Intangiblia™
#1 Podcast on Goodpods - Intellectual Property Indie Podcasts
#3 Podcast on Goodpods - Intellectual Property Podcast
Plain talk about Intellectual Property. Podcast of Intangible Law™
Intangiblia™
AI, IP, and the Public Good
Artificial intelligence is rapidly becoming central to areas such as public health, education, agriculture, and climate resilience. In this context, the role of the State is coming into sharper focus, particularly in how governments can shape innovation to serve broad social goals. Intellectual property frameworks, often seen as tools for exclusivity, are being repurposed to support inclusive access and public benefit.
This special episode of Intangiblia was recorded as part of my participation in the workshop “The Role of the State in Advancing Equitable Access to AI,” taking place in Oxford in September 2025. Organized by Sumaya Nur Adan and Joanna Wiaterek, and supported by the Future of Life Institute, the event brings together legal scholars, policymakers, and technologists to examine how States can ensure that the benefits of AI are equitably shared.
The episode explores five legal and policy mechanisms that are already influencing how AI is governed through intellectual property. It discusses Canada’s ongoing efforts to map and license Crown-owned patents under a broader national strategy. It examines Singapore’s copyright reforms, which have introduced clear legal exceptions to support AI model training. The conversation also includes examples of culturally aware AI development, such as the open-source Falcon model in the UAE and community-led Indigenous data initiatives in New Zealand. It looks at how public interest licensing and voluntary IP pools are evolving in fields beyond health, and how state-led initiatives, such as public procurement and open research mandates, are being used to align technological development with social needs.
The episode also reviews recent legal rulings in the United States that have tested the limits of fair use in AI training. These include the 2024 decision involving OpenAI, the 2025 dismissal of claims against Meta, and the Bartz v. Anthropic case presided over by Judge Alsup, which underscored the difference between statistical pattern recognition and direct reproduction of copyrighted works.
Rather than focusing solely on restrictions or incentives, the discussion emphasizes how IP law can serve as a strategic governance tool. By adapting legal frameworks to current challenges, States can guide AI innovation toward inclusive outcomes and help ensure that technological advancement remains aligned with the public good.
Artificial intelligence isn't just about chips and code. It's about who gets to shape the future and who gets left out. From health breakthroughs to climate tools, AI can serve the public good, but only if the systems around it, like intellectual property, are designed for access, not just ownership. So what happens when IP becomes a bridge instead of a barrier? Stick around? We're about to unpack how states around the world are making that leap. Barrier Stick around.
Speaker 2:We're about to unpack how states around the world are making that leap. You are listening to Intangiblia, the podcast of intangible law, playing talk about intellectual property. Please welcome your host, Leticia Caminero.
Leticia Caminero (AI):Welcome to Intangiblia, where we explore the invisible threads that connect ideas, innovation and law. I'm Leticia Caminero, and this is a special bonus episode to mark my participation in the workshop the Role of the State in Advancing Equitable Access to AI happening this September in Oxford. Organized by Sumayya Nour Adan and Joanna Weaterek, this inaugural workshop is dedicated to exploring how governments can operationalize the benefits of artificial intelligence, ensuring equitable access for all. The event is supported by the Future of Life Institute, a global organization committed to steering transformative technology toward the public good. In this episode, we'll explore how states are rethinking intellectual property tools to make AI more open, ethical and inclusive, from open source licensing to copyright reforms, public innovation, procurement and more. Before we get into the technical parts, let's talk about the real reason we're here. It's not just about what governments are doing with AI. It's about why they're doing it Exactly.
Artemisa:Everyone's talking about access to AI tools, but access isn't enough if those tools aren't built for or by the people who need them.
Leticia Caminero (AI):That's why the role of the state is so crucial, not as a passive regulator, but as an active enabler, funding, negotiating and designing the systems that shape innovation outcomes.
Artemisa:And let's be honest, if systems weren't originally built with equity in mind, they were designed to protect exclusive rights and attract private investment.
Leticia Caminero (AI):But AI is changing the game. It's making innovation faster, more data-driven and way more dependent on shared resources like datasets, infrastructure and collective knowledge.
Artemisa:Which means the IP toolkit needs to evolve, not to throw out incentives, but to stretch the system so that innovation also serves people, not just profits.
Leticia Caminero (AI):In this episode, we're going to unpack five smart strategies governments are using to do exactly that. These aren't just abstract ideas. They're real policy tools with legal teeth.
Artemisa:We're talking public interest, licensing, copyright reforms, open source, ai and procurement strategies that promote digital public goods. So if you've ever wondered how law can shape fairness in the age of algorithms, stay tuned.
Leticia Caminero (AI):Before we dive in, a quick note about how this episode was made.
