Open Heritage Under Threat from AI-Generated Images and Data Analysis Tools

Cultural heritage institutions (CHIs) such as museums, libraries, and archives have a long-standing mission to provide access to the heritage in their collections. This mission is grounded in broad public access and extensive human engagement, with the goal of creating a vibrant cultural commons where heritage can be enjoyed as a shared resource. CHIs understand that providing access to heritage generates numerous benefits for society, including helping define our shared humanity. As stewards of trustworthy information imbued within knowledge and culture, they have a crucial role to play in growing and protecting the commons and enabling uses that benefit humanity.

The recent emergence of generative artificial intelligence (AI) has had a significant impact on CHIs, particularly as their content 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 open datasets available at AI4Culture, Hugging Face’s BigLAM, Harvard’s Institutional Books, Authors’ Alliance The Public Interest Corpus, and potentially in the future, the European Books Data Commons.

This has prompted discussions around who can access and reuse those data, and for what purpose. Heritage collections often yield diverse, high-quality, contextualized, and well-curated datasets that could be used to create more representative AI systems. However, CHIs face many challenges when it comes to sharing their heritage with AI developers. Infrastructure challenges threaten the economic sustainability of open infrastructure and ecosystems, including increased bot traffic by dominant, profit-driven AI companies putting a strain on the infrastructure and increasing knock-on costs.

Commercial AI practices at odds with the values and norms of the commons also pose significant challenges for CHIs. These include lack of transparency and attribution, decontextualization, loss of provenance trail due to opaque AI models and systems, and further enclosures of content into proprietary systems. This points to a conflict between commercial AI developments and CHIs’ commitment to provide open access and commons-based expectations of reciprocity and respect for the social contract underpinning sharing of heritage in the commons.

CHIs are more hesitant than ever to share their collections openly, with some institutions closing up access altogether. Europeana’s report Making Public AI reality: How cultural heritage can lead the way identifies two groups at each end of a spectrum from wide embrace to protective defensive closing up. CHIs face a binary choice between allowing unrestricted extraction by all AI developers or restricting access in blunt and overbroad ways, which is often referred to as ‘defensive enclosure’.

Some institutions have responded by locking up heritage that would otherwise be made available openly, revealing a paradox: CHIs whose mission is to share their collections end up doing the opposite. This conundrum is rattling the fragile scaffolding of open heritage, with content being further restricted and access to heritage in the public interest as collateral damage. The Open Heritage Statement emphasizes ethical and responsible AI and states that openness is neither absolute nor monolithic.

The concept of open heritage encourages access and reuse of heritage free from unfair, unnecessary barriers. CHIs often embrace openness in accordance with its underlying principles, which recognize nuance, contextuality, and the interplay among various governance frameworks. However, closing up completely is not a viable solution as it’s inefficient at best and harms public interests at worst. Instead, we need to move beyond a reactive enclosure pattern towards a more sustainable sharing equilibrium.

CC Signals tooling aims to restore agency in CHIs as data stewards while maintaining the open nature of heritage shared in the commons. CC Signals will create a middle path between ‘free for all vs defensive enclosure’ by establishing standardized prosocial conditions for access and reuse in an AI context. This balancing act preserves access to valuable heritage resources and ensures that institutions remain active participants in shaping the AI ecosystem.

CC is exploring avenues for combining contract and copyright law to give CC Signals legal force, incorporating protections for public interest reuse. CHIs are well-positioned to test and implement CC Signals as part of ethical frameworks for sharing heritage in the commons for AI use. They can help shape an AI ecosystem that fosters collaboration, ensures equitable access, and yields long-term public benefit.

The Open Heritage Statement serves as a timely reminder that openness is not just a means to an end but also a way to achieve it. CHIs need to move beyond mere openness and towards a more nuanced understanding of how their collections can be used responsibly in the AI era. This requires having ambitious conversations about making sure CHIs’ voices inform our increasingly AI-mediated world.

Today, you can contribute to shaping the AI that works for open heritage by signing the Open Heritage Statement, learning more about CC signals project and/or getting involved, building and supporting the commons’ infrastructures and prosocial technologies that align with open values, or investing in the open infrastructure. By doing so, we can work towards creating a future where cultural heritage is protected, preserved, and made available for all to enjoy.