Panel Discussion AI and the Creative Economy

20 Feb 2026 16:00h - 17:00h

Session at a glance

Summary

This panel discussion examined the complex relationship between artificial intelligence and cultural diversity in creative industries, featuring perspectives from business, policy, and open-source communities. The central question explored whether AI strengthens or weakens global creative output, with panelists agreeing that the answer depends largely on how AI systems are designed, governed, and implemented.

Anna Tumadote from Creative Commons emphasized that outcomes depend on whether AI models are open source with transparent governance frameworks or closed and opaque systems. She noted an emerging ethical inconsistency where artists object to AI training on their work while simultaneously using AI tools trained on global content. Nicholas Granatino from Tara Gaming presented India’s unique opportunity, arguing that the country’s rich public domain heritage, particularly ancient epics like the Mahabharata and Ramayana, could provide valuable training data for AI models while allowing India to create new intellectual property layers on top of this cultural foundation.

Kenichiro Natsume from WIPO acknowledged the challenge of achieving global consensus among 194 member states on AI governance, advocating for practical technological solutions rather than lengthy international treaty negotiations. The discussion revealed significant concerns about cultural gatekeeping by major AI platforms and the potential shrinking of creative commons as creators become more restrictive with their work due to lack of consent mechanisms.

All panelists agreed that human-centered approaches should guide AI governance in creative industries, emphasizing that creativity fundamentally remains a human activity that AI should enhance rather than replace.

Keypoints

Major Discussion Points:

– AI’s Impact on Cultural Diversity: The panel explored whether AI strengthens or weakens global creative output, with consensus that the answer depends on factors like open vs. closed source models, governance frameworks, and design principles. There’s current risk of weakening diversity due to underrepresentation of certain cultures in training datasets.

– India’s Strategic Opportunity in AI: Discussion of how India’s rich public domain heritage (particularly the Itihasas – ancient epics like Mahabharata and Ramayana) could provide a competitive advantage while the US and Europe face copyright paralysis in AI training, allowing India to create new IP layers on top of public domain content.

– Global IP Framework Preparedness: Examination of whether current intellectual property systems can handle large-scale AI-generated content, with acknowledgment that achieving consensus among 194 WIPO member states for new international treaties would be extremely challenging, leading to more pragmatic technological solutions.

– Ethical Inconsistencies in AI Use: Analysis of the contradiction where artists object to AI training on their work without consent while simultaneously using AI tools trained on global datasets, highlighting the tension between individual creator rights and collective creative advancement.

– Future of Open Creative Commons: Discussion of how the open movement faces challenges from AI’s massive scale, with creators pulling back from sharing work, potentially shrinking the creative commons and breaking human-to-human collaboration that relies on copyright clarity.

Overall Purpose:

The discussion aimed to examine the intersection of artificial intelligence and intellectual property in creative industries, exploring both opportunities and challenges for global creative output, with particular focus on how different stakeholders (business, policy, and open source communities) can navigate the rapidly evolving landscape.

Overall Tone:

The discussion maintained a thoughtful, nuanced tone throughout, with panelists acknowledging complexity rather than offering simple solutions. The tone was collaborative and forward-looking, with speakers building on each other’s points. While there was underlying concern about potential negative impacts of AI on creativity and cultural diversity, the overall atmosphere remained constructive and solution-oriented, emphasizing the need for human-centered approaches and technological solutions that balance various stakeholder interests.

Speakers

– Speaker: Moderator/Host of the discussion panel

– Nicholas Granatino: Chairman of Tara Gaming, investor who sits on boards of frontier lab companies like Kivita and H company, focuses on business side and gaming industry

– Kenichiro Natsume: Assistant Director General at WIPO (World Intellectual Property Organization), works on policy side and international intellectual property matters

– Anna Tumadote: Chief Executive Officer of Creative Commons, expert in open movement and creative commons licensing

Additional speakers:

None identified beyond the speakers names list provided.

Full session report

This panel discussion brought together three distinct perspectives to examine the complex intersection of artificial intelligence and cultural diversity in creative industries. The conversation featured Anna Tumadote, CEO of Creative Commons; Kenichiro Natsume, Assistant Director General at WIPO; and Nicholas Granatino, Chairman of Tara Gaming, each offering insights from their respective domains of open-source advocacy, international policy, and business innovation.

The Fundamental Question: Does AI Strengthen or Weaken Cultural Diversity?

The central inquiry explored whether AI enhances or diminishes global creative output, with all panellists agreeing that the answer fundamentally depends on how AI systems are designed, governed, and implemented. Anna Tumadote emphasised that outcomes hinge on whether AI models are open source with transparent governance frameworks or closed and opaque systems. She noted that whilst the open movement has traditionally managed problems on the margins—what she termed “5% problems”—AI’s massive scale has transformed these marginal issues into systemic challenges that threaten the entire creative ecosystem.

