By Tony Lai & Primavera de Filippi

The exponential growth of generative AI technologies has transformed how we produce, share, and monetize digital content, creating a complex landscape that simultaneously threatens and empowers creative professionals. Indeed, while generative AI presents significant challenges to the economic livelihood of many artists and creators, it also presents many new opportunities for creative expression and collaborative production—ultimately inviting us to re-conceptualise our relationships to creativity, authorship, and artistic production. 

Artists are beginning to view AI not as a replacement, but as a collaborative tool—a new medium that can extend and augment human creativity. It is allowing them to prototype and iterate through designs more rapidly, as well as to experiment with new forms of artistic expression that blend human creativity with machine-generated outputs. Generative AI challenges us to reimagine creativity not as a purely individual act, but as a more fluid, networked form of collaborative production that can transcend traditional boundaries between human and machine, original and derivative, creation and interpretation.

Figure 1: An image generated through the author’s alias on alias.studio, a platform for artists to create generative ai models, generate revenue and protect their creative rights.

This, of course, also requires new Intellectual Property (IP) management frameworks. A variety of regulatory reforms are on the way (e.g. the AI Act in Europe and the California AI Transparency Act in the U.S.) but are currently limited and fragmented in scope. Existing regulations focus on narrow aspects like data protection, algorithmic transparency, or copyright and data mining—reflecting a piecemeal approach that fails to address the comprehensive challenges posed by generative AI. Key limitations in current regulatory approaches include insufficient mechanisms for tracking and attributing AI-generated content and inadequate frameworks for compensating original creators whose work trains AI models.

The regulatory challenges of generative AI mirror historical precedents, particularly the early internet era when existing legal frameworks struggled to address the new practices of digital content sharing. Peer-to-peer file-sharing once questioned the viability of traditional copyright enforcement. Similarly, generative AI requires a fundamentally new approach to IP management and creative production. To address these challenges, we need flexible IP frameworks that recognize the collaborative nature of AI-assisted creation, along with new mechanisms for transparent attribution and fair compensation. As the law is struggling to cope with the rapid pace of innovation in the generative AI industry, we believe that new “private ordering” mechanisms are required to quickly adapt to these technological innovations.  

A journey towards a consolidated, holistic approach

At the CodeX Blockchain Group, we research and publish informed perspectives around the blockchain ecosystem and seek to become an inclusive, neutral forum for regulators and policy-makers to convene with academics, professionals, and technologists across Stanford and the wider blockchain community. We see blockchain-based systems as expressions of computational law, with many unique properties, including around transparency, interoperability and incentivization.

Figure 2: Traditional vs. Blockchain-enabled IP Management

Feature	Traditional IP Management	Blockchain-Enabled IP Management
Attribution	Manual	Automatic and verifiable
Royalties	Centralized distribution	Decentralized and automated
Transparency	Limited	Full traceability through blockchain
Licensing Flexibility	Rigid	Smart contract-enabled customization

Alongside our wider community of collaborators and partners, we have been gathering across various conferences, projects, jurisdictions and working groups to address some of the generative AI opportunities and challenges by leveraging blockchain technology to design new, interoperable computational law standards for managing IP rights. In expanding this work to the design of new open, decentralized, and transparent standards for generative AI, we aim to establish a foundation for interoperable IP management frameworks that can meet the needs of new forms of collaborative activities—from art, to business, to civic participation and democratic dialogue. These standards include the embedding of legal licenses into NFTs (Non-Fungible Tokens), providing a transparent, automated solution for IP licensing, fostering innovation while protecting the rights of creators and stakeholders.

For example, imagine a visual artist who licenses their work for training a generative AI model. Without standardized IP frameworks, the artist risks losing control over how their work is used or credited. Using blockchain-enabled NFTs with embedded legal licenses, the artist could specify terms for how their artwork can be used in training or incorporated into outputs, or track and verify where and how their work is used, ensuring attribution and fair compensation. As a result, a generative AI platform could automatically enforce royalty payments whenever the platform generates an image inspired by the artist’s original work.

We envision a world where artists, businesses, civic actors, and developers can collaborate seamlessly, while generating and respecting IP rights. At the core of this vision is the development of a standardized governance framework that promotes collaboration amongst the various stakeholders of the generative AI industry that are committed to the “rightful use” of AI. 

