ArtsEnvoy.ai / Arts & Culture Working Group

A successful first Global Dialogue on AI Governance must do more than convene voices—it must change who is heard, who is valued, and who shapes what comes next. We are at an inflection point. AI is not only a technical system—it is a cultural force, reshaping how stories are told, how identities are formed, and how value is created. And yet, many of those whose work and data power these systems remain on the margins of the very structures designed to govern them. Success, therefore, begins with recognition—of creators, artists, and young people not as outputs of the system, but as contributors to its design. It requires governance that can move at the speed of change. Static models cannot keep pace with exponential technologies. More adaptive structures—such as rotating seats or living working groups—are essential to ensure that emerging voices and realities are not locked out of decision-making. It also requires a shift from extraction to equity. The creative economy has already contributed—often invisibly—to the foundations of AI. A just future demands frameworks, such as creator data sovereignty, that restore agency, consent, and value to those contributions. But above all, success will be measured by whether this Dialogue redistributes authorship. Not just of content—but of power. Because the future of AI will not only be built by those who engineer it, but by those who imagine it, challenge it, and live within its consequences. And governance must reflect that truth.

• Social, economic, ethical, cultural, linguistic and technical implications of AI
• Protection and promotion of human rights
• Transparency, accountability, and human oversight
• AI capacity-building

My priorities focus on ensuring that AI governance reflects the full spectrum of human, cultural, and economic realities shaping and shaped by these technologies. First, the social, cultural, and economic implications of AI are central. AI systems are not only technical infrastructures, but cultural ones-shaping narratives, identities, and creative expression at scale. Yet the creative economy, a multi-trillion-dollar sector and a major contributor to AI training data, remains underrepresented in governance discussions. Second, the protection and promotion of human rights must include the rights of creators and cultural workers. This includes questions of ownership, consent, attribution, and fair compensation in the use of creative work within AI systems. Third, transparency, accountability, and human oversight are essential to ensure that the data and systems underpinning AI are developed and deployed responsibly. This includes greater visibility into how creative data is sourced, used, and monetized. Finally, AI capacity-building is critical to ensure that artists, creators, and communities-particularly in the Global South-are not only users of AI, but active participants in shaping its development and governance. Together, these priorities support a more inclusive, equitable, and culturally informed approach to AI governance-one that recognizes creators not as peripheral stakeholders, but as central contributors to the AI ecosystem.

One critical cross-cutting issue not fully captured in the current thematic areas is what I'm focused on - creator data sovereignty-the right of artists and creators to have agency, recognition, and fair participation in how their work is used within AI systems. As generative AI advances, vast amounts of creative work-often sourced without consent, compensation, or attribution-are being used to train models that generate new cultural and economic value. This raises urgent questions not only of intellectual property, but of labor, identity, and ownership in the digital age. Closely linked to this is the broader issue of creative labor and value in AI ecosystems. While other sectors are actively shaping governance frameworks that affect them, creators are often positioned as outputs rather than decision-makers. This creates a structural imbalance in how value is distributed and whose interests are prioritized. Another emerging issue is the governance of cultural and narrative systems. AI is increasingly shaping how stories are told, whose voices are amplified, and how communities are represented. This has profound implications for cultural diversity, linguistic inclusion, and narrative sovereignty-particularly for underrepresented regions and communities. Addressing these issues requires moving beyond traditional governance models to include those with lived experience in cultural production. Without this, AI risks reinforcing existing inequities at scale.