Kenichiro Natsume provided a nuanced perspective from the international policy standpoint, arguing that AI represents another disruptive technology in human history, similar to previous innovations that the copyright system has successfully accommodated. However, he acknowledged the unprecedented speed differential between human and AI learning processes, noting that whilst humans have always learned by mimicking others’ work—indeed, the Japanese term for “learn” originally meant “mimic or copy”—AI accomplishes this at incomparably faster rates.

Nicholas Granatino presented perhaps the most provocative argument, introducing the concept of “Captain America hegemony” to illustrate how Western cultural dominance in digital content creates systemic biases in AI training datasets. He argued that India’s rich oral traditions, despite representing 20% of the world’s population, remain dramatically underrepresented compared to Hollywood content and AAA gaming, creating fundamental imbalances in how AI models understand and generate creative content.

India’s Strategic Opportunity in the AI Landscape

A significant portion of the discussion focused on India’s unique positioning in the global AI development race. Granatino argued that whilst the United States and Europe face “massive uncertainty” and “paralysis” regarding AI training and copyright permissions, India possesses a strategic advantage through its rich public domain heritage. The itihasas—epic narratives including the Mahabharata and Ramayana—represent cultural wisdom that remains both in the public domain and part of living tradition.

This presents what Granatino termed India’s “biggest opportunity”: the ability to create new intellectual property layers on top of established public domain content whilst the West grapples with copyright restrictions. He highlighted his collaboration with Sarvam AI to digitise this cultural heritage using OCR and voice models, potentially creating training datasets that could give India a competitive edge in AI development. The strategic value lies not merely in the content itself, but in having 20% of the world’s population actively engaged with and capable of generating rich datasets around these cultural narratives in latency space.

Global IP Framework Challenges and Pragmatic Solutions

The discussion revealed significant scepticism about the readiness of current intellectual property frameworks to handle large-scale AI-generated content. Natsume candidly acknowledged the practical impossibility of achieving consensus among WIPO’s 194 member states for comprehensive international AI treaties, describing it as “a long journey” that the international community is not yet mature enough to undertake.

Instead, WIPO is pursuing what Natsume termed a “pragmatic approach,” focusing on technological solutions rather than legal frameworks. This approach aims to create technological infrastructure that allows creators to be appropriately rewarded whilst enabling tech companies to understand what content can and cannot be used. Natsume’s frank assessment that stakeholders “don’t have to be necessarily happy very much” but should be “unhappy to some extent equally” reflects the reality of international compromise in complex technological governance.

The moderator, drawing from experience with the Broadcast Treaty negotiations, referenced President Macron’s observation that “it’s not about regulation, it’s about civilization,” highlighting the deeper cultural implications of AI governance decisions.

The Attribution Crisis and Shrinking Commons

One of the most striking aspects of the discussion was the frank acknowledgement of ethical inconsistencies within the creative community. Tumadote identified a fundamental contradiction where artists object to AI training on their work without consent whilst simultaneously using AI tools trained on global datasets. This inconsistency reflects deeper tensions between individual creator rights and collective creative advancement.

The conversation revealed that this ethical confusion is contributing to what Tumadote described as “the shrinking of the commons”—creators are becoming more restrictive with their work due to lack of consent mechanisms, which ironically damages human-to-human collaboration that relies on copyright clarity. Tumadote argued that the issue increasingly resembles a labour concern rather than a copyright problem, with creators primarily fearing replacement rather than unauthorised copying.

The lack of attribution at the inference level—where users cannot see the origins of AI-generated content—further divorces people from understanding the creative sources that inform AI outputs. Nicholas illustrated this problem with a powerful analogy about the Nobel Prize for protein folding: while the prize recognised the AI breakthrough, it overlooked the thousands of contributors to the Protein Database whose work made the AI training possible.

However, the discussion also highlighted positive examples of AI-enhanced creativity. Anna mentioned artists like Holly Herndon and Imogen Heap as pioneers who are successfully integrating AI into their creative processes whilst maintaining human agency and artistic vision.

Technological Solutions Over Legal Frameworks

The panel converged on the need for practical, technological approaches to AI governance challenges. Rather than waiting for comprehensive legal frameworks, stakeholders are exploring technological infrastructure that can provide immediate solutions. WIPO plans to launch its first meeting on this technological approach on March 17th, signalling a shift from traditional treaty-making towards more immediate, practical solutions that can evolve with the technology.

These technological solutions might include better attribution systems, consent management platforms, and reward mechanisms that can operate across different jurisdictions and legal frameworks. Rather than simple opt-in or opt-out mechanisms, Tumadote advocated for a spectrum of “yes if” conditions—creators might agree to AI training if they receive attribution, rewards, or other forms of recognition.

Business Perspectives and Investment Opportunities

From the business standpoint, Granatino expressed optimism about AI’s potential, comparing the current moment to the early internet era but noting that AI development is progressing “much faster than the internet.” He emphasised that successful AI implementation will require collaboration between technological tools and human creativity, rather than replacement of human creative processes.