This includes the creation of a collaborative endeavor, leveraging IP law (trademark and copyright) to promote collaboration, innovation, and safety in the AI ecosystem. At the heart of this initiative is a publicly licensed trademark that signals compliance with ethical and legal standards for generative AI applications, ensuring a recognized and trusted brand for all participating entities. This trademark can be tied to a charter that serves as its licensing mechanism and outlines the principles and commitments required for joining the collaborative endeavor. Members can self-select to use the label, but if they do so, they must legally commit to abiding by the rules of the associated charter. Importantly, by requiring members to provide privileged access conditions to their IP assets to all other members of the initiative (e.g. through a Copyfair license), we aim to move away from the traditional payoff structure whereby competition is the dominant strategy towards a new payoff structure that incentivizes cooperation, fostering a more collaborative and innovative environment. This is particularly relevant for the generative AI ecosystem, where it has become extremely difficult for emergent players and startups to compete on a level playing field with the established dominant players.

We are grateful to every individual and group we have engaged with around this vision, who each offer unique insights and expertise for the journey ahead: Megan Ma, Roland Vogl, and the CodeX community offer established leadership in computational law, and insights into intersections with legal education, I.P., and A.I. The team at Alien develops blockchain-based legal technologies, particularly token-bound licenses, to facilitate transparent and automated IP licensing. We work alongside Josh Tan, B Cavallo and other researchers from the Metagov and Public AI ecosystems, curating discussions and sharing ideas at the frontier of AI governance and decentralized systems. With RadicalxChange we focus on reimagining social institutions, and through their Legal Design Lab have been working on innovative approaches to governance and legal design through systems of private law. The team at Blockscience with their proficiency in complex systems engineering and blockchain analytics, assist in designing and analyzing the technical aspects of the proposed IP management systems, ensuring they are robust, scalable, and effective. As an artist and filmmaker integrating AI into creative works, Lawrence Lek offers a unique perspective on the practical implications of IP management in AI-generated art, contributing to the development of standards that protect and promote creative expression. Dedicated to building tools for rights holders and AI developers, Matt Dryhust, Holly Herndon, Jordan Meyer, Cullen Miller, and the team at Spawning share their expertise in creating ecosystems that respect and protect IP rights, aiding in the development of tools and standards that prevent unauthorized use of protected materials in AI training. This builds upon the work done by Open Futures, led by Paul Keller and Alek Tarwokwsi, focused on promoting the digital commons and fostering better policies for right holders in an open Internet. As a nonprofit R&D lab focused on building AI tools for coordination and deliberation, Colleen McKenzie and the team at the AI Objectives Institute help our work be informed by cutting-edge AI capabilities and aligned with broader societal objectives. Through our discussions with Tenzin Seldon, an advisor to the Stanford Human-Centered AI project, we benefit from her ongoing insights into ethical AI development and deployment.

As we continue our journey alongside these and many other allied friends and colleagues, we are forming a dedicated task force of legal scholars, technologists, and IP stakeholders to collaboratively design, test, and refine the framework. We hope this task force can channel this wealth of expertise spanning computational law, blockchain systems, decentralized governance, and creative industries, to nurture frameworks for collaboration that will help drive innovation, inclusivity, and accountability across the whole lifecycle of Generative AI, from model training to content generation, and in a diverse array of public and civic interest use cases, from art and creativity to health and climate action, from circular economies and community currencies, to food systems and regenerative agriculture.

In the coming months, we aim to:

• Formalize partnerships and finalize criteria for participation in the task force.
• Develop a research roadmap with clear milestones and deliverables.
• Launch pilot projects to test and validate the framework.
• Engage with IP lawyers, creators, and industry leaders through workshops and at CodeX FutureLaw, in April 2025.

Join Us

We invite researchers, technologists, creators, and policymakers to join us in shaping the future of Generative AI and IP standards, including at CodeX FutureLaw on 10 April 2025, and in our CodeX Blockchain Group activities alongside. Together, we can create a transparent, fair, and collaborative ecosystem for the rightful use of AI.

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Tony Lai is a Fellow at CodeX, the Stanford Center for Legal Informatics, leads the CodeX Blockchain Group, and is a Founding Editor of the Stanford Journal of Blockchain Law & Policy. He is a co-founder of legal-tech company Legal.io, and of the non-profit organization, Mothertree Labs. He specializes in governance tooling for public goods and ecological transition.

Primavera de Filippi is a legal scholar at Harvard and cofounder of Alien. She specializes in legal-tech solutions for AI, and has been developing blockchain-based legal technologies, particularly token-bound licenses, to facilitate transparent and automated IP licensing.

For inquiries and updates, please contact the CodeX Blockchain Group.