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Generative AI in Heritage Practice

Improving the Accessibility of Heritage Guidance

Bibliographic Data

ID13124695
AuthorsJessica Witte (0000-0003-1144-8065, University of Edinburgh, corresponding author), Edmund Lee (0000-0002-1166-0878, Historic England), Lisa Brausem (Historic England), Verity Shillabeer (Historic England), Chiara Bonacchi (0000-0002-0872-0614, University of Edinburgh)
Year2025
Volume8
Issue12
Pages513-513
Publication date2025-12-06
Open AccessYes
TypeARTICLE
VenueHeritage (JOURNAL)
Journal identifiersISSN: 2571-9408 • E-ISSN: 2571-9408
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/heritage8120513
OpenAlexW4417114490
LanguageEN
Citations received2
References cited96

This paper discusses the potential for integrating Generative Artificial Intelligence (GenAI) into professional heritage practice with the aim of enhancing the accessibility of public-facing guidance documents. We developed HAZEL, a GenAI chatbot fine-tuned to assist with revising written guidance relating to heritage conservation and interpretation. Using quantitative assessments, we compare HAZEL’s performance to that of ChatGPT (GPT-4) in a series of tasks related to the guidance writing process. The results of this comparison indicate a slightly better performance of HAZEL over ChatGPT, suggesting that the GenAI chatbot is more effective once the underlying large language model (LLM) has been fine-tuned. However, we also note significant limitations, particularly in areas requiring cultural sensitivity and more advanced technical expertise. These findings suggest that, while GenAI cannot replace human heritage professionals in technical authoring tasks, its potential to automate and expedite certain aspects of guidance writing could offer valuable benefits to heritage organisations, especially in resource-constrained contexts

Chatbot · Cultural heritage · Generative grammar · Generative model · Relation (database · AI in Service Interactions · Artificial Intelligence in Healthcare and Education · Spreadsheets and End-User Computing

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Citations per year2
Citation span2026 - 2026 (1)
Highly citedNo

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