IP Fridays - your intellectual property podcast about trademarks, patents, designs and much more

My co-host Ken Suzan and I are welcoming you the episode 176 of the IP Fridays Podcast. Today’s interview guest is returning guest Franklin Graves, who is a senior counsel at Linkedin and teaching IP law at Emerson College. With my co-host Ken Suzan he is discussing how the law for creators has dramatically changed in the past years.

Franklin Graves is expressing his personal views and not the views of Linkedin or Microsoft. He is talking about the paper “Upload Complete” before he joined Linkedin.

Bio: https://www.linkedin.com/in/franklingraves/

Paper: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5271442

Website: https://creatoreconomylaw.com/

But before we jump into this interview, I have news for you!

Richard Meade, a judge on the UK High Court and one of the most prominent figures in European patent law, was appointed Lord Justice of Appeal at the British Court of Appeal on June 12, 2026. Meade played a key role in numerous landmark British patent decisions, particularly in the area of standard-essential patents (SEPs) and FRAND licenses.

In Insulet Corp. v. EOFlow Co., No. 2025-1807, the U.S. Court of Appeals for the Federal Circuit completely overturned the original $452 million judgment (which had already been reduced by the District Court to $59.4 million) in favor of Insulet.

In its decision of June 2, 2026, in the case of Fujifilm v. Kodak, the UPC Board of Appeal provided comprehensive clarifications regarding so-called “long-arm jurisdiction”—that is, the question of whether the UPC can also rule on national patent claims outside the UPC territory (such as in the United Kingdom). In 14 guiding principles, the judges established specific procedural rules for various categories of cases. There is no automatic UPC jurisdiction over national patent claims outside the UPC territory.

The Munich Regional Court has issued an arrest warrant against the managing director of Polytech Health & Aesthetics GmbH because he is alleged to have continued to exploit the Brazilian company Silimed’s patent for breast implants despite a preliminary injunction.

A number of IT and automotive industry associations—which are among the most frequent users of Inter Partes Reviews (IPR) at the U.S. Patent and Trademark Office—have filed an amicus brief with the Supreme Court, urging the Court to grant Google’s certiorari petition.

An attorney for a Las Vegas performer has asked a California federal judge to temporarily prohibit Taylor Swift from using “The Life of a Showgirl” as a trademark while the trademark lawsuit is pending. Swift’s attorney called the lawsuit baseless.

And now let’s hear Ken discuss creator law with Franklin!

AI, Platform Law, and the Creator Economy: What Businesses Need to Know Now

Franklin Graves has spent his entire career watching digital content move through systems that most people never see. He started in marketing at a major music label right out of law school, then represented individual creators on YouTube in a pro bono capacity, then moved to the platform side at Eventbrite, and today works as Senior Product Counsel at LinkedIn, where he focuses on AI, data, and the regulatory questions that come with both. His recently published law review article, Upload Complete: An Introduction to Creator Economy Law, is the first academic paper to address the creator economy as a distinct legal field. In a recent episode of the IP Fridays podcast, he spoke with host Kenneth Suzan about responsible AI development, platform regulation, and what it actually means to own your audience in a world where the rules keep changing overnight.

From Content Creator to Platform Lawyer

The through-line in Graves’ career is a genuine understanding of how content moves from an idea in someone’s head to an audience on a screen. That experience, he argues, is precisely what in-house counsel needs right now. Lawyers working on AI and product development cannot afford to sit at a distance from the technology they are advising on. They need to use the tools, experience them as a creator or end user would, and understand the nuances of how a product actually operates before it reaches the public. Understanding the product first is the precondition for everything else.

That philosophy translates directly into how he approaches responsible AI implementation. The landscape of AI standards is crowded: NIST frameworks, the EU AI Act, sector-specific guidance, and a growing body of industry-adopted best practices. The challenge for in-house counsel is not knowing that these standards exist. It is making them actionable for the engineering and product teams they support. Abstract principles need to become concrete controls and workflows. Graves offers one practical shortcut: most companies already have open source software review processes that involve the right stakeholders, the right sign-off levels, and the right security checks. Layering the specifics of generative AI or large language models onto those existing processes is far more efficient than building something new from scratch.

A Fragmented Regulatory World

The geopolitical dimension of AI regulation is something Graves thinks about constantly in his role at LinkedIn. The EU AI Act, shifting US executive orders, and country-specific approaches to data privacy have created a regulatory environment that can change the rules of the game without warning. His analogy is instructive: creators have long understood what it means to build a community on a platform they do not own. An algorithm change, a policy update, or a government ban can wipe out years of audience-building overnight. Businesses deploying AI tools globally now face a structurally similar problem. The response, for creators and for platforms alike, is to build resilience rather than rely on stability that may not last.

TikTok is the clearest recent example. When the platform faced the prospect of being shut down in the United States on national security grounds, it triggered a broader conversation about platform dependence that had been building for years. Creators who had invested their entire business in one platform suddenly confronted the possibility that their audience could simply disappear. The lesson is not that platforms are bad. It is that concentration of any kind, whether it is your audience, your data pipeline, or your regulatory compliance strategy, creates fragility.

What Is a Creator, Legally Speaking?

One of the central contributions of Graves’ law review article is definitional. The terminology matters more than it might seem. When courts and regulators talk about creators without a shared understanding of what that word means, the resulting legal analysis tends to miss the mark. Graves draws a distinction between users who post content, creators who post with the intent to build an audience and eventually monetize it, and influencers, a subset of creators who are actively running a small business through their content. The difference is intent. A parent posting family photos on Facebook is a user. Someone building a subscription community around their professional expertise is running a business, and the legal framework that applies to them should reflect that.

That distinction matters practically when it comes to liability. As more creators build their own platforms, whether through custom membership sites, open source tools like Ghost, or federated social networks, they take on obligations that previously fell to large platforms: content moderation policies, privacy notices, terms of service, and compliance with data regulations across multiple jurisdictions. A creator in Tennessee running a membership platform with subscribers in Germany is operating a global business, whether they think of themselves that way or not.

Protecting Children Online: A Question Without a Clean Answer

The tension between age verification and privacy is one of the more difficult problems in platform law right now. Australia, several European countries, and a growing number of US states have introduced or passed minimum age requirements for social media accounts. The technical challenge is real: verifying age online requires collecting identifying information, and collecting identifying information creates privacy risk, particularly for the young people the laws are designed to protect. Who should bear the responsibility for that verification is also unresolved. Is it the platform? The app store? The mobile operating system? Graves does not pretend there is a clean answer, but he points to the mobile layer as an underexplored option. The Apple App Store and Google Play Store already have significant leverage over which apps reach users on their devices. Whether that leverage should extend to age verification is a question that deserves more attention than it currently receives.

The Right of Publicity in the Age of AI

Voice cloning, digital replicas, and AI-generated synthetic media have pushed the right of publicity into territory that traditional IP law was not designed to cover. Trademark law, copyright law, and existing publicity rights each capture part of the problem but none of them covers it completely. The result, as Graves describes it, is a period of experimentation: lawyers filing trademarks on vocal sounds and phrases, states updating their publicity statutes to explicitly mention artificial intelligence, and entertainment unions negotiating over who controls a performance and any AI-generated iterations of it.

Tennessee’s Elvis Act is a concrete example of the legislative response: the state updated its right of publicity law to include voice and to reference AI directly. Similar efforts are underway elsewhere. The underlying challenge is calibrating protection so that it gives creators and performers meaningful control over their likeness and voice without foreclosing the development of generative AI systems that depend on broad rights to process and learn from content. Somewhere between those two interests, a workable legal framework needs to emerge.

The brand deal context may be where the issue becomes most immediately practical. When a brand partners with an influencer and the campaign involves generative AI in any form, the contract needs to address control explicitly. Who has final approval over how the influencer’s likeness or voice is used in AI-generated deliverables? What happens to those assets after the campaign ends? These are not hypothetical questions. They are contract drafting problems that any brand counsel or creator attorney should be addressing today.

What Comes Next

Graves is cautious about predictions, but his sense of direction is clear. The regulatory environment will continue to fragment before it converges. The right of publicity will be updated, imperfectly, in more jurisdictions. Creators will continue to move toward owning more of their infrastructure. And the lawyers who do this work best will be the ones who understand the technology well enough to translate it into practical, defensible decisions for the people they advise.

Full Transcript:

Ken Suzan: Thank you, Rolf. Our returning guest today is Franklin Graves. Franklin is the founder and editor of Creator Economy Law, a website and newsletter that educates creator economy professionals on the intersection of law and policy with the world of creators, brands, and platforms. Franklin also published the first law review article focused on the creator economy, Upload Complete, an introduction to creator economy law. He regularly appears across news and media outlets as a commentator and contributor with a focus on educating creators and raising awareness of all legal aspects of the creator economy. Franklin is based in Nashville, Tennessee.

Ken Suzan: Franklin was invited to participate as one of the creators and creator economy professionals in the first ever White House creator economy conference. Franklin works full time as a product counsel at LinkedIn Corporation. As a member of the product and data team, he focuses on emerging issues in AI and data. Franklin previously held roles on the technology law group at HCA Healthcare, the commercial legal team at Eventbrite, and the business and legal affairs team at Naxos Music Group. Welcome back Franklin to the IP Fridays podcast.

Franklin Graves: Thank you so much for having me. It is exciting to be back and reflecting over the last decade since I last joined and also the paper that I wrote that dives into this in more detail. So I really appreciate it. And yes, full disclosure, I currently work for LinkedIn, which is a subsidiary of Microsoft. I’m here in my personal capacity to talk about this, the paper I wrote before joining LinkedIn and all of that. So thank you so much for having me back.

Ken Suzan: Excellent. So Franklin, since your last appearance on IP Fridays in 2017, your career has evolved significantly. You are now senior product counsel at LinkedIn focusing on AI and data. How has working inside a major tech platform changed your perspective on the legal frameworks governing digital content compared to when you were viewing it purely from the creator side?

Franklin Graves: I appreciate that question because when I wrote the article, I did not work for LinkedIn. And I had been coming from a history in my career where I, right out of law school, worked for a record label like we talked about almost 10 years ago. And I was on the content creation side. I’ve represented a major distributor of classical music digitally at the time. And that was my first exposure to understanding how content was taken from the initial inception stage from creators and routed through all the various digital platforms that were at the time still evolving and even arguably still today continue to evolve. The early days of YouTube Music launching and then Apple Music launching, and then going through all the phases of high-res audio and everything that came after that. So that was an interesting perspective to start my career with. And then I went to Eventbrite, which is a ticketing platform, but was also focused on elevating event creators. They kind of took on that moniker of “Hey, we are event creators that we support.” And that was arguably my first exposure to the platform side, the tech platform side of it, because Eventbrite is a platform. And so then I evolved from there in my personal capacity, in a pro bono capacity representing individual creators across the YouTube space. And that’s what we talked about a little bit back when I first came on the podcast.

Franklin Graves: Over the last decade, it’s been a chance to grow my own understanding of the creator economy. The terminology “creator economy” came around. And then now on the other side of it, having written the article and all that, and now being fully in-house at LinkedIn, I truly am experiencing a social media platform. LinkedIn is of course arguably way more than just the platform itself. There are so many different avenues to it, but it is a chance for me to understand what it is like working for a company that is operating the platform that people are distributing content on. There’s a user journey to content and all of that. So it’s definitely enhanced and given me a different perspective from a major tech platform side. And part of my role at LinkedIn is really heavily focused on understanding regulation and how that from an AI and data perspective impacts the company. And so I’ve been really leveling up my game over the last year and a half that I’ve been here, understanding mostly EU regulations, but also US regulations that are still in their infancy when it comes to AI. But really when it comes to privacy and data, those are pretty well established across the board. It’s been kind of a combination of what I learned at Eventbrite, because I went to Eventbrite when GDPR was going into effect. And so that was an eyes-wide-open moment of getting in the weeds with negotiating data processing agreements, understanding data transfers and cross-border data transfers and the like. So it’s been kind of an evolution as the laws and regulations have evolved. So has my career, so has my own understanding, so have the platforms’ responses to those laws and regulations. And I’m sure that probably resonates with a lot of your listeners who have also been growing their practice and their understanding as the laws and regulations in this realm have been evolving too.

Ken Suzan: Yes, indeed. Now let’s switch gears and talk about AI. You advise on AI and data daily. As platforms integrate generative AI tools into their tech stacks, what are the most critical best practices in-house counsel should be adopting right now to embed responsible AI principles into product development?

Franklin Graves: So as an attorney, one of my key roles is to understand the technology. Even representing creators and working for creator platforms, that’s something I’m constantly trying to do: put myself in the shoes of being a creator. And I think I talked about this last time I was on, but I come from a background where I was working for a major label doing marketing, video editing, social media work. And I was creating content. I understood the whole life cycle from the inception point of an idea to execution and then to the final delivery and distribution of that content to an audience within a major music label. And so part of that is the same thing that I think attorneys, especially in-house, should be doing: using the tools that the product and engineering teams are either developing in-house or partnering with third parties to develop, or a combination of the two. Using them, understanding them, using them as a creator would, using them as an end user or a client or customer would. And making sure that if you understand the product and understand the nuances of how it operates, and being a part of the iterations of that internally before it fully ramps, that really gives you a chance to understand: okay, we have a lot of responsible AI principles and standards and protocols that are in existence right now, whether it’s NIST, whether it’s based on the EU AI Act or anything and everything in between. It’s understanding how to apply those and bring those into a product and an engineering environment in a way that is practical and actionable for the people that you’re supporting, the stakeholders you’re supporting. So I think one of the critical best practices is, number one, understand the product or features that you’re supporting.

Franklin Graves: And then understand how you as an attorney can use your expertise and understanding of responsible AI practices, whether it’s a regulatory standard or an industry-adopted standard or a hybrid of the two, to leverage those and implement those, break those down and make them into actionable controls and processes and flows that work within your existing infrastructure. That’s a lot of high-level talk, but that’s the general idea. One concrete example we talk about frequently is with open source AI. If you’re working with a product team or an engineering team that is taking an off-the-shelf open source model and bringing that in-house, a lot of times companies have pre-existing open source processes that cover the use of open source software or code. Piggyback on that. That’s the easiest quick win for attorneys: leveraging your existing open source processes to just build on top of that the AI flavor and layering. It’s not very much that you have to do, but the underlying process of the key stakeholders that need to be involved in the review, whether it’s security, whether it’s executive sign-off if it gets to that point, even export control considerations should already be part of your existing open source software process. So layering in on those existing processes the specifics of generative AI or large language models that you’re trying to bring in is a great way to put this into practice.

Ken Suzan: Now looking at the geopolitical landscape that we currently have, we have the EU AI Act setting strict standards and shifting US executive orders. How should platforms and brands prepare for this fragmented regulatory environment when deploying AI tools to a global user base?

Franklin Graves: It’s a great question. It’s something that is still evolving, I think is fair to say. I would equate it, as I do in the paper that I wrote, to how creators and arguably brands don’t own the platforms that they’re building their communities on. That spawned this concept of de-platforming or going into building your own platform, a decentralized platform of sorts, and owning your community. That gives you that control and takes away the level of instability that can come for creators trying to build a business on a platform they don’t own, they don’t control when certain updates happen, when algorithms change, when tools and functionalities either become available or go away completely. So it’s very similar to what we’ve been experiencing in a regulatory environment where we have geopolitical complexities, for lack of a better term, that can overnight seemingly disrupt the way in which a platform or even a multinational brand is able to connect and reach an audience or continue to leverage the user base that they’ve built. I think TikTok is a great example of that, where it became a national security concern and suddenly it was facing an executive order that required it to be effectively disabled in the US or completely owned and operated by a US entity. All the mechanics and technicalities of whether it’s actually possible and still have a global platform with a global user base is a whole different discussion. But that’s an example of very similar considerations that are now not just a discussion point at the creator level or the individual brand level, but also in a much broader context at a platform level as well.

