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Open Heritage in the Age of Artificial Intelligence

Cultural heritage institutions (CHIs) such as museums, libraries, and archives, carry the important public-interest mission of providing access to the heritage in their collections. Their mission is grounded in broad public access and…

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Aug 19, 2026 at 6:30 PM UTC · 5 min de leitura

Open Heritage in the Age of Artificial Intelligence
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The Prodigious Value of Sharing Heritage

Cultural heritage institutions (CHIs) such as museums, libraries, and archives, carry the important public-interest mission of providing access to the heritage in their collections. Their mission is grounded in broad public access and extensive human engagement, the existence of a vibrant cultural commons, and heritage enjoyed as a shared resource. CHIs understand that, as a representation of who we are, heritage helps define our shared humanity and that providing access to heritage generates numerous benefits for society. As such, CHIs, as stewards of trustworthy information imbued within knowledge and culture, have a crucial role to play in growing and protecting the commons and enabling uses that benefit humanity. 

AI—the Major Disruptor 

The recent emergence of generative artificial intelligence (AI) has had a phenomenal impact on CHIs, especially as the content they steward is accessed and used for AI development. One key question centers on the conditions, norms, and expectations governing the use of openly licensed and public domain cultural heritage materials as data for AI development. Examples include the open datasets available at AI4Culture, Hugging Face’s BigLAM, Harvard’s Institutional Books, Authors’ Alliance The Public Interest Corpus, as well as, potentially in the future, the European Books Data Commons. This is prompting discussions around who can access and reuse those data, and for what purpose. Heritage collections often yield—by virtue of the stewardship duties that underpin them—diverse, high-quality, contextualized, and well-curated datasets. While inclusion of heritage collections data could expectedly yield better, more representative AI systems, CHIs face many challenges, including: 

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