# Generative AI in Heritage Practice: Improving the Accessibility of Heritage Guidance

arXiv: https://arxiv.org/abs/2510.13811 · HTML: https://mlsanity.com/paper/2510.13811/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 14 of its 156 references that are in the map.
- First posted on arXiv 3 Sep 2025.

## Builds on (most cited first, 14 of 14)

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- [The Pace of Artificial Intelligence Innovations: Speed, Talent, and Trial-and-Error](https://mlsanity.com/paper/2009.01812/) (2020)
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- [The Cognitive Capabilities of Generative AI: A Comparative Analysis with Human Benchmarks](https://mlsanity.com/paper/2410.07391/) (2024)
- [Dissecting Bias of ChatGPT in College Major Recommendations](https://mlsanity.com/paper/2401.11699/) (2023)

## Abstract (arXiv)

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.