Artemisa:As your AI co-host. I was generated using artificial intelligence tools my voice, my personality, even some of my sass crafted with code, and Leticia's voice today, also cloned with AI.
Leticia Caminero (AI):The script you're hearing is a blend of human research and machine support. We used AI to organize legal frameworks, summarize case law and shape the narrative, but every word was fact-checked and refined by a real human. That's me Well real me.
Artemisa:So, yes, this is an episode about AI, made with AI, but always with transparency, accountability and a healthy respect for the law.
Leticia Caminero (AI):Now let's explore how governments are rewriting the rules of innovation, starting with how they license the technologies they fund. Let's start with something that sounds obvious but often isn't when the public pays for innovation, the public should benefit from it.
Artemisa:Right. Too often taxpayer-funded research ends up locked behind patents, paywalls or proprietary code that nobody can touch without a license or a lawyer.
Leticia Caminero (AI):But that's beginning to change. Some governments are now attaching conditions to public R&D funding to make sure the intellectual property generated is shared or at least licensed. More broadly.
Artemisa:Take Canada's Explore IP strategy. It maps out government-funded IP and encourages licensing across sectors. Some provinces are even considering models where crown-owned patents must be made available for public interest uses, especially in sectors like health, climate and AI interest uses, especially in sectors like health, climate and AI.
Leticia Caminero (AI):Meanwhile countries like the Netherlands, germany and New Zealand are piloting open supply and open sunlight mandates for AI outputs created with public funding. These include data sets, models and training tools designed to stay open by default.
Artemisa:And this isn't just policy wonk stuff. It's how you build digital public goods AI tools that solve real problems, from flood prediction to rural healthcare, that any country or startup can reuse or adapt. The upside faster innovation, especially in developing countries or underserved regions. Lower costs for researchers and small businesses. Transparency in model development and small businesses. Transparency in model development and training data. Public trust in how AI is funded and deployed.
Leticia Caminero (AI):The challenge is, of course, there's tension. Some inventors or universities worry that open licensing may reduce the commercial value of their discoveries.
Artemisa:Or that mandatory openness could discourage private investment or slow down tech transfer.
Leticia Caminero (AI):That's why many experts now recommend a flexible hybrid model keeping core IP accessible for public use while still allowing exclusive licenses in specific contexts.
Artemisa:Bottom line. When the state funds AI, it has the power and the responsibility to make sure the results don't gather dust in a patent vault.
Leticia Caminero (AI):Or worse, get bought up by a private firm and turn into an access barrier. Let's make that public investment count. When it comes to AI, copyright is one of the most contested frontiers. After all, ai models learn from existing content books, images, articles, music but is that?
Artemisa:legal. Enter the world of copyright exceptions for text and data mining, or TDM. These exceptions allow machines to analyze large amounts of copyrighted content without asking for permission. Each time, at least in some places.
Leticia Caminero (AI):The European Union's DSM directive introduced a structured approach. It allows non-commercial TDM by default and permits commercial TDM if rights holders don't opt out.
Artemisa:Meanwhile, singapore has gone further. In 2021, it passed a progressive copyright reform that explicitly allows data mining for both commercial and non-commercial AI training, with no opt-out clause.
Leticia Caminero (AI):Japan and the UK have also carved out TDM exceptions. The US, however, relies on a more flexible but less predictable concept.
Artemisa:fair use In 2024, a US federal judge dismissed part of a high-profile lawsuit against OpenAI ruling that using publicly available content to train AI can qualify as fair use. Then came June 2025, a busy month for AI and copyright. First, meta won a similar lawsuit brought by a group of authors, including Pulitzer Prize winner Michael Chabon. A US judge sided with the company, stating that the authors failed to prove that Meta's Lama models reproduced their copyrighted books in any meaningful way.
Leticia Caminero (AI):The ruling emphasized that using large volumes of text to extract statistical patterns without direct copying or replacing the market could fall under fair use. It's strengthening the notion that not all ingestion equals infringement.
Artemisa:with another opinion in Barts v Anthropic PBC, he dismissed most of the claims, stating that model training does not necessarily violate copyright if the outputs do not substantially resemble the source works.
Leticia Caminero (AI):Judge Alassip went further, warning that overextending copyright law to cover mere learning by machines could chill innovation. He stressed that copyright protects expression, not facts or functional analysis, and that anthropic outputs had to be judged on what they actually produced, not just what they were trained on.
Artemisa:It's early days and higher courts might still weigh in, but taken together, the open AI, meta and anthropic rulings give AI developers in the US a cautiously optimistic roadmap, especially when working with public content and ensuring non-verbatim outputs.