Ken Suzan: Franklin, let’s now shift gears and talk about your article. In your recently published journal article, Upload Complete, which we will have linked in our show notes, you advocate for a shift in terminology from internet creator law, a term used during our first podcast almost a decade ago, to creator economy law. Why is this distinction important and how does it change the way legal practitioners should view the ecosystem of creators, brands, and platforms?

Franklin Graves: Oh yes, this is part of the reason why I wanted to write the article: to lay this foundation of understanding. Because at the time I’d written the article, the term creator economy and creator had really not appeared but for maybe once in an actual court decision. And it was kind of focused on influencers and this concept, and it was just not getting it right. And so it was also, as you mentioned, when we first spoke I was even using the term internet creators. And I think that was something that was common at the time. The “internet” portion as a qualifier has since dropped off. And now for purposes of the creator economy, the term creators refers to individuals, it can be small businesses, which is what we’ve seen from a regulatory standpoint, how these small businesses are being impacted by regulations. But essentially creators in the article I pin in the context of intent. What is the intent behind the person or the small business that is posting content, trying to build a community and form a community in a virtual environment? And then that can even spill over into real physical world environments. And so the intent is kind of what I look at.

Franklin Graves: And I have a chart in the article that has a diagram showcasing the overlap of what I refer to as “users generating content.” It’s a play on the concept of user-generated content, UGC. Users generating content is that large bucket of anyone posting on a platform of some kind. And within that large bucket, that large circle, are smaller subsets. You have creators, you have brands. Those are really the two buckets you can put people into. Otherwise it’s like your grandmother or your parents posting content on Facebook or Instagram, and those are everyday users of a platform. The distinction to get into that subcategory of being a creator more so has been analyzing the intent behind the posting. Are you posting content to build an audience, to build a community, to eventually have a chance to monetize the following that you’re bringing in or sell services or something like that? Brands are posting for that reason. Creators are maybe posting for that same reason. But even within the creator category, there’s a subcategory of influencers that are trying to sell something, that are trying to build more than just an awareness of who they are, their influence. They are trying to do brand deals, partnership deals, upsells and all that, and start an actual small business aside from just the content itself that they’re creating. So that’s kind of the distinctions that I make in the paper. And that’s why it’s important to understand and lay that foundation, that anyone can post content online, but the intent, the why behind their posting that content, really does ultimately matter, especially when you’re looking at it from a court case or from a regulatory standpoint.

Ken Suzan: Now, Franklin, we’re seeing unprecedented geopolitical activity around platform ownership. For example, the US legislation targeting TikTok and Brazil’s recent temporary ban of X. How do these macro-level battles impact the day-to-day livelihood of creators? And how can they legally and operationally protect themselves?

Franklin Graves: So the shift that we’re seeing, and I alluded to this earlier in our conversation, is this concept of Web 3. And that term may or may not be really popular anymore, but that’s essentially what we’re looking at: a shift into a federated, decentralized operation of a platform. So instead of one owner, one company, one entity owning and operating the platform, it’s decentralized. Anyone can start up a server, and it’s interoperable, meaning anyone can plug and play and connect to that larger network. And it creates this unified social network experience. Within each operating node of that network, there can be your own decisions around content moderation, your own decisions around the hosting providers you use, where you’re operating out of, the terms and conditions that apply to that. But the flip side is that instead of creators posting and sharing in a closed environment run and controlled by a singular entity, you’re now experiencing a peer-to-peer type operation where your experience can change based on which server, which node, which user you’re engaging with. You might have content that’s acceptable in one area but not acceptable in another, and maybe it just doesn’t even show up in that other area.

Franklin Graves: But from a liability standpoint, as creators start to build their own networks and communities, even outside of a concept like the fediverse, it’s even down to creators building their own communities through online courses, subscription membership-based platforms that they run on their own website. There’s open source software out there, even something called Ghost, where you have memberships. And that is a creator or a small business in the creator economy that is now taking on the obligations that would typically fall upon a platform. They need to take into consideration terms and conditions, privacy policies, legal aspects, and regulatory considerations for running a platform, especially in a global world. So it’s a lot of liability that then shifts over to those small businesses and even brands sometimes that are doing the same thing. Whether it is something as simple or complex as content moderation or all the way up to monetizing an audience, this new world where creators can spin up and run a platform all dovetails back to the concept of creators not feeling like they have control in reaching the audience and the community that they’re building on an individual platform. And so this really became more mainstream conversation with TikTok and the issues around it potentially being shut down in the US. That was kind of the mindset shift and eyes opening for many creators, especially within the influencer subset, of realizing: we need to make sure that we have a way to reach the audience we’ve built if the individual platform that we’ve committed to over the last year or three years or so is no longer available. We need a way to continue that relationship outside of that one platform controlling it.

Ken Suzan: Franklin, we have a few minutes left and a number of topics. So I’m going to switch gears and talk about a few issues. First, a major emerging topic in your paper is the evolution of protecting kids online. With state-level age-gating laws like the CAADCA and the recent FTC updates to COPPA, how should platforms navigate the significant tension between strict age verification mandates and the privacy and First Amendment rights of their users?

Franklin Graves: Man, that is a whole discussion to unravel. It is a consideration that we’re seeing happen again, going back to the geopolitical nature of everything. Countries like Australia and certain countries in Europe and now even individual states in the US are trying to look at ways, and some of them have already put into place minimum age requirements before you can even sign up for an account with a social media platform. One of the things I’d just highlight quickly here is that one of the tensions is around how you verify someone’s age online and still maintain the ability to be at least pseudonymous. How do you still have a level of privacy, autonomy, and protection when it comes to having to provide something like a driver’s license or have parental consent tied and connected to an account managed by a parent in a situation where maybe it’s not appropriate or not beneficial to the child in that manner? But then maybe there are counterbalancing factors that outweigh that. All of that comes down to the technicalities of how it’s actually implemented and maintaining the sense of openness and freedom that we’ve had on the internet to date. And then the other element there is, since a lot of the internet that we think of today is more so through mobile applications, is it something that the mobile operating system providers and app store providers should be thinking about? So whether that’s the Google Play Store or the Apple App Store, where does that initial age verification need to fall? Is it at the platform level? Is it the app store or mobile device management level or something else? Yeah, there’s a lot to discuss there. And a lot of the issues we’re seeing with how the internet is changing in terms of being able to browse a website without disclosing personal information that might not have been required before is largely stemming from a focus on protecting children online.

Ken Suzan: It sounds like, Franklin, we could have another episode covering lots of issues connected with that one topic alone.

Franklin Graves: I would absolutely agree with that. There’s a lot going on there. And again, it’s different across the world. And so I know you all have a global listener base. And so there’s a lot of nuances to that whole discussion too, that are worth exploring.

Ken Suzan: Last question for today’s episode is regarding the right of publicity. With the explosion of AI-generated synthetic media, digital replicas, and voice cloning, the right of publicity is taking center stage. What are the biggest legal risks for brands partnering with influencers right now? And how can creators protect their most valuable asset, their likeness?

Franklin Graves: That’s a great question. I think we’re seeing kind of a throwing-spaghetti-against-the-wall-to-see-what-sticks approach right now by a lot of different parties, whether it’s trademark attorneys, whether it’s general entertainment attorneys or whoever. For example, we’ve seen Taylor Swift filing trademarks to protect certain sounds of her voice and phrasing that she uses. It’s a difficult area because in the realm of generative AI with deep fakes and virtual avatars, that is where it gets tricky, because traditional IP laws are just not able to fully cover that spectrum. It’s a piecemeal approach, but even then it doesn’t fully cover it. So for example, I’m based in Tennessee and a couple of years ago we had the Elvis Act that updated our right of publicity law to add voice and to explicitly reference artificial intelligence. And so that’s the kind of effort we’re probably going to continue to see: efforts to develop some framework around protecting what is essentially a privacy right, in a manner that doesn’t restrict generative AI systems from continuing to develop and operate the way they’re operating now, while layering in those protections so that in the US at least a First Amendment right doesn’t necessarily get squashed, and those traditional well-recognized efforts to not overregulate a technology in its early stages are respected.

Franklin Graves: And so I think a lot of what we’re seeing is just a need to update laws. The SAG-AFTRA debate and the strikes that happened around maintaining control of your performance and any iterations of that, or building upon that by a media company that might come later, it’s all on the table right now and still being discussed, still being worked out. I think in the short run, a lot of times if it’s in a brand deal, the key question is: if you are using generative AI to enhance in some way the final deliverable for the campaign, who has control over that? Who has final say and sign-off on how that likeness or that digital replica or that person’s voice is represented? And even outside of the brand space, we’ve seen actors like James Earl Jones signing over certain aspects like their voice and allowing it to continue to be used in these manners powered by generative AI as Darth Vader. And I think I saw something that Boy George was even starting up an AI company that allows musicians, the original recording artist, to rerecord new versions of their masters so that they don’t miss out on that revenue. It’s powered by generative AI, by taking their voice now, which is significantly different than it was back in the 80s, and using generative AI to make it sound closer to the original, but all based on their current performance. So I think it’s still an evolving area. And what’s interesting too is on the platform side, we’re seeing the early stages of platforms like Google starting to acknowledge and rely on the license grant contained in their terms of service for YouTube, which grants them broad rights to use the content to run their platform. So all that to be said, it’s still early stages. I’m very interested to see where we go from here in the future, especially from a global perspective as well.

Ken Suzan: Franklin, I could spend hours talking to you about this. You’re such a knowledgeable person on these topics. Maybe in a few years, will we connect again and talk further on AI and all the things that are yet to be developed?

Franklin Graves: Thank you. Yeah, it doesn’t have to be another decade. Maybe we can cut it to half a decade, given the pace at which technology is going now.

Ken Suzan: Sounds good, Franklin. Thanks again for being on the IP Fridays podcast.

[powerpresss]

My co-host Ken Suzan and I are welcoming you to episode 175 of our podcast IP Fridays! Today’s interview guest is Bruce Dearling, patent attorney and partner at Hepworth Browne in the UK, and we talk about how non-technical features must be considered when assessing inventive step of patents at least according to recent decisions of the UK supreme court and the Unified Patent Court.

Profile of Bruce Dearling

UK Supreme Court Emotional Perception AI Limited

UPC Abbot vs Sinocare

But before we jump into this interesting interview, I have news for you:

On May 20, 2026, the Swiss Federal Council adopted the fully revised Patent Ordinance, which will enter into force on January 1, 2027, together with the revised Patent Act. In the future, the Swiss Federal Institute of Intellectual Property will prepare a mandatory search report for each application; applicants can choose between a partially examined version and a full examination that assesses novelty and inventive step. The full examination costs an additional 300 Swiss francs, and renewal fees will increase by a total of eight percent over the 20-year term.

On May 19, 2026, Asus entered into a licensing agreement with the Wi-Fi multimode patent pool managed by Sisvel, thereby ending all ongoing infringement proceedings. Sisvel bundles standard-essential patents in the pool from, among others, Atlantia, ETRI, and Mitsubishi Electric.

On May 18, 2026, the UPC Local Chamber in Düsseldorf rejected Align Technology’s application for a preliminary injunction against its Chinese competitor Angelalign. Angelalign may continue to sell its clear aligners within the UPC jurisdiction. Our partners Dirk Schulz, Ulrich Storz, and Wanze Zhang, together with Arnold Ruess, successfully represented Angelalign.

The U.S. Patent and Trademark Office (USPTO) announced midweek that, since October of last year, it has invalidated or is seeking to invalidate approximately 10,500 trademark applications and registrations in eleven administrative orders. Reasons include forged attorney signatures and the fabrication of non-existent filing requirements. This stems from ongoing abuse of the U.S. trademark system, primarily by non-U.S. applicants, which can lead to conflicts with validly registered trademarks for legitimate businesses.

On May 12, 2026, the British Court of Appeal overturned a lower court decision that would have required Nokia to grant interim licenses for video coding patents. The court found that Nokia’s license offer to the Taiwanese manufacturers Acer and Asus had already been made on RAND terms.

In May, the U.S. Department of Justice (DOJ) filed a brief in the ongoing Corteva v. Inari litigation, expressing antitrust concerns regarding certain patent practices in the field of plant breeding. This marks the first time the agency has actively intervened in a biopharmaceutical patent dispute with implications for seed innovations.

Episode 175 of the IP Fridays podcast was a conversation I will not forget quickly. My guest Bruce Dearling, partner at Hepworth Brown in the UK and a patent attorney for 36 years, took a case through every level of the British court system up to the Supreme Court and, in doing so, fundamentally changed patent law for AI inventions in the UK. The case is called Emotional Perception, and its effects reach well beyond British borders.

Below I summarize the key points from our conversation. The full episode is available at IP Fridays.

A. What Is the Emotional Perception Case About?

The underlying invention concerns artificial neural networks. Specifically, it relates to a method of closing what is called the semantic gap at the output of a neural network. That sounds abstract, but the idea is straightforward: a neural network always produces an output that does not fully correspond to what a human would actually expect or feel. Closing that gap brings the system closer to human perception and human expectations.

Bruce Dearling drafted this application himself and filed it at the UK Intellectual Property Office (UKIPO). The Office rejected it as excluded subject matter, characterizing it as essentially a computer program as such. The legal basis for that rejection was the Aerotel decision from 2006.

The case then went to the High Court, which found in favor of the applicant. The Court of Appeal reversed that decision. Then the UK Supreme Court stepped in and changed everything.

B. The Aerotel Test and Its Flaws

Since 2006, the Aerotel test had been the standard British method for assessing whether an invention falls within the excluded categories under patent law. It was a four-step approach: construe the claim, identify the actual contribution the invention makes to human knowledge, ask whether that contribution falls solely within excluded subject matter, and finally check whether the contribution is technical in nature.

The problem Dearling described in our conversation is that Aerotel reverses the logical order of the analysis. You start with the contribution and only then ask about the exclusions under Article 52 EPC. The UK Supreme Court described Aerotel in its judgment as “unsound law” and overturned it. The EPO’s Technical Boards of Appeal had previously called Aerotel “disingenuous,” which at the time led to a public dispute between the British courts and the Boards. With the Emotional Perception ruling, that conflict has now been resolved in favor of harmonization with the EPO.

C. What the UK Supreme Court Decided

The Supreme Court made two central findings. First, the exclusion of computer programs “as such” is overcome as soon as a claim includes any piece of hardware. It does not matter whether that is a processor, a memory module, or any other component. The threshold is deliberately low. Dearling described this as the “any hardware” approach, which aligns fully with the EPO’s position following G1/19.

Second, and in Dearling’s assessment the more important finding: when assessing inventive step, the invention must be considered as a whole. The Court introduced what it called an “intermediate step,” an analytical stage in which the interactions between all features of a claim are examined before the question of inventive step is addressed. Non-technical features cannot simply be struck out if they contribute to the overall technical effect of the invention.

D. Inventive Step: The Intermediate Step

This is the heart of the judgment. In EPO practice, Dearling said, it happens regularly that examiners strike through features they consider non-technical and thereby fail to assess the invention’s inventive step correctly. A recent Technical Board of Appeal decision, T 1249/22, already criticized this approach: a claim directed at a technical solution to a problem can be patentable even if the underlying problem is non-technical in nature.