In the creative sector, particularly across Africa and other underrepresented regions, current AI governance gaps are already having tangible impacts on livelihoods, ownership, and participation. One of the most significant challenges is the widespread use of creative work in training AI systems without clear frameworks for consent, compensation, or attribution. Artists, writers, and cultural producers—many of whom operate in informal or under-resourced economies—are contributing to AI ecosystems without recognition or economic return. This risks deepening existing inequalities and reinforcing extractive dynamics between global technology platforms and local creative communities. A second challenge is the lack of meaningful representation in governance spaces. While AI is rapidly shaping cultural production and storytelling, creators are often excluded from decision-making processes, limiting the ability of policies to reflect lived realities, cultural nuance, and regional priorities. At the same time, there are significant opportunities. AI has the potential to democratize access to creative tools, expand global visibility for artists, and unlock new forms of storytelling and income generation—particularly for youth and creators in the Global South. With the right governance frameworks, AI can support more inclusive creative economies and amplify diverse voices that have historically been underrepresented. There is also an opportunity to build new models of value and participation—such as creator data sovereignty frameworks—that ensure artists are not only users of AI, but active stakeholders in how it is developed and governed. Addressing these gaps now is critical to ensuring that AI strengthens, rather than undermines, the creative economies and cultural ecosystems it increasingly depends on.

The Global Dialogue on AI Governance can play a critical role in moving international cooperation from fragmented discussions toward more inclusive, coordinated, and action-oriented frameworks. At present, AI governance is being shaped across multiple spaces—technical, regulatory, and industry-led—often without sufficient alignment or inclusion of all affected stakeholders. The Dialogue can serve as a bridge, bringing together Member States, the private sector, civil society, and underrepresented communities into a shared space for shaping common principles and priorities. Importantly, the Dialogue can expand the definition of who is considered a stakeholder in AI governance. By formally including groups such as artists, creators, and young people—whose work, data, and livelihoods are directly shaping AI systems—it can help ensure that governance reflects not only technical considerations, but also cultural, social, and economic realities. The Dialogue also has the opportunity to foster more adaptive and responsive governance mechanisms. In a rapidly evolving technological landscape, international cooperation must be dynamic. Models such as rotating participation or thematic working groups can support continuous input, rather than static representation. Finally, the Dialogue can help translate global principles into practical pathways for implementation. By connecting policy discussions with real-world initiatives and partnerships, it can support the development of governance approaches that are not only inclusive in theory, but actionable in practice. In this way, the Global Dialogue can move beyond coordination toward meaningful cooperation—helping to shape AI governance that is equitable, culturally informed, and globally relevant.

The Global Dialogue on AI Governance can build upon a growing ecosystem of international initiatives, partnerships, and frameworks that are shaping the AI landscape, including efforts across the United Nations system, multilateral platforms, and civil society. At the same time, there is a critical gap in whose knowledge is being elevated within these processes. In addition to technical and policy-driven frameworks, the Dialogue should actively engage with resources and insights generated by artists and creators themselves. Initiatives such as the We, the Artists reports developed by the Arts & Culture Working Group for global convenings including the High-Level Political Forum and COP29 offer grounded, lived perspectives on how creative communities are experiencing and responding to technological change. These types of contributions represent an important and often overlooked form of expertise—one that reflects cultural, social, and economic realities that are not always captured through traditional policy or academic lenses. The added value of the Global Dialogue lies in its ability to integrate these diverse knowledge systems into a more inclusive and coherent global framework. By doing so, it can move beyond siloed approaches and ensure that governance reflects not only technical and regulatory considerations, but also the lived experiences of those directly impacted. In addition, the Dialogue can help bridge the gap between principle and practice by supporting cross-sector collaboration between policymakers, technologists, and creative practitioners. This is particularly important in emerging areas such as creator data sovereignty, where frameworks are still being defined. By elevating artist-led insights alongside existing initiatives, the Global Dialogue can help shape a more inclusive, responsive, and culturally grounded approach to AI governance.

Different stakeholders can contribute most effectively to the AI Dialogue when their roles move beyond consultation toward co-creation. Member States and international organizations can provide policy direction and alignment with global frameworks. The private sector can contribute technical expertise and implementation pathways. Civil society and academia can offer critical analysis, research, and accountability. However, stakeholders such as artists, creators, and youth—whose work, data, and lived experiences are directly shaping AI systems—must be engaged not only as participants, but as contributors to governance design. To support this, the Dialogue should adopt a more dynamic and inclusive structure. This could include rotating participation models or dedicated working groups that ensure underrepresented voices are continuously integrated, rather than limited to one-off interventions. In addition, thematic tracks should reflect both technical and cultural dimensions of AI, allowing for interdisciplinary exchange between sectors that do not typically engage with one another. Finally, the Dialogue should incorporate mechanisms for ongoing input beyond the event itself, such as open submissions, collaborative platforms, and follow-up working sessions. This would ensure that contributions are not only heard, but carried forward into actionable outcomes. By structuring participation in this way, the Dialogue can shift from a model of representation to one of shared responsibility in shaping AI governance.