Leticia Caminero (AI):The White House AI Action Plan, published in early 2025, acknowledges the tension. It calls for clearer guidelines and multi-stakeholder dialogue on IP rights in AI training, particularly around data sets, transparency and ethical boundaries.
Artemisa:And while the federal government hasn't proposed sweeping reforms yet, it's promoting sector-specific initiatives like encouraging open licensing for publicly funded data sets and supporting the National AI Research Resource, which includes shared data and computing tools for researchers.
Leticia Caminero (AI):So in the US the direction is clear. The government sees value in making AI development more inclusive and transparent, and that includes rethinking how copyright law supports or blocks that mission. But there's a catch Even if training qualifies as fair use, many models are so opaque that we can't tell what copyrighted material they ingested or how it's being used.
Artemisa:This is known as the black box problem. Without transparency in training data and model behavior, it's hard to assess compliance, bias or accountability.
Leticia Caminero (AI):That's why some jurisdictions are now linking TIRMAC exceptions to transparency obligations. Think documentation, data set, registries or even watermarking outputs.
Artemisa:It's a balancing act between enabling innovation and protecting creators, between building powerful models and understanding how they think.
Leticia Caminero (AI):Copyright law is evolving. The question is whether it evolved fast enough and fairly enough to guide AI towards socially beneficial outcomes.
Artemisa:The tools are there, the policies are emerging. Now it's about building systems that serve both human and machine learning.
Speaker 2:Intangiblia, the podcast of intangible law. Playing talk about intellectual property.
Leticia Caminero (AI):Let's talk about open source AI, not just as a technical choice, but as a strategy for inclusion.
Artemisa:In places where private AI development is limited or foreign tech dominates the market, open source models can be a lifeline. They let communities build, adapt and own the tools they need.
Leticia Caminero (AI):They let communities build, adapt and own the tools they need. We've seen this clearly in the UAE, where the Technology Innovation Institute released Falcon, an open source large language model.
Artemisa:The goal help researchers and developers in Arabic speaking countries work with high performing models tailored to their region, and in New Zealand, the government-backed Te Heku Media project is using open-source AI to protect and revive Maori language and culture. They're training models on Indigenous data sets with full community consent to create speech recognition and text tools grounded in local values.
Leticia Caminero (AI):This is a powerful reminder. Inclusive AI isn't just about access. It's about relevance AI that reflects local languages, knowledge systems and social realities.
Artemisa:Open source licensing helps make that possible. It removes commercial and legal barriers, accelerates localization and invites grassroots innovation.
Leticia Caminero (AI):And when the state gets involved by funding, curating or deploying these models, it multiplies the impact. We move from isolated innovation to scalable public infrastructure.
Artemisa:Challenges to watch Data quality and bias. Even open models need strong data sets and ethical guidelines. Capacity gaps. Local teams may need support, not just code. Sustainability maintaining open models requires long-term funding and stewardship. What works? Successful programs often include community participation, transparent licensing terms and clear government leadership.
Leticia Caminero (AI):And the IP structures behind them, like Creative Commons, open data agreements or open source model cards, are what keep the doors open for future use.
Artemisa:Bottom line. When AI tools are built for everyone, they work better for everyone.
Leticia Caminero (AI):And open source is one way states are putting that idea into practice. Now let's talk about something that sounds very technical but is actually very powerful IP pooling and public interest licensing.
Artemisa:These are tools states can use to negotiate access instead of just regulating or reacting, and, when done right, they allow governments to share intellectual property across sectors, companies or even countries.
Leticia Caminero (AI):A perfect example is the COVID-19 Technology Access Pool, or CTAP, created by the World Health Organization. It invited patent holders to voluntarily license health technologies for broader, low-cost access.
Artemisa:While CTAP didn't attract as many tech contributors as hoped, the idea behind it is starting to gain traction in AI.
Leticia Caminero (AI):We're seeing more discussion around sovereign patent pools for AI models and data sets, especially those created with public funding. This means governments can consolidate certain IPS sets and license them non-exclusively for high-impact applications like education, agriculture or public health.
Artemisa:This approach is flexible. It keeps the door open for private sector engagement, but with terms that reflect equity, like requiring licensees to serve underserved markets or disclose how they use. The model Otis unlocks cross-border collaboration on AI for development. Lower licensing barriers for small businesses and NGOs. Lower licensing barriers for small businesses and NGOs. Stronger negotiation power for states in global AI deals.
Leticia Caminero (AI):Of course, voluntary licensing only works when there's trust and transparency, and IP pools require solid infrastructure, clear governance and incentive structures that work for both rights holders and the public.
Artemisa:But here's the real innovation treating IP as a negotiable asset, not just a legal right, something that can be structured to support access, adaptation and scaling, not just exclusivity.