Dearling recalled a remark made by a Board of Appeal member at a hearing he attended years ago: “We understand that examining divisions can operate with a degree of mental laziness and that it’s too easy to throw too many things out of the basket when considering the issues of inventive step.” That quote stayed with him because it names a structural problem that the intermediate step now addresses directly.

The British method for assessing inventive step is the Pozzoli test, which differs from the EPO’s problem-solution approach. The Supreme Court explicitly retained Pozzoli because the problem-solution approach, in its view, is structurally infected with hindsight reasoning: you already know the invention, you work backwards to formulate an objective technical problem, and then you ask whether it would have been obvious for the skilled person to arrive at precisely that solution. Dearling sees this as a source of unfairness toward genuine inventions.

E. Alignment with the Unified Patent Court

In April 2025, the Court of Appeal of the Unified Patent Court issued a decision in Abbott v. Sinocare (APP_000000901/2025, judgment of 17 April 2025). Dearling pointed out that this decision uses language and reasoning strikingly similar to the UK Supreme Court’s Emotional Perception ruling of February 2025.

That is significant because the UPC is bound neither by UK courts nor by the EPO. The overlap suggests voluntary convergence. Dearling reported a conversation with a person close to the EPO, whom he did not name, who used the word “permissive” to describe the UK Supreme Court’s approach and indicated that the EPO might move toward it. Whether and how quickly that happens remains to be seen. What is clear is that the UPC, as the new European patent court, is setting its own standards, and the question of how to handle non-technical features in inventive step assessment is now being asked at multiple levels simultaneously.

F. Implications for the EPO and Practice

The EPO is not directly bound by the ruling. It is an administrative body, not a court. Dearling is nonetheless optimistic that change is coming. On one hand, external pressure is building: when the UK Supreme Court and the UPC articulate similar principles, convergence becomes hard to resist. On the other hand, Article 27.1 TRIPS requires all contracting states to make patents available in all fields of technology. Examiners routinely striking non-technical features from AI claims and rejecting them on that basis sits uncomfortably with that obligation.

For the underlying application in the Emotional Perception case, the ruling has a pointed consequence. The Supreme Court did not grant the patent itself; it referred the matter back to the UKIPO for reconsideration under the intermediate step. The Office’s subsequent response was, in Dearling’s words, unconvincing. He suspects the Office is attempting to reintroduce the Aerotel test through the back door. As a last resort, he has not excluded a judicial review, a procedure that does not simply challenge the substantive decision but holds the Comptroller General of Patents to account for whether the Office is deliberately circumventing the Supreme Court’s direction on the intermediate step. That is, as Dearling put it, “a nuclear option,” but one he would not rule out if the evidence in the file already suggests the Office is in contempt of court.

There is also an international dimension. Singapore’s Intellectual Property Office launched a public consultation shortly after the ruling, asking whether Singapore should adopt the Emotional Perception approach into national law. That is British soft power operating in real time within the Commonwealth.

G. Three Takeaways for Patent Practitioners

At the end of our conversation I asked Bruce Dearling to distill the most important practical points. His first takeaway: make sure the claim contains hardware. This applies not only to UK and European applications but is simply good drafting hygiene. Without hardware in the claim, the application remains exposed.

The second takeaway concerns the description. Anyone filing an AI invention needs to explain clearly which function is achieved by which piece of hardware, circuit, or software. Not as boilerplate, but as a complete technical account that describes the real-world effects. Dearling’s experience is that practitioners who write the claim first and fill in the description afterward run into trouble.

The third takeaway emerged from the conversation itself: how the EPO assesses inventive step for AI inventions is not a settled question. It is worth following the development of UPC case law and any shifts in EPO practice closely. Anyone advising on AI patent applications today needs to know these arguments.

H. Conclusion

The UK Supreme Court’s Emotional Perception ruling is not a British footnote. It has declared the Aerotel test dead, introduced the intermediate step that brings non-technical features back into the inventive step analysis, and set off a convergence movement that is already visible at the UPC and still pending at the EPO. For everyone working in AI patent practice, whether in prosecution, examination, or counseling, this ruling is required reading.

Rolf Claessen: Our interview guest on IP Fridays podcast is Bruce Dearling. He has been in the IP field and a patent attorney for 36 years and is partner at Hepworth Brown in the UK. Thank you very much for being on the podcast.

Bruce Dearling: My pleasure, Rolf. Thank you for inviting me.

Rolf Claessen: All right. We just met at the INTA annual meeting in London. And you talked about the UK Supreme Court case where you were involved. And the core questions were whether non-technical features would be considered when assessing inventive step of patents. Can you briefly summarize this case?

Bruce Dearling: It’s a bit more than that. It started — I actually wrote the case. And I prosecuted it through the patent office. The patent office rejected the case for being excluded subject matter. So pretty much the excluded subject matter provisions in the UK are nearly identical. They’re as near as practical to the language of the EPC, so those of the European Patent Office — Article 52.2. But again, they apply as such.

The actual technology relates to artificial neural networks. And the invention related to a very clever way of what is termed closing the semantic gap at the output of the neural network. So that means that in a neural network, there is always a discrepancy between the output of the neural network in terms of what it’s telling you you should be thinking essentially, and what reality is. So if you can close the semantic gap, then you align the neural network or the artificial intelligence system to better reflect human knowledge or human reactions and human expectations. So that’s really what the invention is about. There’s no point in going into too much detail with it — that’s the way it is. It’s very clever.

So the UKIPO rejected this because they said it was essentially a computer program excluded from patentability as such. And they used a decision which is called Aerotel, which has been around since 2006. And that decision has caused considerable consternation and tension between the EPO Technical Boards of Appeal and the UK courts. Aerotel was described as being essentially disingenuous by the EPO Technical Board of Appeal. And the UK courts pushed back and said, you don’t know what you’re talking about. So that’s where it fell apart.

So that’s where they rejected it for essentially being a computer program as such, possibly with a bit of business methods thrown in as well. But let’s leave that for the time being. So the case then went to the High Court and at the High Court, we won. The judge said, actually, it’s not a computer program. Neural networks aren’t computers. They’re not programs themselves. There’s more to them than that. And the invention as claimed is not excluded from patentability as such.

The UKIPO obviously weren’t very happy about that because they liked their Aerotel case and so they appealed it. And they appealed it on several grounds, including a new one, which was that it was a mathematical method. The Court of Appeal decided that the UKIPO was right and that we were wrong, so we lost the case.

So we then went to the Supreme Court. Well, actually, they denied us an ability to go to the Supreme Court. The court said no appeal. We went — actually, no, I think there is a bigger issue here — because we realized, or I realized at that point, that the work that we were doing was much broader than this. It requires real consideration of what an invention is at a fundamental level. So not only exclusions, but how inventive step is applied. And these issues were built into the case from the very beginning.

And they sort of — I wouldn’t say crept up on the court as we went through — but they became more and more prominent to the extent that ultimately, when we made an application to the Supreme Court, the Supreme Court went, yeah, we’ve got some issues here. We want to hear the full arguments on why this is not excluded from patentability, why Aerotel is potentially bad and how we more or less try to align ourselves with the European Patent Office. So that’s essentially what happened. And the Supreme Court hearing was last July. It took them the thick end of eight months to come out with a decision, which was issued in early February, at which point the entire legal landscape in the UK changed because they said we were right. The Patent Office doesn’t know what they’re talking about.

Aerotel is bad. It’s unsound. That’s what they described it as — unsound law. It needs to be removed and we’re going to harmonize with the European Patent Office.

So before I — I’m just going on a bit of a rant here, standing on my soapbox telling you what you already know. But the Aerotel test essentially was — it was a four-step test, past tense. So you firstly had to construe the claim. That’s pretty straightforward. Then you actually had to identify the actual contribution. This is what they said — identify the contribution. Really in this aspect, you’re asking what, as a matter of substance rather than form, the inventor has added to human knowledge. So that’s what they said the contribution was. And then they said, the next step in Aerotel was to ask, well, does that contribution fall solely within the excluded subject matter field or realm? And then they said, well, if you get through that question, then you check the actual contribution or the alleged contribution to see whether it’s technical in nature.

So that’s the Aerotel test as it was. And what the Supreme Court in their unanimous final decision said was that Aerotel at best jumbles up the order. It reverses the logical order of the analysis by starting with the contributions and then addressing the Article 52 exclusions. And then finally it goes back to what the technical nature of the invention is about. So they really went, no, we don’t like any of this stuff. It’s bad, it’s stupid, it puts the cart before the horse.

So, in the intervening period between finding the case and actually seeing it progress all the way to the Supreme Court, we obviously had the G1/19 decision from the EPO Enlarged Board. And they basically said that they are going to validate any hardware as the approach. And that’s essentially what the UK also went with. The UK Supreme Court said we’re going to say that the threshold of patentability — or the exclusion to patentability — is simply overcome by the inclusion in a claim of any piece of hardware, whether it’s a processor or a piece of memory or whatever. It doesn’t matter. Any hardware makes the invention a technical invention. So it’s a really low threshold to consider.

And they then went, well, actually, if we now align and harmonize with the European Patent Office sensibly, then we need to look at how we assess inventive step, which is the other thing that we raised with the Supreme Court. In fact, we probably raised it at other times and in all the other instances as well, but it came to a head at the Supreme Court. So the Supreme Court then also went a bit further and said, well, actually, whilst we do like the global approach to assessing inventive step for all fields of technology — whether it’s chemistry or biotech or electronics or software or AI — we use a test called Pozzoli. So that isn’t problem-solution. We don’t like problem-solution. We think it’s not codified in the European Patent Office. It’s just a mechanism that the EPO has come up with to try to objectively assess inventive step. We don’t particularly think that’s appropriate. We like our approach called Pozzoli.

That’s it. So we’re going to say with Pozzoli, however, in order to actually understand — particularly in the context of mixed inventions having technical and non-technical features — it’s necessary for the examiner to undertake the so-called intermediate step, where you have to look at the interactions between features within a claim. The invention is defined by the claim. That’s what the act says. That’s what everyone understands. It’s the invention defined by the claim. So you look at the claim features and then you have to understand the interactions that take place. And even if they are between technical and non-technical features, if they bring about an overall technical effect when you consider the invention as a whole, then your claim should be good and you can assess it for classical inventive step.

So that’s really where we’re at. There’s a lot to unpack there already. It’s probably a podcast in its own right, but that’s the positive history of where we’re at. And I can keep going if you wish me to for a second and talk about why I think this is — we’ll just contrast it quickly with the problem-solution approach at the EPO and COMVIK. So for inventions in the computer-implemented field, they use COMVIK and the problem-solution approach.

The Supreme Court said, as I said, they don’t like problem-solution. I think the problem-solution issue is that it is also inherently pre-baked with hindsight because you have to look at the invention and then step back and exclude those features which are common. And then you formulate a problem based on the function that the claim achieves. And then you’re asking whether or not it would be obvious for a skilled person to arrive at the claimed invention, having been given that hindsight-developed problem. So COMVIK is not great by any means.

And we know from a practical perspective that examiners are only too willing to look at a claim and simply line through features which they believe are non-technical, whereas they don’t actually look at the interaction of those features in the context of the claim as a whole.

There is also a decision — very recent one actually, about a year ago — T 1249/22, where the Technical Board of Appeal told the examiners and the examining division, you cannot do this. It’s okay to have a claim directed towards an invention in a non-technical field, as long as the invention is directed to a technical solution of that problem. I think it’s paragraphs 11 and 12 or 10 of that decision that are worth looking at. But they’re saying that in all fields of technology, it doesn’t matter as long as the technical solution is about technology — therefore, you should be able to obtain a patent as long as there is a realistic and appropriate technical effect. Be careful actually, Bruce — I don’t mean technical contribution, I mean technical effect. There’s a reason for that distinction.

Rolf Claessen: The non-technical features are nevertheless used to assess inventive step in the UK now after this decision, right?

Bruce Dearling: Yes, that is the intermediate step. The decision says you must look at the invention as a whole. It’s the important thing. There are a couple of issues that arise out of this. The first one is that you have to provide context for the invention.

The Supreme Court never provided any specific guidance about how we deal with the intermediate step or what the exact test is, which is in some respects fine. It seems to be fairly clear that you just have to engage your gray matter — your neurons — to work out what is going on in the real world. And once you work out what’s going on in the real world, what the benefits are, then you look at whether or not the actual implementation of the invention fundamentally has a technical flavor to it, which is not just coding, not just simple coding, but it does something smarter. There’s a real technical impetus. There’s a technical effect.

Now that actually brings me onto something I’ve postulated or said. I think the intermediate step will follow something like what I’ve termed the holistic character test, which essentially is: work out what’s going on in the real world. Then once you’ve worked out what’s actually being achieved, what the benefits are, what the invention’s concerned with, then you ask the question, how am I achieving it technically? And how is there a technical effect? How does the technical effect arise?

That brings out a couple of issues. The first one is that it’s actually about the word “contribution” because it depends on how the word is used. So if you look at head note one in COMVIK, it uses the word “contribute” — how the non-technical feature contributes to the invention. So that’s an additive inclusive concept. The UK IPO historically, and arguably at the moment today whilst they’re trying to retrain their 400 examiners — which this has caused them to have to do — their idea of contribution is this backward-looking concept.

So technical contribution and technical effect, I think — although we mix them up and interchange them — are distinct. Technical contribution: you’re looking backwards. Technical effect is what you look at when you look forward into what’s going on. So this is subtle — it’s really subtle, but it’s important. And once you realize that you are actually looking for the technical effects, then you’re on much safer ground. It’s much more objective in terms of the assessment. This might be somewhat contentious, because it’s the way I’m looking at this, but I’ve been working on this a long, long time and thinking about it for probably decades, worryingly so. So technical contribution and technical effects are probably not the same, where they are interchangeably used to mean the same thing within existing decisions.

Rolf Claessen: And in the beginning you said, now that Aerotel is dead basically, it’s more harmonized with the EPO’s approach. But what I take from the discussion now is that maybe — especially in view of the problem-solution approach — it’s not fully harmonized with the EPO’s approach at the moment, right? Or did the UK Supreme Court get something wrong, or was that a desired outcome from your point of view that this is not so completely harmonized with the EPO?

Bruce Dearling: Well, the EPO — the any-hardware solution is fully harmonized, no doubt. So it’s now a question of inventive step under Article 56 or Section 3 of the Act. The EPC nowhere mandates the use of problem-solution. And we know that there are many different ways of actually assessing inventive step, including the concrete elaboration test from last year and problem-of-invention approaches. So there are numerous ways of assessing inventive step. So the UK says, “Pozzoli — we like Pozzoli.” Interestingly, I had a discussion with someone I probably can’t mention. They’re saying that the UK approach may actually be more permissive now. It might even influence how the EPO operates. So they may move away from COMVIK towards more of a Pozzoli approach, which basically says this:

You identify the notion of the skilled person — step one. You identify the common general knowledge of that skilled person — step one B. You identify the inventive concept of the claim in question, where you construe it if you can’t work out what it is. You then identify what the differences are. And then you ask the question, is it obvious to the skilled person, given knowledge of the common general knowledge?

This is entirely not artificial because, as I said beforehand, when you look at problem-solution, you are formulating a problem by backtracking from what the claimed invention is to a situation where you say, well, these are the common features and I’m going to project a problem to try and solve. Now that is already tainted with hindsight reasoning. It’s not safe, it’s not thoroughly objective. There is an inherent problem with this which sees good inventions cast by the wayside. Although it’s a preferred mechanism, it’s not fully baked. There are situations where examiners are inherently lazy, or they just simply use something like the requirements specification argument, which is just factual. It just demonstrates that they can’t be bothered to actually argue it properly or think about what the invention is. Sorry to any examiners listening to this, but this is just my personal view, that sometimes there are problems.