Several key voices remain underrepresented in global AI governance discussions, particularly those whose work and livelihoods are already deeply entangled with AI systems. These include artists, creators, and cultural practitioners, whose work is frequently used to train AI models, yet who are rarely included in decisions about how these systems are developed or governed. Similarly, youth—who are both primary users and future shapers of AI—often lack meaningful avenues for participation. Indigenous communities and Global South stakeholders are also underrepresented, despite being disproportionately affected by both the risks and opportunities of AI, particularly in areas such as data extraction, cultural representation, and digital access. These gaps are not only issues of inclusion, but of governance effectiveness. Without these perspectives, policies risk overlooking cultural nuance, reinforcing inequities, and failing to address real-world impacts. To address this, inclusion must move beyond symbolic participation. Mechanisms such as rotating seats, dedicated working groups, and formal recognition of stakeholder coalitions—such as those representing the creative sector—can support sustained and meaningful engagement. In addition, new pathways for contribution should be established, including open calls, artist-led reports, and community-driven inputs that reflect lived experience. Ensuring these voices are included is not only a matter of equity—it is essential to building AI governance that is legitimate, responsive, and globally relevant.

To foster meaningful and dynamic engagement, the AI Dialogue should move beyond traditional panel formats and incorporate more participatory, practice-based approaches. One approach is to integrate creative and experiential formats alongside policy discussions. For example, AI-generated storytelling, visual narratives, or short films based on real-world data can help translate complex issues into accessible and emotionally resonant forms, enabling broader understanding and engagement across diverse stakeholders. Interactive formats such as co-creation labs or design sprints can also be valuable. These spaces allow participants from different sectors—policy, technology, and creative industries—to collaboratively develop solutions, frameworks, or prototypes in real time. In addition, small-group dialogues or "listening sessions" with underrepresented communities can create space for more candid, grounded input that may not emerge in formal plenary settings. Digital engagement tools should also be leveraged to expand participation beyond those physically or virtually present, enabling ongoing contributions before, during, and after the Dialogue. Finally, incorporating outputs that are both analytical and creative—such as artist-led reports, narrative briefs, or multimedia summaries—can help ensure that insights are communicated in ways that are both rigorous and widely accessible. By combining traditional policy dialogue with creative and participatory formats, the AI Dialogue can foster deeper engagement, stronger collaboration, and more impactful outcomes.

Effective AI governance is emerging not only through formal policy frameworks, but through practice-based approaches that integrate technical, cultural, and human-centered perspectives. One important foundation is the development of ethical AI frameworks grounded in human rights, transparency, and accountability. However, these frameworks are most effective when paired with real-world application and meaningful participation from those directly impacted. In my recent article published in the UN Chronicle, I explore the role of storytelling and narrative in shaping public understanding of artificial intelligence, and argue that creative practitioners must be recognized as active contributors to AI governance-not just communicators of its outcomes. This perspective reflects a growing recognition that AI is not only a technical system, but a cultural one. In parallel, artist-led and community-driven initiatives are beginning to offer concrete models for more inclusive governance. For example, the We, the Artists reports developed for global convenings such as the High-Level Political Forum and COP29 provide grounded, lived insights into how AI is affecting creative labor, cultural production, and economic participation. In addition, emerging platforms such as ArtsEnvoy.ai demonstrate how creators can move from passive users to active co-designers of AI systems-shaping outputs, narratives, and applications in ways that reflect diverse cultural contexts. Looking ahead, the most effective policy approaches will be those that combine regulation with participation. This includes advancing frameworks such as creator data sovereignty, which address ownership, consent, and value in the AI ecosystem. AI governance must be built not only on principles, but on practice-and informed by those whose work and livelihoods are already shaping its future.