In May, CC’s Open Culture Program hosted a new webinar in our Open Culture Live series titled “Open Culture in the Age of AI: Concerns, Hopes and Opportunities.” In this blog post we share key takeaways and a link to the recording.

With CC considering new ways to engage with generative AI, we are excited to share highlights from the conversation that demonstrate some of the complex considerations regarding open sharing, cultural heritage, and contemporary creativity.

Suzanne Duncan, Chief Operating Officer at Te Hiku Media, New Zealand, said that her organization was born out of the Māori rights movement. It is collecting an archive of Māori language samples on its own platform to maintain data sovereignty. Te Hiku Media is now working to use AI tools to teach the language to heritage language reclaimers. Suzanne recommended that the best way to ensure diverse representation in AI outputs is to have communities involved in the building and testing of AI models, ideally by communities, for communities.

Minne Atairu, interdisciplinary artist and doctoral student in the Art and Art Education program at Teachers College, Columbia University, USA, shared examples of her works using the Benin Bronzes, artworks from Nigeria stolen by the British in the 19th century, and the changes that happened in the visual representation of art after the looting took place. Using images of the stolen items, she used models to explore visuals and materials and convert text to 3D models. Minne hopes that better ways of attribution and compensation can be re-envisioned, and that the wealth generated by AI and other technologies should be spread among creators, not just tech executives.

Bartolomeo Meletti, Head of Knowledge Exchange at CREATe, University of Glasgow, Scotland, spoke about copyright law and copyright exceptions in the UK, EU and US, focusing on what one can do with AI and copyrighted works without permission from the copyright owner, especially for purposes of research and education. He works to create guidance about how to navigate those permissions with generative AI in mind.

Michael Trizna, Data Scientist at the Smithsonian Institution, has explored how generative AI can help to speed up processes like providing “alt text” (text descriptions of visual materials) to images, without compromising the accuracy of the audio or visual description of works. He has also worked on an AI values statement, including labeling AI generated content as such and mechanisms for the audience to provide feedback. Mike raised concerns about the fact that only a few large cultural heritage institutions are resourced to engage with generative AI responsibly.

Overall, panelists conveyed a need for greater AI literacy to enable people to interrogate AI and ensure it can be used for good.

Watch the recording here.

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What is Open Culture Live?

In this series, we tackle some of the more complex challenges that face the open culture movement, bringing in speakers with personal and professional expertise on the topic.

• Back to Basics: Open Culture for Beginners 
• Respectful Terminologies & Changing the Subject 
• Whose Open Culture? Decolonization, Indigenization, and Restitution
• Maximizing the Value(s) of Open Access in Cultural Heritage Institutions