I’m reminded of a quote from an EPI hearing I was at a long time ago, where the Legal Board of Appeal member said: “We understand that examining divisions can operate with a degree of mental laziness and that it’s too easy to throw too many things out of the basket when considering the issues of inventive step.” Now that one has stayed with me because you think — did someone just say that? And the answer is yes, they did. But it just goes to show that there is some tension between the TBA and the examining divisions, and they don’t always get it right.

Rolf Claessen: So there might be a small difference now between the UKIPO’s future approach of assessing inventive step and the EPO?

Bruce Dearling: Yeah, it might do. But the other interesting thing here — and thank you for pointing this out, I hadn’t entirely caught up with it, I’ve been traveling beforehand and I missed some of the UPC case law. So the UPC case law — in, was it — yeah, we talked about that.

Rolf Claessen: Yeah. There was a decision in April, Abbott versus Sinocare.

Bruce Dearling: Yeah, 901 of 2025. So a Court of Appeal decision from the UPC. It was APP_000000901, I believe, 2025. Decision 17th of April, hearing 27th of March.

The UPC is not bound by — it’s a court. The European Patent Office is not a court, it’s an agency that administers and looks after the administrative rule of law. So the fact that this decision came out from the UK Supreme Court in February, and you see almost identical language used in the UPC decision, suggests that there is some alignment here, or some convergence in thought. Now, whilst the UPC decision also references G1/19 and uses problem-solution, there is enough — you’ve got to bear in mind that high-level courts do look at each other’s decisions. And this is really a question of influence and the desire to converge. So the fact that they’ve done this at this time is quite interesting.

Again, I can’t quote someone directly from the EPO, although I would love to. They were saying — at a very high level — and they used the words “converge UPC practice towards UK Supreme Court practice on interpretation of the law.” So this may actually be happening in real time. Again, it would be wrong to actually refer to anyone by name, but it’s an observation that when I looked at the case, I can see why this is going ahead. And I can see why the judiciaries — they want to maintain independent judicial controls. They won’t reference the UK Supreme Court decision, not least because we’re not in the UPC. But if you look at the arguments in sections 106 and 107 of the UK Supreme Court’s Emotional Perception decision and head note one, you go — wow, this is very close.

Rolf Claessen: Very close and nearly identical wording. Yeah. And the UPC also now uses non-technical features for assessing inventive step. Is that a problem for the EPO that has historically been aggressive in throwing out non-technical features for inventive step analysis?

Bruce Dearling: Well, I think they really need to get to the situation — I don’t know — this holistic character test that I’m sort of proposing, where you really have to think about what the invention is achieving, and then look at how it’s technically being achieved. And then if you look at that again in the context of that other decision I mentioned — T 1249/22 — it says something like, in the case of an invention that amounts to a technical implementation of a non-technical method, provided the non-technical method does not contribute to the technical character of the invention. The board validated the approach of identifying the non-technical method and then goes through and says it’s patentable. There are decisions like this which suggest that examining divisions have to give it a bit more thought, because the Technical Board will realize that to satisfy the WTO requirements — which pretty much everyone is bound by — Article 27.1 TRIPS, which requires that you protect all fields of technology. And that means whether it’s data processing or business methods, because business methods can be patentable so long as they are implemented on a technical basis. That essentially seems to be what T 1249/22 is saying, although it doesn’t explicitly say “allowing business methods.” The exclusion is only “as such.” So does this decision, in combination with the Supreme Court case and the movement of the UPC, say: well, actually, let’s look at this properly? It requires objective assessments, not just superficial “let’s strike through that feature because I don’t like it, it looks non-technical.”

Rolf Claessen: So are you hopeful that the EPO is adjusting and will reshape their case law in view of the UPC decision and the UK Supreme Court decision?

Bruce Dearling: It’s a bit unfortunate that the corresponding UK case at the EPO was dropped by the applicants, because it was heading towards an examination hearing at the examining division. It would have gone to the TBA, and I’m sure it would then have gone from the TBA to the Enlarged Board. I’m pretty sure that’s the case. There is another case from the same client which will probably argue the same thing because the specs are almost identical. It’s just lagged in time. So is it going to change? I hope so, because I think the EPO have got it wrong — more often than not in this field. Well, maybe not more often than not — they get it wrong more times than they should do.

Would I like to see it changed? Yes, I would, because I want the examiners to actually think about the technology as opposed to just — oh, it’s not — I don’t want to engage the gray matter. That serves no one. That doesn’t serve technology. That doesn’t serve industry. These patent rights are there for a reason. They are property rights. I’m referring to the award of the 2025 Nobel Prize for Economics — they are a core driver for society’s development. So the 2025 Nobel Prize was for something called creative destruction — the replacement of old technology with new — and it’s based on the patent paradigm. So all this stuff is coming to a head now. It’s just a question of how quickly the EPO actually catch up, and maybe they have something to catch up on.

It’s just understanding that the examiners have to start to think. As I said, we’ve got the issues at the UKIPO where they’re going to have to retrain 400 examiners.

Rolf Claessen: Yeah, right.

Bruce Dearling: The Emotional Perception case wasn’t granted by the Supreme Court. They referred it back to the patent office for consideration under the intermediate step. So the patent office produced a response that I would describe as — I’d say arguably — not well reasoned, which I’ve filed the response to, which basically says you don’t really know what you’re talking about. What really worries me a bit is that I think they’re trying to introduce the Aerotel case through the back door. It’s backsliding. It’s a mechanism for trying to apply it in a different way or a different context, which would be wrong.

I think they believe that the applicant will appeal this if they get a bad decision — they will appeal it back to the courts again via the High Court, Court of Appeal, Supreme Court route. I say maybe not. I say maybe the client will file what they call a judicial review, which is a nuclear option. That’s when you actually hold the Comptroller General of Patents to account and get full discovery of whether or not there’s internal documentation showing that they are deliberately circumventing the direction of the Supreme Court on the intermediate step. This is basically holding them to account and saying: if you’re not applying the intermediate step appropriately, you are in contempt of the law. So judicial review is a really serious thing to do, but it’s certainly something I would not exclude from consideration.

We’ll see what happens. It’s not saying we’re just going to go through the courts and make them decide on this. We’re going to say you’re wrong. And there’s already enough evidence in the files to suggest that they are probably in contempt of court and they’re not applying the intermediate step appropriately. They may not know any better at the moment — they need to be guided — but the consequences for them are potentially severe.

Rolf Claessen: I have another question for you. You were the instructing attorney — do you think the decision was perfect? What argument that you made was the most underappreciated by the court? And where do you think the judgment got it wrong, or was it all perfect?

Bruce Dearling: No, it got 90% or 95% correct. The intermediate step is right. That’s the most important thing in the decision — it’s the intermediate step. The any-hardware thing — that’s logical, that makes some sense — but if people say “if the any-hardware rule is the important bit,” no it isn’t. It’s the intermediate step. That’s the important thing.

Where do they go wrong? I think they went wrong because — and you’ve got to bear in mind that unlike German courts, I’ve got to be careful about how I express this — generally, as I understand it, and correct me if I’m wrong, but the judiciary in Germany on patent cases are generally more technically able. They’re normally technically qualified.

I look at the Supreme Court justices and the Court of Appeal justices — we had one who was a humanities undergrad, one was a chemist. Good luck with trying to argue complex artificial neural network technologies, which are difficult even for me to understand. And I’ve been working in the field. They’re hard to understand. They require real understanding, real appreciation. They could say, well, actually we don’t need to look at the technology — but frankly, if you’re looking at the statutes and exclusions to patentability and asking what a computer program is, then you need to understand what these technical terms really are. And if you can’t, then the judgment is potentially flawed. Their finding that the neural network is a computer program is, I think, technically obtuse.

You know that the Singaporean government — the Intellectual Property Office of Singapore — released about six weeks ago a consultation note to the Singaporean profession and population, asking: is the Emotional Perception case right, and do we need to adopt it into Singaporean national law? So this is direct soft power from the UK Supreme Court changing Commonwealth legislation and statutes. We’ll see what happens. But from what I’ve seen of a draft response from the attorneys, they’re saying essentially: we agree any hardware is right, the intermediate step is right. The assessment of the neural network as a computer program is wrong, or it just doesn’t make any sense. And I’ve made the same comments before in SIPA, in the relevant round in March.

There’s a disconnect. I mean, it’s like they equate a computer program with being able to be run on an analog computer. Now, an analog computer has no central processing unit. An analog computer just has resistors and transistors and capacitors. So if they’re saying that an analog computer can run a program — that’s essentially what they’re saying in part of the judgment. Where is the program in an analog computer? And if they’re saying it’s in the values of the resistors and the capacitors, then that has implications for any circuit we’ve got — it’s potentially a computer program — which is just madness, because it doesn’t sit well with the legislation and decisions we’ve looked at over the last 50 years.

This is a real problem. It may be a storm in a teacup because you can overcome the objections by having any hardware, but it’s an argument they shouldn’t have been making. It seems to be abstract legal argumentation which has little credibility in my personal view, although it’s now law. It may be that someone can take that, have an argument with the Supreme Court, get them to fix this. The other thing is the EPO looks at a neural network as a mathematical method, and the UK now says it’s a computer program. Neither is right.

The EPO is wrong as well. If you look at the actual decision which they regularly quote — the Vicom case — if you actually read the claim and look at the case, you see that it doesn’t make a huge amount of sense. A neural network has applied mathematics in it. It can be based on a computer program because it’s required to set up the learning objectives and the loss function. Mathematical processes — it tweaks the weighting factors of neurons over the course of the training epochs. But at the end of the day, if the function performed by the neural network is new and it’s directed towards a technical implementation which is technically relevant, then it shouldn’t fail for being a mathematical method.

And I think the EPO guidelines actually say that. Even recommendations — the UK court said that a recommendation is not technical. Well, actually it is, because it’s data processing, and you’ve got to work out how does the data processing work to provide an improved recommendation? Again, it goes back to the T 1249/22 decision. There’s a whole raft of these things which are left not entirely resolved. There’s enough here to keep someone busy for a few more years.

Rolf Claessen: Right. So I have a question for you now that we’ve talked about the decision of the UK Supreme Court and the UPC — the Unified Patent Court — with very, very similar wording. What do you say are the three most important takeaways for patent practitioners in the US, in Europe, in the UK, before the EPO? Are there any things that you really want patent practitioners to take away from our discussion here?

Bruce Dearling: Yeah, okay. So first: make sure the claim has some structure in it. You need to have any hardware. That’s number one — in terms of claim drafting.

In terms of the description, you really have to understand what the invention is about. And you’ve got to make sure that you explain what function is achieved by what piece of hardware, kit or software. And if you do that — don’t nickel-and-dime this by writing the claim first — I would suggest that you run into problems. You need to understand what the invention is about. And you need to make sure that the description is complete and full to describe the functionality and the effects that are achieved in the real world. And if you can do that, then you’re on a much sounder basis — much, much stronger. There’s a much stronger foundation for this. So that’s two things. Is there a third one? That’s me being a bit cheeky, but I suppose I know what’s going on.

Rolf Claessen: Yeah, but maybe the third takeaway is that maybe the EPO will rethink the way — at least how AI inventions are assessed for inventive step.

Bruce Dearling: Well, as I said to you before, it could be that that’s the case. I don’t want to repeat myself again. The word “permissive” was used in a conversation I had with respect to the UK Supreme Court approach. COMVIK fundamentally still breaks with me and has done for years, because the way it’s set up and the way it’s applied distorts fundamentally what the invention is about. And until such time as that distortion is removed, there is a problem of objectivity versus subjectivity. And I think that’s really what the EPO has to grapple with. It’s not an easy thing to deal with, but maybe there are things going on.

Bruce Dearling: It’s not an easy thing to deal with. I don’t know who’s going to argue it. It would have been useful for me to still have the original case up and running at the EPO because these arguments would have been fleshed out. I’m pretty sure they would have been referred to the Enlarged Board. We would have got it resolved. So it’s whether or not I can now work this into the existing case to try and get the examining division to — well, they will refuse, I suspect. And then it’ll go to the TBA. And then the TBA will have to look at this, hopefully with the referrals to the Enlarged Board. And then that fixes the problem on a national and international basis.

Rolf Claessen: Yeah. Let’s see.

[Laughs]

Bruce Dearling: No, we don’t know. I mean, you might have a different view. What do you think? Do you think COMVIK is fundamentally right or fundamentally wrong?

Rolf Claessen: Well, I’m not so much into AI inventions. I’m a chemist and I usually deal with chemistry inventions. But from the discussion that we had, I think that the EPO might rethink their position. I don’t know. Let’s see. Let’s hope so.

Bruce Dearling: Well, they liked it. They liked problem-solution. It’s been with us for 25 years. It suggests that it’s a compromise. It’s not mandated by the European Patent Convention — that’s the point. It’s something they think works. And these things only work until such time as someone comes along and says, actually, you’re wrong, and this is the reason.

Rolf Claessen: Let’s see if they choose a different route at least for AI inventions. So Bruce, thank you very much for your insight and for talking about the case that you were involved in with the UK Supreme Court. Where could people reach you if they have more questions about this field — basically patents, AI protection in the UK and Europe — and if they want to ask you more questions about this case?

Bruce Dearling: Sure. Through the Hepworth Brown website or my LinkedIn profile, I suppose. The Hepworth Brown website has an email link. I’m trying to post things on it as well to try and provide a bit more context. But if people have fundamental questions on this stuff, then I’m happy to try and answer them. I suppose that I can be considered to be quite knowledgeable in the area.

Rolf Claessen: Right. Certainly more than I am.

[Laughing]

Bruce Dearling: So I was fortunate. As a consequence of the work I’m doing, I was appointed last year to the WIPO Standing Committee on Patents and Privacy. That was discussed for the issues of where WIPO goes and what the direction of the problems are that we have in high-tech areas. So there seems to be some degree of understanding that I might know what I’m talking about. I think I probably do.

Rolf Claessen: Thank you, Bruce. Thank you very much for being on IP Fridays.

Bruce Dearling: My pleasure. Thank you very much, Rolf.

My co-host Ken Suzan and I are welcoming you to episode 174 of our podcast IP Fridays!

In today’s interview, Ken Suzan interviews Brian McGinnis, partner at Barnes & Thornburg and co-chair of the firm’s data security and privacy practice, about why companies need to stop treating data privacy as a compliance burden and start treating it as a core business asset. McGinnis argues that data is either a managed asset or an unmanaged liability, with no middle ground.

But before we jump into this interview, I have news for you!

The EPO saw a Record Year with 200,000+ Patent Applications in 2025: German filings dropped 2.2% while China grew 9.7%, overtaking Japan for the first time. Germany remains Europe’s top patent nation but loses ground globally. SMEs and universities now account for nearly half of all Unitary Patents granted to European innovators.

News from the UPC Court of Appeal: Non-Technical Features Count for Inventive Step. An April 17 ruling clarifies that all claim features must be evaluated in their combined effect, including non-technical ones. Companies with software-related or mixed-technology inventions pending at the EPO or UPC should reassess recent inventive step objections at the UPC in light of this decision.

Nokia Withdraws UPC and Munich Suits After Global FRAND Settlement; Following a global FRAND rate-setting decision by the UK High Court, Nokia withdrew parallel suits against Warner Bros. and Paramount at the UPC and in Munich. One UK ruling resolved litigation spanning Germany, the UPC, the US, and Brazil simultaneously.

