AI and Swedish Heritage Organisations: challenges and opportunities

Gabriele Griffin · Elisabeth Wennerström · Anna Foka

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Digital and Traditional Archives Management Digital Humanities and Scholarship Artificial Intelligence Applications

Abstract

Abstract This article examines the challenges and opportunities that arise with artificial intelligence (AI) and machine learning (ML) methods and tools when implemented within cultural heritage institutions (CHIs), focusing on three selected Swedish case studies. The article centres on the perspectives of the CHI professionals who deliver that implementation. Its purpose is to elucidate how CHI professionals respond to the opportunities and challenges AI/ML provides. The three Swedish CHIs discussed here represent different organizational frameworks and have different types of collections, while sharing, to some extent, a similar position in terms of the use of AI/ML tools and methodologies. The overarching question of this article is what is the state of knowledge about AI/ML among Swedish CHI professionals, and what are the related issues? To answer this question, we draw on (1) semi-structured interviews with CHI professionals, (2) individual CHI website information, and (3) CHI-internal digitization protocols and digitalization strategies, to provide a nuanced analysis of both professional and organisational processes concerning the implementation of AI/ML methods and tools. Our study indicates that AI/ML implementation is in many ways at the very early stages of implementation in Swedish CHIs. The CHI professionals are affected in their AI/ML engagement by four key issues that emerged in the interviews: their institutional and professional knowledge regarding AI/ML; the specificities of their collections and associated digitization and digitalization issues; issues around personnel; and issues around AI/ML resources. The article suggests that a national CHI strategy for AI/ML might be helpful as would be knowledge-, expertise-, and potentially personnel- and resource-sharing to move beyond the constraints that the CHIs face in implementing AI/ML.

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2006Using thematic analysis in psychology 2005Reassembling the Social 2020One size fits all? What counts as quality practice in (reflexive) thematic analysis?1994We have never been modern 2020Can I use TA? Should I use TA? Should I not use TA? Comparing reflexive thematic analysis and other pattern‐based qualitative analytic approaches 2004After Method 2010A definition of cultural heritage: From the tangible to the intangible 2018How Does the Digital Transformation Affect Organizations? Key Themes of Change in Work Design and Leadership

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2024AI, Cultural Heritage, and Bias: Some Key Queries That Arise from the Use of GenAI 2024Generative Artificial Intelligence, Human Agency and the Future of Cultural Heritage 2024Will Artificial Intelligence Affect How Cultural Heritage Will Be Managed in the Future? Responses Generated by Four genAI Models 2025Tracing the bias loop: AI, cultural heritage and bias-mitigating in practice 2025AI-driven experiences in cultural and creative industries: a review of literature and development of a multifaceted framework

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