The investment thesis centres on recognising that AI enhances rather than replaces human creativity, particularly in complex creative endeavours involving hundreds of people. Granatino argued that storytelling—a fundamentally human skill—will become increasingly valuable in business contexts, suggesting that the future lies in human-AI collaboration rather than competition.

Human-Centred Governance as the Core Principle

Despite the complexity of the challenges discussed, all panellists agreed on a fundamental principle: AI governance must remain human-centred. Both Natsume and Tumadote emphasised that creativity fundamentally originates from human activity, and any governance framework must preserve and enhance human agency rather than diminish it.

This human-centred approach extends beyond simple preservation of human roles to ensuring that AI development serves human flourishing and cultural diversity. The discussion suggested that successful AI governance will require maintaining space for human creativity whilst harnessing AI’s capabilities to enhance rather than replace human creative processes.

The conversation concluded with shared recognition that whilst the challenges are significant, the opportunities for positive transformation remain substantial if stakeholders can develop collaborative, human-centred approaches that preserve cultural diversity whilst harnessing AI’s creative potential. The key lies in developing technological solutions that can bridge the gap between creators’ desire for agency and the practical needs of AI development, ensuring that the future of AI serves human creativity rather than replacing it.

Session transcript

Ameet Datta

Yes. Yes. three crucial elements. I’ll start with Nicholas Granatino, who’s on the business side, the chairman of Tara Gaming. Second is Kenichiro Natsume, who is the assistant director general at WIPO on the policy side. And we have Anna Tumadote, who is the chief executive officer of Creative Commons. Since we have a half an hour, I don’t want to waste time. I have this urge to do a lot of context setting, but I will refrain. And I will jump into the first question for each of the panelists, and then we can do it more conversational. First question to each of the panelists. Anna, can we start with you? Does AI strengthen or weaken cultural diversity in the global creative output?

Anna Tumadote

It’s a good question, and I think we can just do our context setting along the way here with this. So I think this is one of those wonderful questions where the answer is going to be, it depends. It depends. Is the model open source, and we can all interrogate what’s in it and build upon it and improve it? Or is it closed source? Is the model got good governance frameworks attached to it so we can understand some of the intentions behind it or is it all very opaque? So I think ultimately it’s going to just come down to what sorts of values and design principles we’re able to instill as we build this new ecosystem.

I think currently we are at risk for a weakening.

Kenichiro Natsume

Thank you very much. My answer is not a binary answer. Because if we think about the intellectual property aspect, namely copyright, then AI is okay. AI can be used to enhance the copyright table or artworks. At the same time, that could be also kind of a threat because people can create something or generate something by using artificial intelligence. and in terms of the legal perspective or international perspective we do have a copyright system which in my personal opinion can still cope with the artificial intelligence because I think that artificial intelligence at this stage is one of the cutting edge technologies which is magnificent but one of the cutting technologies or disruptive technologies we have been experienced in the history of our human life.

Thank you.

Nicholas Granatino

Yeah. Namaste. I think I will actually give an answer which is very positive on the creativity side and that’s what we saw at Atara Gaming as an opportunity is the fact that from the web to social graph to now AI I think we always underestimate and don’t talk enough about the data and the content and the case of AI is what is called the latency space which includes the training data set. which is used for these models to respond to prompts. And if we look at the case of India, which has been mainly an oral tradition, and we look also at how much of their content have been digitized to the level of Hollywood in movies or AAA game in gaming, it is not represented.

And that has huge implication in terms of these models and whether or not they enhance creativity or whether or not they need creativity. And my answer to that is they need creativity. They need actually the wonderful epic and story and living traditions that are in the ETS, which are these Indian epics, to be represented in their data set. And at the moment, they’re not. And so the bigger question for me is how do we make sure that India, with its phenomenal history and culture and 20 % of the world population, punches at its weight? in the training data sets of these AI models. And the first work that needs to be done is a creative work.

It’s not an AI work.

Ameet Datta

You know, Nicholas, when I sent these questions, the kick I got was Nicholas pushed back happily and he gave me three questions which I told him that one of them really fired my imagination. I want to ask him about this in terms of this aspect and this whole AI IP sort of dispute in terms of the US and Europe are currently facing massive uncertainty in terms of AI training and copyright assets and permission. And that’s either, depending on who you are, it’s either stalling, you know, development, etc. You’ve said, Nicholas, that this paralysis is India’s biggest opportunity. How does India’s rich public domain heritage, the itihas, as you called it, give us a strategic edge right now?

Nicholas Granatino

Yeah, so the ETS, actually, maybe most of you know one part of the Mahabharata, which is one of the ETS. The second one is the Ramayana. The one I’m referring to is the Gita. And so maybe most of you are more familiar with the Gita, which is actually just a short part of the Mahabharata. These are epics that are thousands of years old. What’s phenomenal about them is they are in the public domain, but they are still living tradition. Parents and grandparents still tell their children about Lord Ram, about Ravan, about Hanuman. Prime Minister Modi speaks about it all the time as well. And they are in the public domain. And the reason, and nobody has actually done any work with them and created any IP on top of that, the quality we’re looking to do at Tara Gaming.