China Abandons Anti-Suit Injunctions in SEP Disputes: After a WTO arbitration ruling from July 2025, China withdrew its practice of blocking SEP holders from filing suits abroad. The EU Commission continues monitoring compliance, since the former policy was largely informal rather than codified in statute.

The Trump Administration has put 100% Tariffs on Imported Patented Pharmaceuticals: Based on Section 232, the Trump administration imposed 100% tariffs on patented drugs and biologics effective April 2, 2026, with a 120-day transition period until July 31. EU member states face a reduced rate of 15%. Generics and biosimilars are explicitly excluded.

China Rejects 1.27 Million Trademark Applications in Three-Year Crackdown: China’s CNIPA rejected over 1.27 million trademark applications and invalidated more than 3,300 marks, targeting so-called edge-ball marks designed to mislead consumers about product quality or origin. The announcement was made at an official press conference on April 23, 2026.

Now let’s jump into the interview with Brian McGinnis!

Brian McGinnis is a partner at Barnes & Thornburg and co-chair of the firm’s data security and privacy practice. In this episode of IP Fridays, he argues that companies treating data privacy as a compliance burden are missing the point entirely and leaving significant value on the table.

Data Is Either an Asset or a Liability

Most companies still treat their data as invisible and costless. They do not manage it the way they would manage a patent portfolio or a trademark. That, McGinnis argues, is a fundamental strategic error. Data is either a managed asset or an unmanaged liability. There is no middle ground.

When companies invest in understanding what data they collect, how it is used, and who has access to it, they unlock opportunities to drive real revenue and growth. Done right, a data governance program is not a cost center. It is a foundation for trust, operational efficiency, and competitive advantage.

One Program, Not Twenty

With more than 20 US state privacy laws now in effect, and major economies worldwide introducing their own frameworks, building separate compliance programs for each jurisdiction is neither practical nor smart. McGinnis recommends a single, comprehensive governance framework designed around the core purpose and intent of privacy law, flexible enough to absorb new requirements as they emerge.

Companies that threw together a quick program when California’s CCPA came into force in 2020 are now overdue for an upgrade. The goal is to move from reactive compliance to a mature, proactive program that positions the company ahead of the regulatory curve rather than perpetually catching up.

Website Tracking Tools: An Underestimated Risk

One of the fastest-growing areas of privacy litigation involves tracking technologies built into company websites: pixels, session replay tools, analytics scripts, and chat widgets. Legal teams are often entirely unaware of what IT or marketing has deployed. That gap is expensive.

Plaintiffs’ attorneys are applying 1970s-era telephone wiretapping statutes, including the California Invasion of Privacy Act, to argue that collecting any personal information, including IP addresses, before a user has consented constitutes illegal interception. Demand letters are being sent at industrial scale, with settlements typically running between $10,000 and $20,000 per case. What makes this particularly difficult is that a company can be fully compliant with statutory privacy law and still face these wiretapping claims, because the legal theory turns on the timing of data collection rather than the existence of a privacy notice.

Vendor Contracts: The Hidden Exposure

Marketing and technology agreements are another major source of unmanaged data risk. When a company deploys a third-party tool that handles personal data, the underlying contract needs to define precisely who owns that data, what the vendor is permitted to do with it, and what obligations flow down to any sub-processors involved.

McGinnis draws a direct parallel to IP licensing: owning valuable data and then handing it to a vendor under a poorly drafted agreement is the equivalent of signing a bad IP license. Data processing agreements need to cover ownership, use restrictions, sub-processor obligations, breach notification timelines, audit rights, and deletion obligations. Many companies simply do not have these terms in place. Without them, a vendor who suffers a breach of non-personal business information has no contractual obligation to disclose it.

Consumer Rights Requests: Process Matters

Privacy laws give individuals the right to access, correct, delete, and opt out of the use of their personal data. Responding to these requests effectively requires pre-built processes, trained staff, and the technical ability to locate and act on individual data across all systems and sub-processors. Most companies, before engaging in formal data mapping, are not in a position to do this reliably.

Staff failing to recognize a deletion request as a legal data subject request and routing it through a standard customer service queue instead is one of the most common failures McGinnis sees. The consequences can include regulatory complaints and class action lawsuits, particularly when a company continues to send emails to someone who has already requested deletion of their data.

A newer risk involves Global Privacy Controls: browser-level opt-out signals that regulators and courts are now treating as legally binding deletion and non-collection requests. Companies receiving these signals daily without acting on them face growing exposure under several state laws.

AI Governance: Policy Before Tools

Generative AI tools are now embedded across business functions, from contract review and customer service to content creation and internal search. McGinnis is direct: every company needs an AI acceptable-use policy, and the absence of one is not a neutral position. Without clear rules, employees will use unapproved or publicly available tools regardless, feeding proprietary and sensitive information into open models with no control over how that data is used or retained.

He draws a precise parallel to patent law. Posting proprietary information into an open AI system carries the same risk as publishing it publicly, potentially destroying patentability. The distinction between closed, organization-specific AI systems and open, publicly accessible ones is something employees need to understand explicitly. Making compliance easier than non-compliance is the practical goal.

The Regulatory Outlook: More Laws, More Enforcement

McGinnis expects the regulatory landscape to continue expanding. The EU AI Act is already setting the direction, and several US states have introduced or are developing AI-specific legislation. The pattern mirrors what happened with data privacy: Europe leads, US states follow in a patchwork, and federal legislation remains uncertain.

Enforcement of existing privacy laws is also intensifying. GDPR has been in force since 2018, CCPA since 2020, and regulators are now past the period of extended tolerance for companies that are still catching up. Companies with immature compliance programs should expect less patience from regulators going forward.

McGinnis closes with a clear point of view: if you have to comply anyway, get credit for it. A well-built governance program is a trust signal to customers, a sales asset, and a foundation for responsible AI use. Compliance done right is not a tax. It is a differentiator.

The Full Transcript:

Ken Suzan: Our guest today on the IP Fridays podcast is Brian McGinnis. Brian is a partner with Barnes and Thornburg and a founding member and co-chair of the firm’s data security and privacy law practice group. Brian serves as a member of the intellectual property department and the internet and technology practice. Brian is a Chambers Global and national ranked privacy and data security attorney, a certified information privacy professional, and the firm’s chief privacy officer. Brian brings nearly two decades of experience at the intersection of law and technology. Brian advises on a wide range of technology-driven legal matters, including privacy and data security, intellectual property, artificial intelligence, corporate transactions, software, and internet law. His deep understanding of privacy and technology law enables him to guide clients through rapidly evolving regulatory and operational challenges. Welcome Brian to the IP Fridays podcast.

Brian McGinnis: Hey, thanks Ken. I appreciate it. Great to be here and thanks for having me.

Ken Suzan: Excellent. Brian, the C-suite tends to treat data privacy as a compliance tax, something to hand off to legal and forget about. But when you see how companies actually get into serious trouble, what’s really going on?

Brian McGinnis: Yeah, well, it’s a great place to start Ken and looking forward to the conversation today covering some of these privacy issues and AI issues, which I found in my own practice is really bled into the straight privacy stuff. Companies can’t really handle these things in a silo anymore. It’s really about managing and coming together as a coherent program for governance for the organization. I think if you do that right, the good news is we can become revenue generators and show growth for the company and not just compliance centers and a compliance tax. But I think the core problem that we face in working with most companies is that a lot of companies still treat their data as invisible, costless. They don’t treat it, in other words, like they would a patent portfolio or trademark or other IP portfolio. It’s just not managed as an asset in the ways that we’ve seen more sophistication around IP. And it really should be. Data is either a managed asset for the company or it’s an unmanaged liability. There’s really not an in between. And so for those companies that haven’t gotten their arms around all this data and what can be done with it, I think they’re really missing an opportunity. Having an understanding of what data the organization is collecting, how it’s being used, and having the proper governance around it really unlocks a lot of opportunity for use of that data in new ways — ways that can drive revenue and growth for the company. So I approach privacy not just about compliance, not just about avoiding penalties or doing it because some law out there says that we have to do it. It’s really about knowing and controlling one of the company’s core assets. And if you’re not doing that, you’ve got unmanaged data that you’re not getting value out of and that potentially could be a huge liability for the company. Managed well, it really supports trust, efficiency, and growth of the organization. Otherwise, I think it’s a missed opportunity.

Ken Suzan: Yes, well said. Now let’s talk about state laws. With 20-plus state privacy laws now in effect, how should companies build a program that actually works across the board without starting over every time a new state law kicks in?

Brian McGinnis: Yeah, so the first answer is don’t build 20 separate programs. This really goes back to having a comprehensive, sophisticated, well thought out program that really takes into account not only the 20 state laws, but obviously we’ve got international exposure with laws like GDPR and upcoming privacy laws internationally. Most of the larger economies in the world have some form of laws around privacy and AI. So you can’t really anymore build programs that account for the one, two, three, four, five different laws that in the past we had experience with — where you could just treat California as its own thing, treat New York as something else, and treat Europe as something else. The laws and the pace of these have really forced companies into having comprehensive programs. I don’t expect to see fewer laws. You’re only looking at potentially additional state laws, additional federal laws here in the US, and then certainly additional laws throughout the world. So a lot of the strategy these days is not only where are we today with these laws, but how do we set up our governance program in a way that really cuts to the core of the purpose and intent behind these laws so that we can be better prepared when new laws come about in the future. Historically, at least in the US, most companies just haven’t had laws that force them into compliance postures. As these laws have started to come along, a lot of companies have been playing from behind and saying, oh, the California Consumer Privacy Act, I just read about it and it goes into effect next week — let’s throw something together and call that our compliance program. We’ve now got years of these laws being in place, CCPA came into effect in 2020, and what we’re seeing much more of are companies looking to get more sophisticated in their programs and stop feeling like they’re always rushing to catch up. The goal is to level up their program, going from level one — constantly playing from behind — to level two and then level three, so that they really feel like they’re on top of it and have a sophisticated program that not only accounts for all the various privacy requirements that come at them, but also positions them to take advantage of the data and all the things that come along with having a good governance program.

Ken Suzan: Brian, there’s an explosion of litigation targeting something most companies barely think about — the tracking tools baked into their own websites: pixels, session replay tools, analytics scripts, chat widgets, the list goes on and on. What’s happening, Brian, and what should companies do?

Brian McGinnis: Yeah, and I think a lot of companies — the executives, the business teams — don’t even realize a lot of these tools are on their sites. IT deployed them years ago, the web team deployed them, marketing teams are constantly using them and certainly have a good understanding of it. But in a lot of cases, legal has never touched them and has no idea what’s happening on the website. We also see a lot of cases of companies who, even if they’re generally aware these tools are in use, aren’t aware what other teams are putting on the site or what those pieces of technology are tracking. And that gap can be really expensive. What we’re seeing right now — and this has been a trend for a number of months now and is really continuing to pick up steam — is a series of what I call gotcha lawsuits, where you have some enterprising plaintiffs’ counsel who have taken a look at some 1970s-era telephone wiretapping laws, including a law called CIPA, the California Invasion of Privacy Act, passed in the 70s with the idea that you shouldn’t be able to wiretap people’s telephone conversations. They’ve taken that and applied that theory to the internet. The way it works is: if a website has some sort of cookie, pixel, or other tracking technology on it that collects personal information about an individual — and that can be as simple as an IP address and device ID — and if that collection occurs as soon as the individual shows up at the website, prior to them being able to have notice provided to them or opt in and consent to that collection, then the theory under these lawsuits is that it constitutes wiretapping. We see a lot of this with the Meta pixel, with LinkedIn pixels, and the like. What they’re doing is effectively showing up and suing, threatening to sue, trying to take you to arbitration, depending upon what’s included in the company’s existing privacy notice. If you don’t have a cookie banner, if you don’t have a cookie notice, if you’re not getting opt-in on these things, they’re leaning on those failures and effectively trying to force you into a position where you are forced to make a settlement. Because the cost to litigate one of these to their conclusion would be expensive, whereas a lot of these cases will settle for $10,000 to $15,000 somewhere in that range. They’ve got technology crawling the internet looking for websites that don’t have these risks covered, sending demand letters and then collecting settlements, $10,000 to $20,000 at a time. It’s been very profitable for them and a very dangerous thing for our clients. And it’s a bit unusual because you can be fully compliant with the statutory privacy laws that require notification of the use of tracking technologies and cookies and banners — and still be subject to these lawsuits because of the wiretapping arguments being made. The timing wherein the data is collected from the individual could still subject you to these lawsuits. So it’s a tricky problem, one that I hate seeing companies get hit with and one that we spend a lot of time helping companies avoid.

Ken Suzan: Yes, let’s talk about contracts, Brian, because I know you work with contracts probably on a daily basis. A lot of data risk lives inside vendor and technology agreements — the contracts companies sign with marketing platforms, analytics providers, cloud infrastructure, and SaaS tools. What should those agreements actually contain?

Brian McGinnis: Yeah, so there’s quite a lot of things. You’ve got a world where marketing is constantly under pressure to learn more about their customers. The way they can do that is through any number of different tools and data gathering techniques, and we have all this technology available to help marketing and sales do better at their jobs. But we, at least in this country, got to a position where people really felt like they lost control of their information and their data. And so these privacy laws came along and really started to provide more rights to individuals — to have an understanding of what data exists within various companies that they do business with, who they’re sharing it with, trading it with, selling it to for advertising purposes; to have the right to opt out; the right to delete their information. Not checking through the agreements by which these teams are implementing these tools is a huge issue for companies. As part of an overall compliance program, having some kind of process where people who are aware of the growing numbers of privacy laws are reviewing these marketing contracts to make sure they are aligned with that program and aligned with those laws is absolutely critical. To talk about IP, given the IP Fridays audience: it’s kind of the equivalent of having really bad IP licenses. In other words, you own and control this information and data, and you need to control what the other side can do with one of your most valuable assets — or you’ve effectively given it away. So thinking about it in that way could be useful. In terms of more specifics: a big one is ownership of the data. The agreement itself may or may not have anything that addresses data. If there’s personal information involved, you probably need what we call a data processing agreement or addendum — a DPA — that specifically controls what that third party is able to do with that data, how they’re able to use it, whether they’re able to share it, whether they’re able to get value out of it on their own, or if they’re only allowed to be what we call a service provider, just providing services to the business that hired them. There needs to be explicit prohibition on retaining, using, and disclosing personal information for any purpose other than performing the exact services in the contract. Whether or not they’re permitted to sell or share data under CCPA terms is another key point. Certification that the provider will comply with any restrictions and security requirements you have on your data, and making sure those obligations flow down to any sub-processors they might use. You hire Company A, but Company A works with Company B and C to provide parts of their service. You’re effectively responsible for the protection of personal information throughout its lifecycle. A couple of other key provisions: breach notification triggers and timeline. It’s very possible under a lot of agreements that one of your vendors can suffer the world’s worst hacker breach and have no legal obligation to tell the company that hired them about it — unless there’s personal information involved. State data breach laws apply to personal information, not to other types of sensitive business information. Unless you have a contract that explicitly requires notification, there’s a good chance that vendor may not want to disclose it. And then other things like audit rights and deletion obligations go in there as well.

Ken Suzan: Certainly a lot to cover. Let’s talk about privacy laws and consumer rights. Privacy laws give consumers real rights — to access their data, correct it, delete it, and opt out of how it’s being used. Most companies have a process for this on paper. What does it actually take to get it right, and what happens when it breaks down?

