The invisible legal architecture behind AI systems, either talking to each other or failing spectacularly, takes center stage in this deep dive into interoperability. Far more than technical specifications, the ability of AI models to connect and share data represents a battlefield where intellectual property rights, competition law, and global governance clash to determine who controls the digital ecosystem.

Starting with IBM’s mainframe antitrust case, we trace how European regulators forced a tech giant to provide third parties with technical documentation needed for maintenance. This early precedent established that when your system becomes essential infrastructure, monopolizing access raises legal red flags. The SAS v. World Programming Limited ruling further clarified that functionality, programming languages, and data formats cannot be protected by copyright, giving developers freedom to create compatible systems without infringement concerns.

Patent battles reveal another dimension of interoperability politics. Cases like Huawei v. ZTE established detailed protocols for negotiating Standard Essential Patents, preventing companies from weaponizing their intellectual property to block competitors. The Microsoft v. Motorola judgment defined what “reasonable” licensing fees actually look like, protecting the principle that interoperability shouldn’t bankrupt smaller players.

Google’s decade-long fight with Oracle over Java API copyright culminated in a Supreme Court victory validating that reimplementing interfaces for compatibility constitutes fair use, a landmark decision protecting the ability to build systems that communicate with existing platforms without permission. Meanwhile, the Oracle v. Rimini ruling reinforced that third-party software support isn’t derivative copyright infringement, even when designed exclusively for another company’s ecosystem.

Beyond courtrooms, international frameworks increasingly shape AI interoperability standards. From UNESCO’s ethics recommendation to ISO/IEC 42001 certification, from the G7 Hiroshima AI Process to regional initiatives like the African Union’s Data Policy Framework, these governance mechanisms are establishing a global language for compatible, trustworthy AI development.

Whether you’re building AI systems, crafting policy, or simply trying to understand why your tools won’t work together, these legal precedents reveal that interoperability isn’t just about good coding. It’s about who controls the playground, the rulebook, and ultimately, the future of AI innovation.

Jean Marc Seigneur – In Trust We Build: Designing the Future of Digital Reputation – Intangiblia™

What if your glasses could spot a deepfake before your gut does? We sit down with Jean Marc Seigneur, a veteran researcher of decentralized trust, to map where security failed, where it’s catching up, and how proof—not vibes—will anchor the next decade of digital life. From central bank digital currencies to NFTs that carry qualified electronic signatures, we unpack how legal recognition and cryptography can finally meet in the middle, turning tokens into enforceable rights and payments into reliable public infrastructure.We also go beyond buzzwords to the missing pieces: education and design. Friendly apps hide sharp edges, so we talk about why countries need their own experts, not just imported tech, and how wallets must evolve with safer recovery, better defaults, and interfaces that explain risk without slowing you down. AI raises the stakes, so we explore signed videos, verifiable identities, and provenance trails that help you tell a real voice from a cloned one at a glance. Reputation won’t live on a web page for long; it’s moving into the physical world as augmented overlays that can help or harm depending on what they reveal and to whom.Bias won’t vanish either, because human trust is social and local. We discuss how to balance peer signals with regulators’ oversight, why transparency about AI use will give way to tracking human effort, and what a time-based “work token” could add to creative markets. The red thread across it all—payments, NFTs, augmented humans, and AI media—is simple and demanding: protect freedom while proving claims. If we want technology that empowers rather than deceives, we have to design, debate, and defend the trust layer itself.Enjoy the conversation? Subscribe, share with a friend who cares about digital trust, and leave a review to help more curious minds find the show.Send us a textCheck out "Protection for the Inventive Mind" – available now on Amazon in print and Kindle formats. The views and opinions expressed (by the host and guest(s)) in this podcast are strictly their own and do not necessarily reflect the official policy or position of the entities with which they may be affiliated. This podcast should in no way be construed as promoting or criticizing any particular government policy, institutional position, private interest or commercial entity. Any content provided is for informational and educational purposes only.

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