And so there is basically a data set. And what’s really exciting about Sarvam AI is that they’re actually going to help. to actually digitize with their OCR model, with their voice model, all this culture which is in the public domain and which can enter through SARVAM and through the works that we’re doing, actually the data set to train. And that creates an opportunity, I think, which is quite unique. And the second layer is the fact that you have 20 % of the world population here in India to talk about it and create rich data sets about that.

Ameet Datta

And the interesting point is that on this public domain content and body of work, you have this opportunity to create IP. And Ken, the question is for you. Is the global IP framework prepared for large -scale AI -generated content today?

Kenichiro Natsume

Thank you very much for the very interesting but big question. It’s not very easy to answer in a short time, but let me try. Because I… Artificial intelligence, particularly in the area of the creative industry, of course, it’s changing the work of the artists and creators. and I’ve been discussing with let’s say in India for example taking advantage of my visit to Delhi meeting with different stakeholders publishers music industry or tech industries and the views are very much different it’s no secret and you know that the views are very much different that’s the reality in front of us and even among the same segment for example publishers there are different views and for example artists, one of my friend artists, she’s using AI to create digital art at the same time the other artists are kind of feeling threatened by the generation of the artwork or the output generated by so called generative AI so it’s not very straightforward and the reality in front of us is that it’s not There are very much different views and it’s not so easy to find a common denominator because the views are so different.

It’s not something like zero and one and let’s see 0 .5. It’s not like a mathematic. So if we see about the intellectual property system, at this stage our view is the following because that we, WIPO, as a UN international organization sometimes are asked that, hey WIPO, why don’t you think about making some rules or regulations, international treaty of AI and intellectual property. Not sounds bad, but how long does it take? We have 194 member states. Our principle is consensus. Okay. So 194, meaning 194 member states, including of course India, should agree upon one common thing. and just to be frank with you, don’t quote me, it’s a long journey. Sounds relatively easy. Yes, yes.

So our approach is more pragmatic. Okay, we can think of something, legal framework, but let’s put it aside because it’s not, the international scene is not matured enough. It’s not ready enough. So our idea is let’s think about something more practical, more technological, to see if there is any technological solution possible so that both creators’ side and industry side, tech industry side, can live with. I would say can live with. They don’t have to be necessarily happy very much. They have to be unhappy to some extent equally. They have to compromise each other. But it’s not an international legal negotiation. It’s a collaboration or cooperation explore to find some technological infrastructure where people can live with us so that creators can be benefited or remunerated as well as tech industries can utilize those products.

Thank you.

Ameet Datta

Anna, you know one of the things Ken said is an artist and use AI to create artworks and you have artists today and if I look at the music industry film industry you have composers who use AI to generate production music and a lot of musical works maybe not declared or otherwise but it’s a huge industry but at the same time the creator voice often complains about the lack of consent in AI training whereas most of them work on AI models which have trained on a worldwide corpus of data and content. Do you see a sort of ethical or rational inconsistency here in this sort of kind of use and objection or what do you think is the correct position?

Anna Tumadote

Is there an ethical inconsistency? Yes, yes is the answer. It’s funny that you get the, hey, WIPO, can you fix this? Because Creative Commons gets that from time to time, too. In fact, in the early days of generative AI, we were getting a, hey, Creative Commons, can you fix AI for us? We’re like, okay, which direction are we going to fix it in? I’m just kidding. We never suggested that we would actually fix it. But it actually comes down to this question that you were asking. So, you know, here we have the world’s creativity that has been scraped, crawled, trolled, whatever, you know, however you want to describe it. And we built these massive foundation models.

And the, you know, the sort of relative weight of every individual work in there is infinitesimal. It’s tiny. It’s tiny. The bigger concern is what does use of these technologies do to the creative industries, right? It’s more a fear of, like, replacement. It’s a labor issue. It actually feels increasingly less. Like a copyright issue when we’re talking about some of these considerations. But then there’s that layer on top in the sort of inference level where. you know, you’re querying, like, tell me, you know, tell me a story about this, you know, tell me, tell me, you know, about a certain concept, or whatever the case may be, and we’re not seeing where that information is coming from, right?

So, we’re sort of divorced from where the origin of the creativity, or the knowledge, or whatever it was, came from, and that, I think, is going to be a longer -term problem for these tools, because you’re not really going to trust in how they work, and you see it show up similarly with the artistry piece, right? So, we have artists who have always embraced the free culture movement, you know, give things over to the public domain, or give things over with a creative commons license, and are enthusiastically experimenting with these technologies. We have artists, too, who have, like, vast bodies of work, where they’re building their own models, and so they’re just enhancing their own craft.