Brian McGinnis: Yeah, it takes pre-planning. It takes a process. Some companies receive many more of these requests than others — some B2B companies receive none or a couple per year, while companies heavily involved in marketing to consumers might receive tens or hundreds a day. To be able to respond to these effectively and efficiently requires some forethought. It requires policy and procedure internally to be set up, and it requires the education of the team. Some of the common ways we see this go wrong: staff isn’t trained to know the difference between what we call a DSR — data subject request — versus a regular customer service inquiry. Maybe somebody submits what would be construed by law to be a deletion request and you just put it into your normal customer service response flow — and then you’re potentially missing timelines and the like. There also need to be systems in place to respond in accordance with the individual’s rights. Somebody submits a request saying, you have my information — what information do you have about me? Can your company determine that right now? Can you look through all your systems and down the line to all the processors and sub-processors you’ve worked with and hired, and identify what information you have about that individual? Most companies, until they engage in a governance program and data mapping, are at a real disadvantage to be able to do that. Why is that a problem? Because two weeks from now your company could be sending emails to the individual who just told you to delete their data, and they get really upset. That’s when they go and complain to regulators or start class action lawsuits. The lack of planning can be really, really expensive for a lot of companies. Making sure you’ve got some kind of process to understand what’s coming in, that the people receiving those requests know the difference between a regular customer service request and a data subject request, and that it gets to the appropriate parties for action — all of that is really, really key. Another one that we’re seeing pop up is what we call GPC, or Global Privacy Controls. It used to be that people would say “do not track” in their browser and most companies would ignore those signals. Now we’ve got advancements in law and browser technology where the browser you’re using to visit a company’s website sends a signal saying, opt me out of this. Regulators and courts are construing those as deletion requests, as opt-out requests that companies are now required to respond to. If your company hasn’t gone through an exercise to understand that, and is probably receiving GPC opt-out requests on a daily basis without acting on them, there’s some exposure there. At the end of the day, a lot of this really is about getting the appropriate people from across the organization — really each department — around a table, figuring out what data you collect, how you use it, who you share it with, where it comes from. That starts the process of your data map. Then you set about mapping that to the various legal requirements and figuring out how to respond, how to make it easy for people to exercise their rights so they’re not complaining, not suing, not going to regulators. Letting these squeaky wheels out of the process — the ones who don’t want you to be processing their information any longer — is really key.

Ken Suzan: Let’s switch gears a bit and talk about AI. I know we’re hearing about it every day. Generative AI tools are now embedded in how companies work — contract review, customer service, content creation, internal search. Before employees start using these tools with customer data, confidential business information, or proprietary content, what has to be in place first?

Brian McGinnis: Yeah. I think we’re long past the days when companies provided individuals access to corporate technology — computers, devices, and the like — without having some kind of acceptable use policy that governs that. We don’t want you downloading stuff that could harm our network or create security issues. We don’t want you using our technology in certain ways, whether that’s a BYOD policy or just general use of company internet or company devices. An AI acceptable use policy is really a continuation of those. Every company needs to have an AI acceptable use policy. Period. In my opinion, things like that are as important as the fire escape policy out in the hallways for these companies. I can tell you with absolute certainty: if your organization has not provided rules to your employees and personnel about the use of AI, what they can and can’t use — or if you’ve said you can’t use any AI — the personnel is still using AI. They’re just not using any approved tools. They’re probably using their own private tools that they subscribe to, or even worse, tools they don’t pay for, in which case they’re putting company information into a wide open public model. The more companies can do to think through this ahead of time, reduce it to policy, and then train and educate people on that company’s particular policy, the better. You need to make it easier for people to comply than not comply. An acceptable use policy should talk about: here’s how we can and can’t use it, here’s the data that should and should not go into the system, here’s some proper uses of AI, here’s some data that’s on the fringe that we need to keep out — more sensitive information, proprietary information, etc. Making sure you’re funneling and educating people about the difference between closed systems and open systems. In other words, this is a tool that only looks at our organization, only uses the data within a certain box, and is not publicly available — the AI system is not training on our data. You have more leeway to put more sensitive information into those types of systems than you do with open systems which potentially lose control of your data. It’s almost like a patent consideration in terms of keeping information secret. If something potentially has some patentability that you want to seek to file in the future, you can’t just go out and post it publicly and use public search engines and all this other stuff at the risk of exposing it. Similar concepts here — really getting a handle and control over what tools people can use and providing some education to them about how the company wants to think about what’s acceptable and what’s not in those uses is really the key starting point.

Ken Suzan: Very useful information. Indeed, we’re coming towards the end of today’s episode. One final question for you, Brian. Where do you think we’ll be two years from now in this developing field, and how best for companies to stay ahead of the curve?

Brian McGinnis: Yeah, this kind of takes us full circle, Ken. I think it’s kind of back to the beginning comments about the privacy space — and we’ve only got more of these laws coming. It’s still a developing field. We’re still really in the early days of enforcement. I mean, GDPR has been around since 2018, CCPA in the US really kicked us off in about 2020, and so there’s been a settling-in period as companies adjust and get used to having these laws and get compliance programs in place at various levels — from not at all prepared to highly sophisticated. We’re still pretty early on in terms of enforcement of these things. We’re already starting to see enforcement of more egregious violations of these various laws, and we’ll only continue to see more enforcement as the laws exist currently and as they continue to come along. The days of not having to pay attention to this are kind of over. And I always tell clients: if you’re going to have to do these things, you’re going to have to be compliant — you might as well get credit for it. By which I mean, let’s put all the policies in place, let’s do all the compliance activities, let’s have a sophisticated governance program, but then let’s also use that as a sales tool, as a way to help grow the company, as a way to sell new products and gain trust and earn trust with our customers — so that they know when they’re doing business with us, or when they’re giving us information, or when they’re using our AI tool, that we respect that and are going to take care of their information and have the structure in place internally to be able to do that. With respect to AI, what I’m seeing is very similar to what we have seen with the growth of privacy law — again led by Europe, with the EU AI Act in this case. Now you’ve got a handful of states in the US that already have AI laws, and others that are interested in continuing to roll those out. There’s friction with the federal government around whether there’s going to be a comprehensive law there. Like the privacy space, you’ve got varying factions — some of which want to develop really quickly with very little guardrails, others which say we’re threatening the future of humanity if we don’t get those guardrails in place. I think ultimately, at least in the US, we’re going to end up with another patchwork of AI laws for the foreseeable future that we’ll have to navigate. So really having a company position, a company philosophy of how do we handle all these various laws, how do we treat people’s data, how do we get our arms around it, how do we respond to whatever legal rights they currently have, and what principles do we put in place so that we can adapt for the future — and then, once we’ve done those things, how do we actually get value out of this and move the business forward. So it’s not a compliance tax, but a benefit to the business. That’s the end goal here, and I think the North Star for us.

Ken Suzan: Fantastic, Brian. This has certainly been a very comprehensive interview. Really appreciate you taking the time to talk about it with us here on the IP Fridays podcast.

Brian McGinnis: Happy to do it, Ken. Thanks for asking me and good to see you. Thank you.

Register for the 2016 INTA Annual Meeting at https://inta.org !!

In a recent episode of the IP Fridays podcast, I spoke with Deborah Hampton, President of the International Trademark Association (INTA) and Global Brand Enforcement and Trademark Team Leader at the Chemours Company.

I am Rolf Claessen and my co-host Ken Suzan and I are welcoming you to episode 173 of our podcast IP Fridays! Today’s interview guest is Deborah Hampton. She is the Global Brand Enforcement & Trademark Team Leader at The Chemours Company and is currently serving as the president of the International Trademarks Association. But before we jump into this interview, I have news for you:

The US Department of Justice and the USPTO filed a joint statement supporting the right of Non-Practicing Entities (NPEs) to seek injunctions against patent infringers. This position challenges established post-eBay case law, which has made it difficult for NPEs to obtain injunctive relief.

The UPC Court of Appeal ruled that security for costs can be provided through specialized insurance policies. This significantly lowers the financial barriers to bringing patent actions at the UPC, as companies no longer need to deposit large amounts of liquid capital as security.

Huawei has filed a new lawsuit at UPC Mannheim against twelve Walt Disney Group companies (Ref. UPC-CFL-0000352/2026), asserting EP 3 211 897 relating to transform coefficient coding under the HEVC standard used by Disney+. Two additional suits were filed at Munich Regional Court I. In a parallel action, Huawei is suing Meta and Facebook at the UPC over EP 3 471 419, covering video compression in end devices. This continues Huawei’s strategy of pressuring streaming and platform providers into licensing its SEP portfolios.

In a landmark first, the UPC Court of Appeal has referred a legal question to the European Court of Justice (ECJ): whether the UPC has jurisdiction over defendants without a seat in a UPC member state, provided a co-defendant is domiciled within the UPC territory (“long-arm jurisdiction”). The case arose from a dispute between Dyson and Chinese competitor Dreame; the first-instance injunction was simultaneously extended to cover newer Dreame hair dryers. For German companies, this signals a gradual expansion of UPC jurisdiction beyond its territorial borders, with significant implications for cross-border patent strategy.

And now let’s jump into the interview with Deborah Hampton:

Our conversation covered one central question:
How must intellectual property enforcement evolve in a world that is more global, digital, and complex than ever before?

A Career Built on Intellectual Property

Deborah Hampton has spent more than four decades in the field of intellectual property. She began her career as a paralegal in a small IP firm in New York and quickly discovered her passion for the subject.

Over the years, IP has taken her around the world. She has worked with leading professionals, governments, and institutions. Her experience reflects a key truth: IP is not a narrow legal discipline. It is a global ecosystem that connects law, business, innovation, and policy.

Counterfeiting: A Much Bigger Problem Than Many Think

One of the key topics in our discussion was counterfeiting.

Many people still see counterfeit goods as a minor issue—cheap handbags or fake T-shirts bought on holiday. But the reality is far more serious.

Counterfeiting creates real risks for consumers because products often bypass safety and quality standards. It damages trust in brands and undermines legitimate marketplaces, especially online.

The economic impact is also significant. Companies lose revenue, innovation slows down, and jobs are affected. Smaller businesses suffer the most because they often lack the resources to fight counterfeiting effectively.

Perhaps most concerning is the link to organized crime. Counterfeiting is not an isolated activity. It is often part of larger illegal networks.

From Deborah Hampton’s perspective, effective enforcement must address both supply and demand. That includes stronger border measures, better online enforcement, and, importantly, consumer education.

The Core Problem: Fragmentation in IP Enforcement

A central theme of the interview was fragmentation.

Many companies approach IP protection in silos. Legal teams, cybersecurity experts, business units, and external advisors often work separately. Even when they pursue the same goal, their efforts are not aligned.

This leads to inefficiencies, missed opportunities, and unnecessary risks.

To address this, Deborah Hampton has launched a Presidential Task Force at INTA. The goal is to create a unified approach to IP protection and enforcement.

The idea is simple but powerful:
Bring all stakeholders together and align strategy, enforcement, and measurement.

This includes not only companies and their advisors but also regulators, courts, customs authorities, and IP offices. Only a coordinated approach can effectively address global challenges like counterfeiting.

The Changing Role of IP Professionals

Another important insight is how the role of IP professionals is changing.

In the past, IP work was often reactive and focused on legal protection. Today, expectations are much higher.

IP professionals are now expected to:

Act as strategic advisors to the business

Align IP with commercial goals

Manage global and digital portfolios

Use data to make better decisions

At the same time, new technologies such as artificial intelligence are transforming how IP is managed and enforced. These tools create efficiencies but also raise new legal and strategic questions.

Budget constraints add another layer of complexity. Teams must achieve more with fewer resources.

In short, IP professionals must become more strategic, more integrated, and more business-focused.

Why the INTA Annual Meeting Matters

We also discussed the upcoming INTA Annual Meeting in London.

For many in the field, this event is the most important gathering of the year. It brings together more than 10,000 professionals from around 140 jurisdictions.

According to Deborah Hampton, the value lies in three areas:

First, the return on investment is exceptionally high. The combination of education, networking, and business development is difficult to replicate elsewhere.

Second, the educational program is extensive. It covers law, policy, technology, and the business of intangible assets.

Third, the networking opportunities are unmatched. The meeting creates a unique environment where a year’s worth of work can be done in a single week.

At the same time, Hampton addressed a sensitive issue: attending without registering. She made it clear that this practice undermines the entire system. Without proper support from participants, events like this would not be possible.

A Clear Message for the Future

If there is one key takeaway from the conversation, it is this:

Intellectual property protection must become more coordinated, more strategic, and more closely aligned with business objectives.

The challenges are growing. Counterfeiting is more sophisticated. Markets are more global. Technology is changing rapidly.

But the opportunity is also clear. By breaking down silos and working together across functions and borders, companies can protect their IP more effectively and create real value.

For IP professionals, this means stepping into a broader role. Not just as legal experts, but as strategic partners in the business.

Rolf Claessen: Today’s guest on the IP Fridays podcast is Deborah Hampton. If you don’t know Deborah, she’s the global brand and enforcement and trademark team leader at the Chemours company and is currently serving as the president of the International Trademark Association. Thank you for being on our podcast IP Fridays, Deborah.

Deborah A. Hampton: Thank you. Thank you for having me.

Rolf Claessen: So you have been in the field of IP for more than 25 years now. How did you get there and where did it lead to you?

Deborah A. Hampton: I’ve actually been an IP practitioner for 43 years. I started at a small IP firm in New York; it was my first paralegal position, and I fell in love with IP from the very beginning. This field has allowed me to travel the world meeting some amazing and brilliant colleagues as well as high-ranking government, judicial, and IPO officials. I’ve also worked extremely hard to stay abreast of trends, statutes, precedent cases, and practices that enhance the way we do our jobs.

Rolf Claessen: Wow. That sounds really exciting. I didn’t know you’ve been in the field so long. Great to hear that. So I’m personally very interested in the fight against counterfeit goods. Why, in your personal opinion, is it so important to fight counterfeit goods? Maybe you can share your thoughts on why it is important and a little bit about how you do it.

Deborah A. Hampton: There are a number of factors that I always take into consideration when it comes to counterfeit goods. Starting with consumer safety, counterfeits often bypass safety and quality standards, putting consumers at real risk. Then there’s consumer trust; fake goods undermine confidence in brands and legitimate marketplaces, especially online.

Economic harm is another factor; counterfeiting drains revenue from lawful businesses, weakens innovation, and ultimately costs jobs. Smaller businesses (SMEs) are hit the hardest because they lack resources to combat fakes at scale.

The factor that scares me the most is organized crime, as counterfeiting fuels criminal networks and is linked to broader illicit activity. There is also the issue of fair competition, where fake goods distort markets by undercutting compliant, responsible producers. Finally, strong enforcement protects the integrity of the IP system and the trademarks that drive investment, innovation, and growth.

It is important to combat the production, sale, and demand for counterfeit goods. At INTA, our anti-counterfeiting priorities focus on customs and border measures, criminal enforcement, online counterfeiting, and consumer education. Our Anti-Counterfeiting Committee leads initiatives to address the production and sale of fakes by monitoring worldwide developments in treaties and legislation and proposing policy recommendations to the board. We also partner with stakeholders to promote cooperation across agencies and borders.

Additionally, the Unreal Campaign Committee addresses the demand for counterfeit goods by educating young consumers ages 14 to 23 about the importance of brands and the dangers of fakes. I remember being that age and wanting low-priced goods that looked good, but now I realize I probably wasn’t always getting genuine products.

Rolf Claessen: Yes, that helps me explain to friends who buy fake clothes on holiday in Turkey and don’t realize the harm they are doing. You’re also on the presidential task force for unifying IP protection and enforcement strategy. Can you tell us more about who is part of this task force and what the agenda is?

