Are you thinking about how generative artificial intelligence (AI) intersects with creativity? Or how it draws from existing works and collections? Or enables new understandings of culture?
Join Creative Commons in NYC on 13 September 2023 for a full-day symposium focused on the intersection of generative artificial intelligence, cultural heritage, and contemporary creativity. This event brings together cultural heritage experts, contemporary creators working with AI tools, legal experts, and platform builders.
Spots are limited! Register now to make sure you are part of the live conversation.
We are excited to share the program for this symposium, featuring a series of panels tackling critical questions regarding the potential of AI tools for creators, cultural heritage institutions, and the general public. The proceedings will be recorded for online distribution after the event. We are grateful to our sponsors for their support of this event: Akin Gump LLP (lead symposium sponsor), Morrison Foerster LLP (workshop sponsor), and the Engelberg Center on Innovation Law & Policy at NYU Law School (hosting sponsor).
|Time (all EDT)
|Catherine Stihler (CEO) and Brigitte Vézina of Creative Commons
|Welcome and opening remarks
|Mike Kemezis (Connecticut Humanities) moderating a conversation with Mike Trizna (Smithsonian Institution), Garvita Kapur (The New York Public Library), Abbey Potter (Library of Congress), and Amanda Figueroa (Curationist)
|Can AI propel cultural heritage institutions through their digital transformation? AI has been used as an enabler for several cultural heritage institutions’ (CHIs) transformational goals: from digitization, to preservation, to providing open access to users far and wide. How can digital and AI technologies help institutions realize their mission? This panel will probe the role of AI in ensuring CHIs’ relevance in the 21st century.
|Brigitte Vézina (Creative Commons) moderating a conversation with Yacine Jernite (Hugging Face), Stacey Lantagne (Western New England University), and Nicholas Garcia (Public Knowledge)
|Can AI help everyone enjoy culture as a global public good? In 2022, UNESCO declared culture a global public good, paving the way for culture to be recognized as a sustainable development goal in and of itself. The advent of AI technologies hold many promises to reduce the barriers for enjoyment of culture by people all over the world, especially for marginalized groups such as women, youth and Indigenous peoples. At the same time, AI may pose risks in perpetuating cultural power imbalances. This panel will strive to determine how AI can concretely support culture as a global public good.
|Ami Bhatt (McKinsey & Co) moderating a conversation with Justin Haan (Morrison Foerster), Wade Wallerstein (Grey Area), karen darricades (CC Canada), and Carla Gannis (NYU)
|Fair remuneration of creators — Can AI be an answer? This panel will look at existing and potential remuneration models for creators in the age of AI and explore solutions for fair and equitable retribution of creators, including through the lens of distributive justice.
|A light lunch and beverages will be provided.
|Marta Belcher (Filecoin Foundation) moderating a conversation with Aviya Skowron (EleutherAI), Dave Hansen (Authors Alliance), Rebekah Tweed (All Tech Is Human), and Eryk Salvaggio (Siegel Family Endowment)
|Copyright and open sharing of heritage collections and data: bounty or bane for creativity in the age of AI? This panel will focus on some of the challenges posed by copyright, on a global scale, with regards to sharing of cultural heritage, with humans and machines. It will also explore the barriers that cultural heritage institutions face in sharing their collections, and the opportunities that emerge when they are able to do so.
|Matthew Allen (BRIC Arts) moderating a conversation with Allison Sherrick (METRO), Kengchakaj (elekhlekha artist collective), and Minne Atairu (Columbia University)
|Diversity, inclusivity, sustainability, and cultural identity — What role for AI? This panel will focus on the necessary interplay between labeling of culture heritage materials and the creation of datasets for ML/AI, with a particular view to emerging practices around the ethical sharing of cultural heritage.
|Nitcha Tothong (eleklekha artist collective) moderating a conversation with Sasha Stiles (Artist), Max Sills (Midjourney), and Sarvesh Mahajan (Crowell & Moring)
|Creativity, machines, and the heritage commons — What collaboration opportunities are there? This panel will bring together those who are actively experimenting with and using AI technologies in conversation with creators and cultural heritage practitioners who steward heritage collections in the commons.
|Scott Sholder (CDAS) moderating a conversation with Kayvan Ghaffari (MakersPlace), Jennie Rose Halperin (Library Futures), and Heather Timm (Artist)
|Users are creators — Is AI blurring the lines of creativity in the copyright framework? With AI opening the doors to fresh modes of creative expression, the traditional roles of art creators and users blend into each other to offer new forms of collaborative creation. This panel will focus on the new intertwined patterns at play in the creativity process enabled by AI technologies.
|/ CLOSING REMARKS
View or download the full program and schedule >
Like the rest of the world, CC has been watching generative AI and trying to understand the many complex issues raised by these amazing new tools. We are especially focused on the intersection of copyright law and generative AI. How can CC’s strategy for better sharing support the development of this technology while also respecting the work of human creators? How can we ensure AI operates in a better internet for everyone? We are exploring these issues in a series of blog posts by the CC team and invited guests that look at concerns related to AI inputs (training data), AI outputs (works created by AI tools), and the ways that people use AI. Read our overview on generative AI or see all our posts on AI.
Note: We use “artificial intelligence” and “AI” as shorthand terms for what we know is a complex field of technologies and practices, currently involving machine learning and large language models (LLMs). Using the abbreviation “AI” is handy, but not ideal, because we recognize that AI is not really “artificial” (in that AI is created and used by humans), nor “intelligent” (at least in the way we think of human intelligence).