So, interesting examples to look at would be Holly Herndon and Imogen Heap, who’ve, like, really been on the forefront of this, um, but at the same time, it was to your point, you know, there are artists who are playing with this, but are like, no, no, no, anything that I create, that’s mine, but I’m going to use all the world’s creativity here freely, and we have to find some kind of a middle ground in this, because Ultimately, all knowledge builds on prior knowledge. All creativity builds on prior creativity. The richness of the public domain, like Nicholas was talking about, you can walk into any museum and be inspired. You don’t have to go, I saw this work and that work and that work and that work and that work, and now I’ve sketched this drawing.

But there is something with the technological layer where if you are fusing together different things or asking for certain styles or certain inspirations or so on, there really should be some sort of form of credit given.

Ameet Datta

Please, Nicholas.

Nicholas Granatino

Yeah, I mean, I think everybody has celebrated, including the Nobel Committee, the work of Demis Hassabis at DeepMind on protein folding. But the reality is there have been actually scientists which have been for 50 years putting their crystal structure of proteins into a database called the Protein Database. I think it would have been nice of the Nobel Committee to also include the protein data bank as a recipient of that Nobel Prize. And actually, the data has always been put under the carpet. I mean, a lot of the big tech is saying content is free, what people pay for is search, tech, AI, whatever it is, the link, the graph, the link graph, the social graph, and now the AI model.

And so, the question they want to pose is, do you want AI as a society to have the best data? And the answer is probably yes on the condition that you are open, but if you are going to make money at the gateway of the chat or whatever is your application, and you’re going to assume that everybody works for you, I don’t think society wants that. President Macron yesterday talked about it’s not about regulation, it’s about civilization. And I think it’s, as a civilization, what do we want as a future? How much do we want to rework the work of these protein crystallographers, of these creatives, etc.? That’s the real question.

Ameet Datta

Please, Ken.

Kenichiro Natsume

Just one quick note. Anna’s comment was very touching to me because you mentioned it. we human beings refer to or learn from the other person’s creative work, which is true. I’m a Japanese, and the Japanese term of learn originally meant mimic or copy. So the learning is starting from to look at some other person’s work and try to imitate, and based on that we develop our own flavor or texture. And this has been done by human beings for ages. The big difference is that if it’s done by human, it takes time. But if it’s done by computer, it takes very, very limited time. And that’s a big difference. So what it’s doing is essentially more or less the same, but the speed is completely different.

And maybe we have to draw a line. This is what exactly Anaba was saying. And the answer, where do we have to draw a line? Is a difficult question.

Anna Tumadote

You know, it’s so funny you say that because even in the open movement and in the open knowledge communities, we’ve had problems for years, but they’ve been problems on the margins, right? They’ve been the sort of 5 % problem, and we’ve thought to ourselves, you know, this is 95 % good, and so that’s good enough. But AI comes along, and the scale is so massive that now you have to grapple with this. So, for instance, like, what if you’ve shared your work freely, and then it’s used for nefarious purposes? Nobody wants that. Like, that’s the sort of, like, another ethical conundrum that you face. But copyright is not built to handle that. Like, society ideally would find ways around that.

Maybe there’s normative frameworks we need to introduce. Maybe we need to think about sort of different legal or technical solutions to this because the scale is just so extreme.

Ameet Datta

So, Ana, is the open movement something that can withstand this, the AI onslaught or the spread of AI? Is it structured to do that, or would it have the same challenges that, let me call it the proprietary copyright model as the traditional… The traditional copyright model.

Anna Tumadote

I think there’s a transformation that’s going to have to happen because I think what we’re actively seeing is people pulling back from sharing their works because, you know, for whatever, you know, if they have no consent or, you know, consent mechanism or no agency over how it’s used, they’re going to probably do the only thing that they can in that situation and either take it back or put it behind a wall or try to make you pay for it or, you know, any of these other levers that they can pull. And we are actively seeing the shrinking of the commons already. Like, this is a really bad outcome. And here’s the real kicker when we’re talking about the sort of humans have been doing this for a long time.

Like, human -to -human collaboration relies on copyright clarity, on the CC licenses, on this ability that, like, if I write something, you know what you can do with it because it’s under this license and so on and so forth. But now we’re seeing creators say, no, no, I’m going to go more restrictive. And that breaks the human collaboration element. So there’s all these downstream negative consequences from this. So I think we can withstand it, but I think collectively we have to reckon with the fact that there is a problem. and the scale is so magnificent that we can’t just stick our fingers in our ears and say, you know, ultimately this is in the public interest.

It’s not going to be that way because if nobody shares, then there’s nothing left for us.

Ameet Datta

You know, Nicholas, to your point on the opportunity for India and the use of ethos and public domain, but, you know, being the opportunity for India to create that IP layer, isn’t there also the danger that we might slip into this cultural gatekeeping by a handful of AI platforms? Is that then an overwhelming danger as well?

Nicholas Granatino

Yeah, absolutely. I mean, I think, you know, Europe and Mistral are pushing a lot for, you know, open source, and China is pushing a lot also in the open source community. But that’s just a layer above of what I think we’re talking about here. today. There’s something I call the Captain America hegemony, which is basically we all grew up in France, in India, anywhere with Captain America as being this kind of powerful with all the weapons, all the defense mechanism, etc. And if you actually have open source, you just have a gateway which is free to steal a corpus of creativity, which is in this Captain America hegemony. And I think what we want is we have to remember that AI is just on top of something that has been done, and so the creative process is not really part of that.