Leticia Caminero (AI):In a world where AI systems often cross borders and sectors, public interest licensing gives governments the tools to stay in the game and shape outcomes that benefit more people.
Artemisa:Especially when private innovation doesn't automatically serve the public good.
Leticia Caminero (AI):Let's wrap up the strategy walkthrough with a big idea Governments not just reacting to innovation, but leading it.
Artemisa:We mean governments acting like innovators themselves, using public procurement, challenge funds and sandbox environments to steer AI in directions that serve society.
Leticia Caminero (AI):Exactly, this is the space of government-led open innovation, and it's getting traction fast From national AI sandboxes to data collaboratives and AI research hubs. States are creating control spaces where risks are managed and equities designed in.
Artemisa:Let's take the G7s AI Grand Challenges. These are publicly funded missions designed to crowd in innovation for the public good, focusing on trustworthy AI, healthcare and sustainability. They don't just ask for private solutions.
Leticia Caminero (AI):They co-design the terms of access and IP and the European Commission's AI factories combine funding, infrastructure and open licensing frameworks to accelerate collaborative model development for small firms and researchers.
Artemisa:What makes it open? Pre-competitive collaboration, ip terms baked into contracts, not as an afterthought. Shared data infrastructures, public oversight of outputs.
Leticia Caminero (AI):What's tricky. States need legal capacity to build this. That means smart contract design, ip literacy and long-term digital governance, not just flashy announcements.
Artemisa:And they must avoid extractive models where public R&D gets privatized at the finish line. The goal is to keep innovation circulating, not captured.
Leticia Caminero (AI):This is the future States as co-creators, not just regulators, not blocking innovation, but unlocking it on terms that include more people and more possibilities.
Artemisa:And using IP law as a lever, not a wall.
Leticia Caminero (AI):So what can policymakers actually do with all this? We've explored five big ideas, and now it's time to draw some conclusions.
Artemisa:Not slogans, not theory practical steps. If you're a government actor, innovation funder or policymaker, here's a roadmap to make AI more inclusive using the power of IP code datasets include clear licensing terms that promote broad reuse.
Leticia Caminero (AI):Not everything has to be open source, but public money should create public value Two codify fair training practices.
Artemisa:introduce or clarify copyright exceptions for text and data mining with transparency requirements, consider sector-specific carve-outs or guidelines for ethical AI training, especially in education, health and public language models. Three support regional and cultural relevance. Fund open source models and tools built for and by local communities. Prioritize languages, indigenous data and domain-specific AI that reflect the realities of diverse populations and protect contributors through clear benefit sharing and data sovereignty frameworks.
Leticia Caminero (AI):Four enable voluntary IP sharing mechanisms. Build and maintain public interest, patent pools or open licensing platforms. Offer financial or reputational incentives for rights holders who contribute. Ensure clear governance and alignment with national development goals.
Artemisa:Five lead innovation by example. Use public procurement and government-led challenges to drive inclusive outcomes. Design IP terms from the start. Ensuring that AI built with public involvement remains accessible, safe and auditable.
Leticia Caminero (AI):All of these tools already exist. The real shift is in how we combine them with courage, creativity and a long-term view.
Artemisa:Because equitable access to AI isn't just about what's invented. It's about what's shared, what's protected and who gets to use it.
Leticia Caminero (AI):And that means rewriting the rules, not to limit progress but to invite more people in. That's a wrap on this special bonus episode of Indangibria. Whether you're a policymaker, researcher, legal advisor or simply curious about the future of AI and society researcher, legal advisor or simply curious about the future of AI and society we hope this gave you new ways to think about how IP can support, not stifle, equitable innovation.
Artemisa:From open licensing to copyright exceptions, from community-driven models to public innovation strategies, we've seen that the role of the state isn't just about catching up to AI. It's about shaping it.
Leticia Caminero (AI):This episode was created to accompany my participation the real Leticia that is in the workshop the Role of the State in Advancing Equitable Access to AI, organized by Sumaya Nooradan and Joanne Weaterek with support from the Future of Life Institute. We'll be back soon with our regular season of interviews, inventions and imagination.
Artemisa:Until then, keep questioning, keep creating and, above all, keep innovating with intention.
Speaker 2:Intangiblia the podcast of intangible law plain talk about intellectual property. Did you like what we talked today? Please share with your network. Do you want to learn more about intellectual property? Subscribe now on your favorite podcast player. Follow us on Instagram, Facebook, linkedin and Twitter. Visit our website, wwwintangibliacom. Copyright Leticia Caminero 2020. All rights reserved. This podcast is provided for information purposes only.