Deborah A. Hampton: When I was nominated to become an officer, I immediately wondered what my presidential task force topic would be and what I would wear for the opening ceremonies. The 2026 task force is titled “Unifying Intellectual Property Protection and Enforcement Strategy”. The goal is to eliminate value leakage and risk caused by fragmented approaches to IP protection. We want to deliver a unified global operating model that aligns strategy and enforcement, allowing organizations to work smarter and quantify their impact across all jurisdictions.

Many organizations, including my own, currently operate in disconnected silos that sometimes work at cross purposes. The challenge is to maintain internal coordination across all intangible-related aspects. We have many stakeholders—business, security, cybersecurity, outside counsel, customers, the judiciary, and IPOs—all striving for the same goal, but the road we take is not always unified. I hope to build a strong cross-functional partnership focused on protecting all forms of IP, including patents and designs, not just brands.

Rolf Claessen: Right, IP includes patents and designs and everything. Most importantly, you are this year’s INTA president. What is your agenda for the year and what do you want people in the field to realize?

Deborah A. Hampton: As president, I chair the board and steward our strategy and governance. I am also an ambassador, representing INTA globally to IPOs and government officials.

My agenda has three pillars. First is the 2026–2029 Strategic Plan, which is the roadmap for our future. Second is my Presidential Task Force on unifying IP strategies. Third is volunteer mobilization; with a new committee structure in 2026, I want to energize our volunteers and recognize their contributions.

I want people in the field to prioritize mentorship and professional development for the next generation. We need to ensure young practitioners are prepared to lead. I also want them to embrace the unified approach to IP protection we are advocating.

Rolf Claessen: That’s a powerful vision. Thank you so much for sharing your insights and for the work you’re doing with INTA.

Deborah A. Hampton: Thank you again for the opportunity. I really enjoyed the interview

I am Rolf Claessen and together with my co-host Ken Suzan I welcome you to Episode 172 of our podcast IP Fridays. Today’s interview guests are Co-Founder & CEO of Inception Point AI, Jeanine Wright, and Mark Stignani, who is Partner & Chair of Analytics Practice at Barnes & Thornburg LLP.

https://www.linkedin.com/in/jeaninepercivalwright

https://www.linkedin.com/in/markstignani

Inception Point AI

But before the interview I have news for you:

The Unified Patent Court (UPC) ruled on Feb 19, 2026, that specialized insurance can cover security for legal costs. This is vital for firms, as it eases litigation financing and lowers financial hurdles for patent lawsuits by removing the need for high liquid assets to enforce rights at the UPC.

On Feb 12, 2026, the WIPO Coordination Committee nominated Daren Tang for a second six-year term as Director General. Tang continues modernizing the global IP system, focusing on SMEs, women, and digital transformation. His confirmation in April is considered certain.

An AAFA study from Feb 4 reveals 41% of tested fakes (clothing/shoes) failed safety standards. Many contained toxic chemicals like phthalates, BPA, or lead. The study highlights that counterfeiters increasingly use Meta platforms to sell unsafe imitations directly to consumers.

China’s CNIPA 2026 report announced a crackdown on bad-faith patent and trademark filings. Beyond better examination quality, the agency will sanction shady IP firms and stop strategies violating “good faith” to make China’s IP system more ethical and innovation-friendly.

Now, let’s hear the interview with Jeanine Wright and Mark Stignani!

How AI Is Rewiring Media & Entertainment: Key Takeaways from Ken Suzan’s Conversation with Jeanine Wright and Mark Stignani

In this IP Fridays interview, Ken Suzan speaks with two repeat guests who look at the same phenomenon from two angles: Jeanine Wright, Co-Founder & CEO of Inception Point AI, as a builder of AI-native entertainment, and Mark Stignani, Partner and Chair of the Analytics Practice at Barnes & Thornburg LLP, as a lawyer advising clients who are trying to use AI without stepping into a legal (or ethical) crater.

What emerges is a clear picture: generative AI is not just “another tool.” It is rapidly becoming the default infrastructure for creative work—while the rules around ownership, consent, and accountability lag behind.

1) What “AI-generated personalities” really are (and why that matters)

Jeanine’s company is not primarily “cloning” real people. Instead, Inception Point AI creates original, fictional personalities—characters with backstories, ambitions, and evolving arcs—then deploys them into the world as podcast hosts and content creators (and eventually actors and musicians).

Her key point: the creative work still starts with humans. Writers and creators define the concept, tone, audience, and story engine. What AI changes is speed, cost, and iteration—and therefore what is economically feasible to produce.

2) The “generative content pipeline” isn’t a magic button

A recurring misconception Ken raises is the idea that someone “pushes a button” and content pops out. Jeanine explains that real production looks more like a hybrid studio:

A creative team defines character, voice, format, and storyline.

A technical team builds what she calls an “AI orchestration layer” that combines multiple models and tools.

The “stack” differs by format: the workflow for a long-form audio drama is different from a short-form beauty clip.

This matters because it reframes AI content not as a single output, but as a pipeline decision: which tools, which data sources, which QA, and which governance steps are used—and where human review happens.

3) The biggest legal questions: origin, liability, ownership, and contracts

Mark doesn’t name a single “top issue.” He describes a cluster of problems that repeatedly show up in client conversations:

Training data and “origin story”

Clients keep asking: Can I legally use AI output if the tool was trained on copyrighted works? Even if the output looks new, the unease is about whether the tool’s capabilities are built on unlicensed inputs.

Liability for unintended harm

Mark flags risk from AI content that inadvertently infringes, defames, or carries bias. The legal exposure may not match the creator’s intent.

Ownership and protectability

He points to a big gap: many jurisdictions are still reluctant to grant classic IP rights (copyright or patent-style protection) to purely AI-generated material. That creates uncertainty around whether businesses can truly “own” what they produce.

Old contracts weren’t written for AI

A final, practical point: many agreements—talent contracts, author clauses, data licenses—predate generative AI and simply don’t address it. That leads to disputes about scope, permissions, and—crucially—indemnities.

4) Are we at a tipping point? The “gold rush” vs. “next creative era” views

Jeanine frames AI as “the world’s most powerful creative tool”—comparable to previous step-changes like animation, special effects, and CGI. For her, the strategic implication is simple: creators who learn to use AI well will expand what they can build and test, faster than ever.

Mark’s metaphor is more cautionary: he calls the moment a “gold rush” where technology is sprinting ahead of law. Courts are getting flooded with foundational disputes, while legislation is fragmented—he notes that states may move faster than federal frameworks, and that labor agreements (e.g., union protections) will be a key pressure point.

5) Democratization: more creators, more niche content, more experimentation

One of the most concrete themes is access. Jeanine argues AI will:

Lower production barriers for independent filmmakers and storytellers.

Reduce the need for “hit-making only” economics that dominate Hollywood.

Make micro-audience content commercially viable.

Her example is intentionally niche: highly localized, specialized content (like a “pollen report” for many markets) that would never have made financial sense before can now exist—and thrive—because the production cost drops and personalization scales.

6) Likeness, consent, and “digital performers”: what happens when AI resembles a real actor?

Ken pushes into a sensitive area: what if someone generates a performance that closely resembles a living actor without consent?

Mark outlines the current (imperfect) toolbox—because, as he emphasizes, most laws weren’t built for this scenario. He points to practical claims that may come into play in the U.S., such as rights of publicity and false endorsement-type theories, and notes that whether something is parody or “too close” can become a major fault line.

Jeanine explains her company’s operational approach:

They focus on original personalities, designed “from scratch.”

They build internal checks to avoid misappropriating known names, likenesses, or recognizable identities.

If they ever work with real people, the model would be licensing their likeness/voice.

A subtle but important business point also appears here: Jeanine expects AI-native characters themselves to become licensable assets—meaning the entertainment economy may expand to include “celebrity rights” for fully synthetic personalities.

7) Ethics: the real line is “deception,” not “AI vs. human”

The ethical core of the conversation is not “AI is bad” or “AI is good.” It’s how AI is used—especially whether audiences are misled.

Mark highlights several ethical risks:

Misuse of tools to manipulate faces and content (“AI slop” and political misuse).

Displacement of creative workers without adequate transition support.

A concern that AI often optimizes toward “statistical averages,” potentially flattening originality.

Jeanine agrees ethics must be designed into the system. She describes regular discussions with an ethicist and emphasizes a principle: transparency. Her company discloses when content or personalities are AI-generated. She argues that if people understand what they’re engaging with and choose it knowingly, the ethical problem shifts from “AI exists” to “Are we tricking people?”

Mark adds a real-world warning: deepfakes are now credible enough to enable serious fraud—he references a case-like scenario where a synthetic video meeting deceived an employee into authorizing a payment. The point is clear: authenticity and verification are no longer optional.

8) The “dead actor” hypothetical: legal permission vs. moral intent

Ken raises a provocative scenario: an actor’s estate authorizes an AI-generated new performance, but the actor opposed such technology while alive.

Neither guest offers a simplistic answer. Jeanine suggests that even if the estate holds legal rights, a company might choose to avoid such content out of respect and because the ethical “overhang” could damage the storytelling outcome. She also notes the harder question: people who died before today’s capabilities may never have been able to meaningfully consent to what AI can now do—raising questions about how we interpret legacy intent.

Mark underscores the practical contract problem: many rights are drafted “in perpetuity,” but that doesn’t automatically settle the ethical question.

9) Five-year forecast: “AI everywhere,” but audiences may stratify

Ken closes with a prediction question: in five years, how much entertainment content will significantly involve AI—and will audiences care?

Jeanine predicts AI becomes the default creative layer for most content creation. Mark is slightly more conservative on the percentage, but adds an important nuance: the market will likely stratify. Low-cost, high-volume content may become saturated with AI, while premium segments may emphasize “human-made” as a differentiator—especially if disclosure norms become standard.

Bottom line for business leaders and creators

This interview lands on a pragmatic conclusion: AI will change how content is made at scale, and the competitive edge will go to teams that combine creative taste, operational discipline, and legal/ethical governance.

If you’re building, commissioning, or distributing content, the questions you can’t dodge anymore are:

What’s the provenance of the tools and data you rely on?

Who is responsible when output harms, infringes, or misleads?

What rights can you actually claim in AI-assisted work?

Do your contracts and disclosures match the new reality?

Ken Suzan: Thank you, Rolf. We have two returning guests to the IP Friday’s podcast. Joining me today is Jeanine Wright and Mark Stignani. Our topic for discussion, how is AI transforming the media and entertainment industries today? We look at the issues from differing perspectives. A bit about our guests, Jeanine Wright is a seasoned board member, CEO, global COO and CFO. She’s led organizations from startup to a $475 million plus revenue subsidiary of a public company. She excels in growth strategy, adopting innovative technologies, scaling operations and financial management. Jeanine is a media and entertainment attorney and trial litigator turned technologist and qualified financial expert. She is the co-founder and CEO of Inception Point AI, a growing company that is paving new ground with AI-generated personalities and content through developing technology and story. Mark Stignani is a partner with Barnes & Thornburg LLP and is based in Minneapolis, Minnesota. He is the chair of the data analytics department with a particular emphasis on artificial intelligence, machine learning, cryptocurrency and ESG. Mark combines the power of artificial intelligence and machine learning with his skills as a corporate and IP counsel to deliver unparalleled insights and strategies to his clients. Welcome, Jeanine and Mark to the IP Friday’s podcast.

Jeanine Wright: Thank you. Thank you. Thank you so much for having me and fun to be back. It feels nostalgic to be here.

Ken Suzan: That’s right. And you both were on the program. So it’s fantastic that you’re both back again. So our format, I’m going to ask a question to Jeanine and or Mark and sometimes to both of you. So that’s going to be how we proceed. Let’s jump right in. Jeanine, your company creates AI-generated actors. For listeners who may not be familiar, can you briefly explain what that means and what’s now possible that wasn’t even two years ago?

Jeanine Wright: Sure. Yeah, we are creating AI-generated personalities. So new characters, new personalities from scratch. We design who these personalities are and will be, how they will evolve. So we give them complex backstories. We give them hopes and dreams and aspirations. We every aspect of them, their families, how they’re going to evolve. And in the same way that, say, you know, Disney designs the character for its next animated feature or, you know, an electronic arts designs a character for its next major video game. We are doing that for these personalities and then we are launching them into the world as podcast hosts, content creators on social platforms like YouTube, Instagram and TikTok. And even in the future, you know, actors in feature length films, musicians, etc.

Ken Suzan: Very fascinating. Mark, from your practice, what’s the single biggest legal question or dispute you’re seeing clients wrestle with when it comes to AI and media creation?

Mark Stignani: Well, I think that, you know, it’s not just one thing, it’s like four things. But most of them tend to be kind of the origin story of AI data or AI tools that they use because, you know, but for the use of AI tools trained on copyrighted materials, the tools wouldn’t really exist in their current form. So a lot of my clients are wondering about, you know, can I legally use this output if it’s built upon somebody else’s IP? The second ask, the second flavor of that is really, is there liability being created if I take AI content that inadvertently infringes or defames or biases there? So there’s the whole notion of training bias from the training materials that comes out. The third phase is really, you know, can I really own this? Because much of the world does not really give IP rights into AI-generated inventions, copyrighted materials. It’s still kind of a big razor. Then at the end of the day, you know, if it’s an existing relationship, does my contract even contemplate this? So everything from authors contracts on up to just use of data rights that predate AI.

Ken Suzan: And Jeanine and Mark, a question to both of you. How would you describe where we are right now in the AI revolution in media and entertainment? Are we approaching a tipping point? And if so, what are the things we need to watch for?

Jeanine Wright: Yeah, I definitely think that we’re at a phase where people are starting to come to the realization that AI is the world’s most powerful creative tool. But that, you know, storytelling and point of view is what creates demand and audiences. And AI doesn’t threaten or change that. But it does mean that as people evolve in this medium, they’re very likely going to need to adopt, utilize and figure out how to hone their craft with these AI-generated content and these AI-generated toolings. So this is, you know, something that people have done certainly in the past in all sorts of ways in using new tools. And we’ve seen that make a significant change in the industry. So you look at, you know, the dawn of animation as a medium. You look at use of special effects, computer-generated imagery in the likes of Pixar. And this is certainly the next phase of that evolution. But because of the power of the tool and what will become the ubiquity of the tool, I think that it’s pretty revolutionary and all the more necessary for people to figure out how to embrace this as part of their creative process.

Ken Suzan: Thank you, Jeanine. Mark, your thoughts?

Mark Stignani: Yeah, I mean, I liken this to historically to like the California gold rush right now, because, you know, the technology is so far outpaced in any of the legal frameworks that are available. And so we’re just trying to shoehorn things in left and right here. So, I mean, the courts are beginning to start to engage with the foundational questions. I don’t think they’re quite there yet. I just noticed Anthropic got sued again by another group of people, big music group, because of the downloaded works they’ve done. I mean, so the courts are, you know, the courts are certainly inundated with, you know, too many of these foundational questions. Legislatively, hard to tell. I mean, federal law, the federal government is not moving uniformly on this other than to let the gold rush continue without much check and balance to it. Whereas states are now probably moving a lot faster. Colorado, Illinois, even Minnesota is attempting to craft legislation and limitations on what you can do with content and where to go with it. So, I mean, the things we need to watch for any of the fair use decisions coming out here, you know, some of the SAG-AFTRA contract clauses. And, you know, again, the federal government, I just, you know, I got a big shrug going as to what they’re actually going to come up with here in the next 90 to 100 days. So, but, you know, I think they’ll be forced into doing something sooner than later.

Ken Suzan: Okay, let’s jump into the topic of the rise of generative content pipelines. My first question to Jeanine. Studios and production companies are now building what some call generative content pipelines. This is where AI systems produce everything from scripts to visual effects to voice performances. What efficiencies and creative possibilities does this unlock for the industry?