It’s above language, it’s above image, etc. And we know that everybody agrees in the AI community there’s actually two, three things that need to happen to reach AGI. And those two, three things probably overlap with a lot of the creativity that makes us unique and allow us to make this corpus that AI will continue to be trained of. So I’m quite optimistic because there is things that is pre – art, whether it’s text, whether it’s image, whether it’s video, whether it’s game, you know, that is still a creative process. Sometimes that involves hundreds of people. And that you’re not going to, it’s not that you’re going to have agents speaking to each other and creating a game.

We’re very far from that.

Ameet Datta

Ken, you know, to your point on we need to find a middle ground, is this, realistically, is this a level and as a copyright lawyer, the Berne Convention, Rome, the whole push to sort of a harmonized, largely sort of co -existent copyright model across the world, has generally worked. The one exception being the Broadcast Treaty, which I started working when I was a young associate and it’s still being discussed and I love those documents because I see how that conversation has changed. But is, in the context of IP and AI, is global harmonization realistic or is fragmentation something? you know that we’ll all have to live with

Kenichiro Natsume

i wish i could immediately say yes however the reality is as i mentioned briefly before that having a consensus with 194 member states including this country and big other countries is not always easy so that’s why we are opting at this stage for a little bit softer approach so that the technique technological solution or technological platform or technological infrastructure could actually solve the issues where creators can be rewarded or remunerated appropriately where the tech companies can easily recognize what is opted in what is opted out what is the artwork made by generated by the artificial intelligence what is done by the human being so that they can understand what can be done and what cannot be done.

So that’s the approach we are taking place. And just for your information, we will launch the first meeting of that next month, March 17th, which is available online. So please stay tuned. Thank you.

Anna Tumadote

Oh, it’s in our calendar. Yeah. Great, thank you very much. Yeah, we’ll be there because I was thinking about this sort of global standard and framework question. And one of the things that we’ve tried to do with the Creative Commons community is think about, all right, what are the things that everybody wants in this moment? What are the choices they want? And what are the sort of conditions under which they would share, right? And you can imagine it going everywhere from, to your point, like in the EU, there’s the opt -out. It’s like, no, I’m not interested in this. Very important that we maintain limitations and exceptions there, though, for research. All the way to the full yes, because maybe there’s a world where people are like, put me in, put me in and tell people who I am.

But somewhere in between there, there’s a yes if. yes if you reward me, yes if you attribute me, yes if you contribute to this project, yes if you support the open infrastructure etc. and I think we just have to get a lot more sort of creative and nuanced in that spectrum.

Ameet Datta

I sense that at least for the short -term countries are going to try to find their own you know sort of policy solutions given and hopefully and I would hope that the intention is to harmonize as much as possible because I think the implications of just the AI business across the world require harmonization and scream for harmonization and so will businesses that use those models to create more IP or IP -like content. Nicholas you sit on these boards of companies frontier lab companies like Kivita and H company if there’s one mandate to Indian investors or something like that, what would you say? I think there’s a lot of work and creators in this room you want to give to ensure that we aren’t India is just not consumer of AI 2030, what would that be?

Nicholas Granatino

No, I think as an investor, it’s a tremendous time. I mean, I think it feels like the internet all over again. I think there’s lots of opportunity. It’s moving very fast, you know, much faster than the internet. So it’s a bit, you know, difficult to pack the right opportunity. But I think it’s going to be a collaboration with these wonderful, you know, tools that we have and human creativity. And that is going to stay. I mean, some people say storytelling is going to be the main skill in business. That is very much a human inequality. So the future is bright.

Ameet Datta

I’m seeing this big flashing red sign which says time’s up. I don’t know, mine or the panel’s. I’m hoping it’s only the panel’s. But I’m going to do a little Don Quater thing and do one last question in terms of what single principle should guide international AI governance in the creative industries over the next decade? Ken? Ken?

Kenichiro Natsume

That’s a big question. It says time’s up, so let me do it very briefly. I think we should put human -centered approach because still creativity comes from human beings’ activity, not from the artificial intelligence. So this is one fundamental which I should take. Thank you.

Anna Tumadote

I’ll just say plus one. Just keep the humans. Keep the humans at the center.

Ameet Datta

Insightful answer as always. Thank you. Thank you to the panel. Thank you to this very engaging audience. Thank you for listening to us.

