Interdisciplinary Framework for AI-Powered Restoration Storytelling

This paper introduces a multi-layered interdisciplinary framework for AI-powered restoration storytelling and its sets the groundwork for the AI4Re-story tool, that will be developed by HighESt Lab (University of Turin) in collaboration with CCR - La Veneria Reale and with the financial support of Fondazione CRT. This paper explores how Artificial Intelligence (AI) can be integrated into an interdisciplinary framework to create cultural value from restoration data, specifically focusing on how to communicate the often-overlooked material history of artworks. While museum communication typically emphasizes artists, subjects, and contexts, the material aspects of artworks, including their restoration and conservation, are often neglected. These aspects, however, hold valuable insights that can tell rich, untold stories about an artwork’s life. Communicating these stories to the general public is challenging, as conservation and restoration knowledge is highly specialized, making it inaccessible to most visitors. The effectiveness of the interdisciplinary framework for AI-powered restoration storytelling depends on the active involvement and collaboration of a wide range of stakeholders across cultural, technical, and educational domains. The paper begins by situating this challenge within the broader context of digital transformation in the cultural heritage sector, considering both the potential and difficulties of storytelling in conservation. It then examines existing frameworks for digital and AI-data storytelling, before introducing an interdisciplinary framework for AI-powered restoration storytelling. The AI4Restory project aims to provide a tool that helps curators, restorers, and art historians communicate their work more effectively to different audience segments. This framework aligns with broader societal and technological shifts, addressing the evolving needs of cultural institutions, policymakers, and audiences.