Jeanine Wright: Yeah, so this is quite a bit of what we do. And if I could help pull the curtain back and explain a little bit.

Ken Suzan: That’d be great.

Jeanine Wright: Yeah, there’s this assumption that, you know, somebody is just sitting behind a machine pushing a button and an out pops, you know, what it is that we’re producing. There’s actually quite a bit of humans still in the loop in the process. You know, we have my team as creators. The other half of my team is the technologists. And those creators are working largely at what we describe as the the tip of the sphere. So they’re, of course, coming up with the concepts of who are these personalities? What are these personalities, characters, backgrounds going to be a lot of like rich personality development? And then they’re creating like what are the formats? What are the kind of story arcs? What is the kinds of content that this this character wants to tell? And what are the audiences they’re desiring to reach and what’s most going to resonate with them? And then what we built internally is what we refer to as an AI orchestration layer. So that allows us to pull from basically all of the different models and then all of these different really cool AI tools. And put those together in such a way and combine those in such a way that we can have the kind of output that our creative team envisions for what they want it to be. And at the end of the day, what you what the stack looks like for, say, a long form audio drama, like the combination of LLMs that we’re going to use in different parts of scripting and production and, you know, ideating and all of that. And the kinds of tooling that we use to actually make it and get it to sound good and have the kinds of personality characteristics that we want to be in an authentic voice for a podcast is going to be different than the tech stack and the tool stack that we might use for a short form Instagram beauty tip reel. And so there’s a lot of art in being able to pull all of these tools together to get them to do exactly what you want them to do. But I think the second part of your question is just as interesting as the first. I mean, what is what possibilities is this unlocking? So of course you’re finding efficiencies in the creative production process. You can move faster. You can do things were less expensive, perhaps, and you were able to do it before. But on the creator side, I think one thing that hasn’t been talked about enough is how it is really like blown wide the aperture of what creators can do and can envision. Traditionally, you know, Hollywood podcasting, many of these businesses that become big businesses have become hit making businesses where they need to focus on a very narrow of wide gen pop content that they think is going to get tens of millions, hundreds of millions in, you know, fans and dollars in revenue for every piece of content that they make. So the problem with that is, is that it really narrows the kinds of things that ultimately get made, which is why you see things happening in Hollywood, like the Blacklist, which is, you know, this famous list of really exceptional content that remains unpredited, unproduced, or why you see things like, you know, 70 to 80% of the top 100 movies being based on pre-existing IP, right? Because these are such huge bets that you need to feel very confident that you’re going to be able to get big, big audiences and big, big dollars from it. But with AI, and really lowering the barrier to entry, lowering the costs of production and marketing, the experimentation that you can do is really, really phenomenal. So, you know, my creative team, if they have an idea, they make it, you know, they don’t have to wring their hands through like a green lighting process of, you know, should we, shouldn’t we, like we, we can make an experiment with lots of different things, we can do various different versions of something. We can see what would this look like if I placed it in the 1800s, or what if I gave this character an Australian accent, and it’s just the power of being able to have this creative partner that can ideate with you and experiment with you at rocket speed. With the creators that are embracing it, you can see how it is really fun for them to be able to have this wide of a range of possibility.

Ken Suzan: Mark, when you hear about these generative pipelines, what are the immediate red flags or concerns that come to mind from a legal standpoint? How about ethics underlying all of this? Well,

Mark Stignani: that was not, that’s the number one red flag because I mean, we are seeing not just that in the entertainment industry, but it literally at political levels, and the kind of the phrase, to turn the phrase AI slop being generated, we’re seeing, you know, people’s facial expressions altered. In some cases, we’re seeing AI tools being misused to exploit various groups of individuals and genders and age groups. So I mean, there’s a whole lot of things ethically that people are using AI for that just don’t quite cover it. Especially in the entertainment industry, I mean, we’re looking at a fair amount of displacement of human workers without adequate transition support, devaluation of the creative labor. I mean, the thing though that I’m always from a technical standpoint is AI is simply a statistical average of most everything. So it kind of devalues the benefit of having a human creator, a human contribution to it. That’s the ethical side. But on the legal side, I see chain of title issues. I mean, because these are built on very questionable IP ownership stages, I mean, in most of these tools, there has been some large copying, training and taking of copyrighted materials. Is it transformational? Maybe. But there’s certainly not a chain of title, nor is there permission granted for that training. I mentioned SAG-AFTRA earlier, I think there’s a potential set of union contract aspects to this that if you know many of these agreements and use sub-licenses for authors and actor agreements, they weren’t written with AI in mind. So that’s another red flag. And also I just think in indemnification. So if we ultimately get to a point where groups are liable for using content without previous license, then who’s liable? Is the tool maker the liable group or the actual end user? So those are probably my top four red flags. But I think ethics is probably my biggest place because just because we can do something from an ethical standpoint doesn’t mean we should.

Jeanine Wright: Yeah, if I can respond to both of those points. I mean, one from a legal perspective, just to be very clear, I mean, we are always pulling from multiple different models and always pulling from multiple different sources. And we even have data sources that we license or use for single source of truth on certain pieces of information. So we’re always pulling things together from multiple different sources. We also have built into our process, you know, internal QAing and checking to make sure that we’re not misappropriating the name or likeness of any existing known personality or character. We are creating original personalities there. We design their voice from scratch. We design their look from scratch. So we’re not on our personality side, we’re not pulling or even taking inspiration from existing intellectual property that’s already out there in creating these personalities. On the ethical side, I agree. I mean, when we came out of stealth, we came out of stealth in September. There was certainly quite a bit of backlash from folks in my—I previously co-founded a company in the audio space. I mean, there’s been many rounds of layoffs in audio and in many other parts of the entertainment industry. So I’m very sensitive to the feedback around, like, is this job displacement? I mean, I do think that the CEO of NVIDIA said it right when he said, you’re likely not going to lose your job to AI, but you will lose your job to somebody who knows how to use AI. I think these tools are transforming the way that content is made and that the faster that people can embrace this tooling, the more likely they’re going to be having the kinds of roles that they want in, you know, in content creation and storytelling in the future. And we are hiring. I’m hiring AI video creators, AI audio creators. I’m hiring AI developers. So people who are looking for those roles, I mean, please reach out to me, we would love to work with you and we’d love to grow with you. We also take the ethics very seriously. For the last few months or so, I’ve met regularly with an ethicist, we talk about all sorts of issues around, you know, is designing AI-generated people, you know, good for humanity? And what about authenticity and transparency and deception, and how are we in building in this space going to avoid some of the problems that we’ve seen with things like social media and other forms of technology? So we keep that very top of mind and we try to build on our own internal values-based system and, you know, continue to elevate and include the humanity as part of the conversation.

Ken Suzan: Thank you, Jeanine. Jeanine, some argue that AI content pipelines will level the field for filmmaking, giving independent creators access to tools that were once available only to major studios. Is that the future you envision?

Jeanine Wright: I do think that with AI you will see an incredible democratization of access to technology and access to these capabilities. So I do think, you know, rise of independent filmmakers, you won’t have as many people who are sitting on a brilliant idea for the next fantastic script or movie that just cannot get it made because they will be able to with these tools, get something made and out there, at least to get the attention of somebody who could then decide that they want to invest in it at a studio kind of level in the future. The other thing that I think is really interesting is that I think, you know, AI will empower more niche content and more creators who can thrive in micro-communities. So it used to be because of this hit generation business model, everything needed to be made for the masses and a lot of content for niche audiences and micro-communities was neglected because there was just no way to make that content commercially viable. But now, if you can leverage AI—we make a pollen report podcast in 300 markets, you know, nobody would have ever made that before, but it is very valuable information, a very valuable piece of content for people who really care about the pollen in their local community. So there’s all sorts of ways that being able to leverage AI is making it more accessible both to the creator and to the audience that is looking for content that truly resonates with them.

Ken Suzan: Mark, let’s talk about the legal landscape right now. If someone creates an AI-generated performance that closely resembles a living actor without their consent, what legal recourse does that actor have?

Mark Stignani: Well, I mean, I think we can go back to the OpenAI Scarlett Johansson thing where, you know, if it’s simply—well, the “walks like a duck, quacks like a duck” type of aspect there. You know, I think it’s pretty straightforward that they need to walk it back. I mean, the US doesn’t have moral rights, really, but there’s a public visage right, if you will. And so, one of the things that I find predominantly useful here is that these actors likely have rights of publicity there, we probably have a Lanham Act false endorsement claim, and you know, again, if the performance is not parody, and it’s so close to the original performance, we probably have a copyright discussion. But again, all of these laws predate the use of AI, so we’re going to probably see new sets of law. I mean, we’re probably going to see “resurrection” frameworks, we’ll probably have frameworks for synthetic actors and likenesses, but the rules just aren’t there yet. So, unfortunately, your question is largely predictive versus well-settled at this point.

Ken Suzan: Jeanine, your company works with AI actors. How do you navigate the questions of consent and likeness compensation when creating digital performers?

Jeanine Wright: I mean, if we—so first of all, if we were to work with a person who is an existing real-life person or was an existing real-life person, then we would work with them to license their name and likeness or their voice or whatever aspects of it we were going to use in creating content in partnership with them. Not typically our business model; we are, as I said, designing all of our personalities from scratch and making all of our content originally. So, we’ve not had to do that historically. Now, you know, the flip side is: can I license my characters as if they’re similar to living characters? Like will I be able to license the name and likeness and voice of my AI-generated personalities? I think the answer is yes and we’re already starting to do that.

Ken Suzan: Let’s just switch gears into ethics and AI because I find this to be a really fascinating issue. I want to look at a hypothetical. And this is to both of you, Jeanine and Mark: an AI system creates a new performance by a beloved actor who passed away decades ago, and the actor’s estate authorizes it, but the actor was known to have expressed opposition to such technology during their lifetime. Is this ethical?

Jeanine Wright: This feels like a Gifts, Wills, and Trusts exam question.

Ken Suzan: It sounds like it, that’s right.

Jeanine Wright: Throwing me back to my law school days. Exactly. What are your thoughts? It’d be interesting to see like who has the rights there. I mean, I think if you have the legal rights, the question is around, you know, is it ethical to go against what you knew was somebody’s wishes at the time? I guess the honest answer is I don’t know. It would depend a lot on the circumstances of the case. I mean, if we were faced with a situation like that where there was a discrepancy, we would probably move away from doing that content out of respect for the deceased and out of a feeling that, you know, if this person felt strongly against it, then it would be less likely that you could make that storytelling exceptional in some way—it would color it in a way that you wouldn’t want in the outcome. And I feel like there’s—I mean, certainly going forward and it’s already happening—there are plenty of people I think who have name, likeness, and voice rights that they are ready to license that wouldn’t have this overhang.

Ken Suzan: Mark, your thoughts?

Mark Stignani: Yeah, I mean, again, I have to kind of go back to our property law—the Rule Against Perpetuities. You know, from a property standpoint to AI rights and likenesses—since most of the digital replica contracts that I’ve reviewed generally do talk about things in perpetuity. But if it’s not written down for that actor and the estate is doing this—is it ethical? You know, that is the debate.

Jeanine Wright: Well, gold star to you, Mark, for bringing up the Rule Against Perpetuities. There’s another one that I haven’t heard for many years. This is really taking me back to my law school days.

Ken Suzan: It’s a throwback.

Jeanine Wright: The other thing that’s really interesting is that this technology is really so revolutionary and new that it’s hard to even contemplate now what it is going to be in a decade, much less for people who have passed away to have contemplated what the potential for it could be today. So you could have somebody who is, perhaps, a deceased musician who expressed concerns about digital representations of themselves or digital music while they were alive. But now, the possibility is that you could recreate—certainly I could use my technology to recreate—that musician from scratch in a very detailed way, trained on tons of different available data. Not just like a digital twin or a moving image of them, but to really rebuild their personality from scratch, so that they and their music could be reintroduced to totally new generations in a very respectful and authentic way to them. It’s hard to know, with the understanding that that is possible, whether or not somebody who is deceased today would or would not agree to something like that. I mean, many of them might want, under those circumstances, for their music to live on. These deceased actors and musicians could live forever with the power of AI technology.

Mark Stignani: Yeah, I really just kind of go to the whole—is deep-faking a famous actor the best way to preserve them or keep them live? Again, that’s a bit more of an ethical question because the deep fakes are getting good enough right now to create huge problems. Even zoom meetings in Hong Kong where a CFO was on a call with five synthetic actors who all looked like his coworkers and they sent a big check out based upon that. So again, the technology is getting good enough to fool people.

Jeanine Wright: I think that’s right, Mark, but I guess I would just highlight the same way that it always has been: the ethical line isn’t AI versus human, the ethical line is about deception. Like, are you deceiving people? And if people know what it is that they’re getting and they’re choosing to engage with it, then I think it isn’t about the power of the technology. In our business, we have elected—not everybody has—but we have elected to be AI transparent. So we tell people when they listen to our show, we include it in our show notes, we include it on our socials. Even when we’re designing our characters to be very photo-realistic, we make an extra point to make sure that people know that this is AI-generated content or an AI personality. Like, our intention is not to deceive and to be candid. From a business model perspective, we don’t need to. I mean, there’s already people who know and understand that it is AI, and AI is different than people. Because it is AI, there’s all sorts of things that you can do with it that you would not be able to do with a real person. You know, we get people who ask us on the podcast side, we get all sorts of crazy funny requests. You know, people who say, “Can I text with this personality? Can I talk to them on the phone? Can they help me cook in the kitchen? Can they sing me Happy Birthday? Can they show up at my Zoom meeting today because I think my boss would love it?”

You know, all sorts of different ways that people are wanting to engage with these characters. And now we’re in the process of rolling out real-time personalities so people will be able to engage with our personalities live. It is a totally different way that people are able to engage with content, and people can, as they choose, decide what kind of content they want to engage with.

Ken Suzan: Jeanine and Mark, we’re coming to the end of this podcast. I would love to keep talking for hours but we have to stay to our timetable here. Last question: five years from now, what percentage of entertainment content do you predict will involve significant AI generation, and will audiences care about that percentage? Jeanine?

Jeanine Wright: I mean, I would say 99.9%. I mean, already you’re seeing—I think YouTube did a survey—that it was like 90% of its top creators said that they’re using AI as material components of their content creation process. So, I think this will be the default way that content is created. And content that is not made with AI, you know, there’ll be special film festivals for non-AI generated content, and that will be a special separate thing than the thing that everybody is doing now.

Ken Suzan: Mark, your thoughts?

Mark Stignani: Yeah, I go a little lower. I mean, I think Jeanine is right that we’re seeing, especially in the low-quality content creation and like the YouTube shorts and things like that, you know, there’s so much AI being pushed forward that the FTC even acquired an “AI slop” title to it. I do think that disclosure will become normalized, that the industries will be pushed to say when something is AI and what is not. And I think it’s very much like, you know, do you care about quality or not? If you value the human input or the human factor in this, there will be an upper tier where it’s “AI-free” or low AI assistant. I think that it’s going to stratify because the stuff coming through the social media platforms right now—I can’t be on it right now just because there’s so much nonsense. Even my children, who are without much AI training at all, find it just too unbelievable for them. So, I think it will become normalized, but I think that we’re going to see a bunch of tiers.

Ken Suzan: Well, Jeanine and Mark, this has been a fantastic discussion of an ever-evolving field in IP law. Thank you to both of you for spending time with us today on the IP Friday’s podcast.

Jeanine Wright: Thank you so much for having me.

Mark Stignani: Appreciate your time. Thank you again.