Anna Tumadote

Speech speed

198 words per minute

Speech length

Guiding principle for international AI governance in creative industries

Topics

Human rights and the ethical dimensions of the information society | Artificial intelligence

Kenichiro Natsume

Speech speed

133 words per minute

Speech length

Guiding principle for international AI governance in creative industries

Topics

Human rights and the ethical dimensions of the information society | Artificial intelligence

Nicholas Granatino

Speech speed

163 words per minute

Speech length

India’s strategic opportunity and investment in AI‑driven creative sector

Topics

Data governance | Social and economic development | Artificial intelligence

Ameet Datta

Speech speed

Default speed

Speech length

Default length

Speech time

Default duration

Questioning global IP framework readiness

Explanation

Ameet asks whether the current international IP system can handle large‑scale AI‑generated content and whether global harmonisation is realistic, highlighting the need for coordinated policy responses.

Evidence

“Is the global IP framework prepared for large -scale AI -generated content today?” [27] “But is, in the context of IP and AI, is global harmonization realistic or is fragmentation something?” [46] “I sense that at least for the short -term countries are going to try to find their own you know sort of policy solutions … I would hope that the intention is to harmonize as much as possible because I think the implications of just the AI business across the world require harmonization…” [47].

Major discussion point

Readiness of the IP framework for AI‑generated content

Topics

The enabling environment for digital development | Artificial intelligence

Agreements

Artificial intelligence | Data governance | The enabling environment for digital development

Artificial intelligence | Social and economic development | Information and communication technologies for development

Unexpected consensus

Acknowledgment of ethical inconsistencies in creator behavior

Speakers

– Anna Tumadote
– Speaker

Arguments

There is ethical inconsistency when artists use AI trained on global content while objecting to their own work being used without consent

The music and film industries extensively use AI for production while creators simultaneously object to AI training on their works

Explanation

It’s unexpected that both a Creative Commons CEO and a moderator would openly acknowledge and criticize the contradictory behavior of creators who use AI while objecting to AI training on their work. This honest assessment of ethical inconsistencies within the creative community shows remarkable candor

Topics

Artificial intelligence | Human rights and the ethical dimensions of the information society | The digital economy

Optimism about AI-human collaboration despite challenges

Speakers

– Nicholas Granatino
– Anna Tumadote
– Kenichiro Natsume

Arguments

Creative processes involving hundreds of people remain essential and cannot be replaced by AI agents

The open movement faces transformation as creators restrict sharing due to lack of consent mechanisms, breaking human collaboration

Human-centered approach should guide AI governance since creativity fundamentally comes from human activity

Explanation

Despite discussing numerous challenges and risks, all speakers maintain optimism about the future of human creativity and AI collaboration. This consensus on maintaining human centrality while embracing technological advancement is unexpected given the severity of the challenges they identify

Topics

Artificial intelligence | Human rights and the ethical dimensions of the information society | Social and economic development

Overall assessment

Summary

The speakers demonstrate strong consensus on fundamental principles: human-centered AI governance, the need for practical technological solutions over lengthy legal processes, recognition of ethical inconsistencies in current practices, and the importance of cultural diversity in AI development. They agree on both the challenges (scale, speed, cultural hegemony) and opportunities (public domain heritage, collaboration potential) presented by AI.

Consensus level

High level of consensus on core principles and problem identification, with complementary rather than conflicting perspectives. The agreement spans across different stakeholder types (business, policy, advocacy) and suggests a mature understanding of AI governance challenges. This consensus provides a strong foundation for collaborative approaches to AI governance in creative industries, though implementation details may still require negotiation.

Differences

Artificial intelligence | Human rights and the ethical dimensions of the information society | Social and economic development

Unexpected differences

Role of open source in addressing cultural representation

Speakers

– Nicholas Granatino
– Anna Tumadote

Arguments

Danger of cultural gatekeeping by handful of AI platforms, even with open source models built on culturally hegemonic content

AI’s impact depends on whether models are open source with good governance or closed and opaque; currently at risk of weakening diversity

Explanation

This disagreement is unexpected because both speakers generally support open approaches, but Nicholas argues that open source doesn’t solve the fundamental problem of cultural bias in training data (Captain America hegemony), while Anna sees open source with good governance as a potential solution to strengthen diversity.

Topics

Artificial intelligence | Social and economic development | Closing all digital divides

Effectiveness of current copyright systems for AI

Speakers

– Kenichiro Natsume
– Anna Tumadote

Arguments

AI can enhance copyrighted artworks but also poses threats; copyright system can still cope with AI as another disruptive technology

AI’s massive scale transforms marginal problems into major issues; people are pulling back from sharing, shrinking the commons

Explanation

Unexpected because both are IP/legal experts but have fundamentally different assessments. Kenichiro believes existing copyright systems can handle AI as they have other disruptive technologies, while Anna argues that AI’s scale has fundamentally changed the nature of the problems beyond what copyright can handle.

Topics

Artificial intelligence | Human rights and the ethical dimensions of the information society | Data governance

Overall assessment

Summary

The speakers show significant disagreement on fundamental approaches to AI governance, the adequacy of existing legal frameworks, and the level of optimism about AI’s impact on creativity and cultural diversity. While they agree on keeping humans central, they diverge sharply on implementation strategies and urgency of concerns.

