review rather than an empirical validation.
Analysis. The analysis identifies patterns relevant to prospective archival appraisal and examines how predictive analytics can be aligned with established archival principles. It also examines the epistemological and ethical implications of algorithm-supported appraisal, including questions of bias, legitimacy, and responsibility.
Conclusions. The article proposes a conceptual framework combining AI-assisted predictive appraisal with well-founded archival criteria. It positions predictive analytics as a complementary tool for optimising curation, prioritising resources, and supporting more strategic and sustainable archive management. Its contribution is conceptual rather than demonstrative and remains dependent on human oversight, archival interpretation, and documented accountability.
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