Disagreement level

Moderate to high disagreement with significant implications for AI governance approaches. The disagreements suggest that stakeholders are still far from consensus on basic questions about whether existing systems can handle AI’s challenges, whether technological or legal solutions are preferable, and how urgent the threats to creative ecosystems really are. This level of disagreement could lead to fragmented approaches and delayed coordinated responses to AI governance challenges.

Partial agreements

All speakers agree that humans should remain central to AI governance and that human creativity is fundamental. However, they disagree on implementation approaches – Kenichiro favors technological solutions, Anna advocates for nuanced legal frameworks, and Nicholas focuses on cultural representation and investment opportunities.

Speakers

– Anna Tumadote
– Kenichiro Natsume
– Nicholas Granatino

Arguments

Keeping humans at the center of AI development and governance

Human-centered approach should guide AI governance since creativity fundamentally comes from human activity

Creative processes involving hundreds of people remain essential and cannot be replaced by AI agents

Topics

Artificial intelligence | Human rights and the ethical dimensions of the information society

Both speakers acknowledge ethical inconsistencies in how creators use AI while objecting to AI training on their work. However, Anna focuses on the labor and replacement concerns versus copyright issues, while Nicholas emphasizes the need for recognition and reward of data contributors.

Speakers

– Anna Tumadote
– Nicholas Granatino

Arguments

There is ethical inconsistency when artists use AI trained on global content while objecting to their own work being used without consent

Society should recognize and reward data contributors; the question is whether we want open AI with best data or closed systems profiting from others’ work

Topics

Artificial intelligence | Human rights and the ethical dimensions of the information society | Data governance

Both acknowledge the need for coordinated approaches but disagree on feasibility and methods. The Speaker emphasizes harmonization as essential for business operations, while Kenichiro argues it’s unrealistic through traditional treaty-making and advocates for pragmatic technological solutions.

Speakers

– Kenichiro Natsume
– Speaker

Arguments

Global consensus among 194 countries is unrealistic; WIPO pursuing technological infrastructure solutions for March 2024 launch

Global harmonization in AI governance is essential for business operations and should be the goal despite current fragmentation trends

Topics

Artificial intelligence | The enabling environment for digital development

Artificial intelligence | Social and economic development | Information and communication technologies for development

Takeaways

Key takeaways

AI’s impact on cultural diversity depends on whether models are open source with good governance or closed and opaque, with current risk of weakening diversity

India has a strategic opportunity to leverage its rich public domain heritage (itihas/epics) while US and Europe face copyright paralysis

Global IP frameworks are not ready for AI-generated content due to vastly different stakeholder views and the impracticality of achieving consensus among 194 WIPO member states

There are ethical inconsistencies when creators use AI trained on global content while objecting to their own work being used without consent

The fundamental difference between human and AI learning is speed – AI processes at unprecedented scale compared to human learning timelines

The open movement faces transformation as creators restrict sharing due to lack of consent mechanisms, leading to shrinking of the commons

Human-centered approach should guide AI governance since creativity fundamentally comes from human activity

AI represents tremendous investment opportunities similar to early internet, requiring collaboration between AI tools and human creativity

Resolutions and action items

WIPO will launch first meeting of technological infrastructure solution approach on March 17th (available online)

Focus on developing technological platforms that help creators get rewarded while allowing tech companies to understand what content can be used

Creative Commons and other stakeholders to participate in WIPO’s March meeting

Unresolved issues

Where to draw the line between acceptable AI learning and human learning given the speed difference

How to achieve global harmonization vs accepting fragmentation in AI governance approaches

How to prevent cultural gatekeeping by handful of AI platforms while maintaining open innovation

How to balance creator consent and attribution with the practical needs of AI development

How to maintain human collaboration when creators are becoming more restrictive with sharing

How to ensure diverse cultural content (like India’s traditions) gets properly represented in AI training datasets

How to reward data contributors and original creators in AI systems

Suggested compromises

WIPO’s pragmatic approach focusing on technological solutions rather than legal frameworks to help creators and tech industries ‘live with’ each other

Creating a spectrum of sharing conditions from opt-out to conditional sharing with attribution, rewards, or other requirements (‘yes if’ approach)

Technological infrastructure where creators can be appropriately rewarded while tech companies can easily recognize what is opted in/out

This comment is refreshingly honest about the realities of international consensus-building and offers a pragmatic alternative to waiting for perfect legal frameworks. The phrase ‘unhappy to some extent equally’ captures the essence of workable compromise.

Impact

This shifted the conversation away from idealistic solutions toward practical interim measures. It influenced Anna’s subsequent discussion of the ‘yes if’ framework and demonstrated that technological solutions might bridge gaps that legal frameworks cannot currently address.

Overall assessment

Explanation

This seeks concrete recommendations for positioning India as an AI creator and innovator rather than merely a consumer market

Disclaimer: This is not an official session record. DiploAI generates these resources from audiovisual recordings, and they are presented as-is, including potential errors. Due to logistical challenges, such as discrepancies in audio/video or transcripts, names may be misspelled. We strive for accuracy to the best of our ability.