Youngo Working Groups Human Rights

A successful first Global Dialogue on AI Governance should deliver both shared direction and practical outcomes. It should agree on core principles such as human rights, transparency, accountability, and safety to guide global AI development and reduce fragmentation. Beyond principles, it must produce concrete steps, including a roadmap for aligned governance frameworks, risk standards, and mechanisms for international cooperation. Inclusivity is essential. Meaningful participation from the Global South, youth, and civil society should be ensured, alongside commitments to capacity-building and fair access to AI. The Dialogue should also establish continuity through ongoing multi-stakeholder processes to track progress and adapt to rapid changes. Ultimately, success lies in setting a common path, securing actionable commitments, and building an inclusive, long-term approach to global AI governance.

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

I selected these priorities because they reflect the most urgent and interconnected challenges in global AI governance. AI capacity-building is essential to ensure that all countries especially in the Global South can meaningfully participate in and benefit from AI development. Without it, existing inequalities will deepen. The social, economic, ethical, cultural, linguistic, and technical implications of AI must be addressed holistically, as AI systems already shape labor markets, public services, and cultural representation. Ignoring these dimensions risks reinforcing bias, exclusion, and digital divides. The protection and promotion of human rights is a fundamental baseline. AI systems can impact privacy, freedom of expression, and non-discrimination, making rights-based governance non-negotiable. Transparency, accountability, and human oversight are critical to building trust. Clear standards for explainability, responsibility, and human control ensure that AI remains aligned with societal values and can be effectively governed. Together, these priorities support a balanced, inclusive, and rights-based approach to AI governance that is both practical and forward-looking.

Yes,several cross-cutting and emerging issues are not fully captured. First, AI and environmental sustainability is often overlooked. The energy and resource demands of large-scale AI systems have growing climate impacts, making it essential to align AI governance with sustainability goals. Second, data governance and ownership remains a critical gap. Questions around who owns data, how it is sourced, and how benefits are shared especially across borders are central to fairness and equity. Third, geopolitical dynamics and power concentration are increasingly shaping AI development. A small number of countries and companies dominate the field, raising concerns about digital sovereignty, dependency, and global inequality. Fourth, misinformation and information integrity is an urgent issue, particularly with generative AI accelerating the spread of false or manipulated content at scale. Finally, accountability in cross-border contexts is still unclear. As AI systems operate globally, there is a need for mechanisms to address harms that transcend national jurisdictions. Addressing these issues alongside the core themes would strengthen a more comprehensive and future-proof approach to AI governance.

In Indonesia and the broader Southeast Asian region, governance gaps in AI are already shaping both risks and opportunities. A key challenge is limited AI capacity and infrastructure. While adoption is growing, gaps in technical expertise, compute resources, and regulatory readiness make it difficult to fully leverage AI while managing its risks. This creates dependency on foreign technologies and reduces local control over data and innovation. Second, weak data governance and enforcement increases risks to privacy and human rights. The rapid expansion of digital platforms has not always been matched by strong oversight, leaving room for misuse of personal data, biased algorithms, and limited accountability. Third, the social and economic impacts are uneven. AI has the potential to boost productivity and public services, but it also raises concerns about job displacement especially in informal sectors and unequal access between urban and rural communities. Cultural and linguistic diversity in the region is also underrepresented in many AI systems. However, these gaps also create opportunities. Indonesia has a large, young, and digitally active population, which can drive inclusive AI innovation if supported by targeted capacity-building and education. There is also strong potential for regional cooperation in Southeast Asia to develop shared standards and reduce fragmentation. Finally, strengthening transparency, accountability, and human oversight could position the region as a leader in responsible AI, building public trust while attracting sustainable investment. Overall, addressing these governance gaps can turn current vulnerabilities into long-term advantages for inclusive and ethical AI development.

The AI Dialogue can serve as a key platform to bridge fragmented global efforts and foster meaningful international cooperation. First, it can help align countries around shared principles and standards, reducing regulatory divergence and enabling more interoperable governance frameworks. This is especially important as AI systems operate across borders. Second, the Dialogue can promote inclusive multistakeholder engagement, ensuring that governments, industry, civil society, academia, and underrepresented regions particularly the Global South have a voice in shaping AI governance. Third, it can facilitate knowledge sharing and capacity-building, allowing countries with more advanced AI ecosystems to support those with limited resources. This helps reduce global inequalities and supports more balanced participation. Fourth, the Dialogue can act as a trust-building mechanism, encouraging transparency, cooperation, and open communication between stakeholders, including leading AI developers. Finally, it can lay the groundwork for ongoing coordination, such as working groups, joint initiatives, or regular review processes, ensuring that governance efforts remain adaptive to rapid technological change. Overall, the AI Dialogue can move global discussions from fragmented debates toward coordinated, inclusive, and action-oriented cooperation on AI governance.

The AI Dialogue should build on existing global and regional initiatives to avoid duplication and strengthen coherence. Key efforts include the UNESCO Recommendation on the Ethics of AI, which provides a global normative framework; the OECD AI Principles, which guide responsible AI policy; and the Global Partnership on AI (GPAI), which advances multistakeholder collaboration and applied research. Regional initiatives such as the European Union AI Act and ASEAN's emerging AI governance frameworks also offer important regulatory and policy models. In addition, the AI Safety Summit has contributed momentum on global AI risk and safety discussions. The added value of the AI Dialogue lies in its ability to connect and harmonize these fragmented efforts. It can serve as a neutral platform that brings together diverse stakeholders, including underrepresented regions, to align priorities and share best practices. Furthermore, the Dialogue can focus on implementation and coordination, translating existing principles into actionable steps, especially for countries with limited capacity. It can also strengthen inclusivity and equity, ensuring that Global South perspectives are better integrated into global governance processes. Finally, by fostering continuous engagement through working groups or follow-up mechanisms the AI Dialogue can ensure that global cooperation remains adaptive, practical, and responsive to rapid technological change.

Different stakeholders can contribute in complementary ways to ensure the AI Dialogue is inclusive, practical, and impactful. Governments can provide policy direction, share regulatory experiences, and commit to aligning national frameworks. Industry can offer technical expertise, transparency on AI systems, and support for standards and safety practices. Civil society and academia can bring critical perspectives on human rights, ethics, and social impacts, while also contributing research and accountability mechanisms. Youth and underrepresented groups can highlight lived experiences and ensure future-oriented, inclusive solutions. In terms of format and structure, the AI Dialogue should adopt a multistakeholder and hybrid model. This could include: Plenary sessions to set shared priorities and political momentum Thematic working groups focused on key areas (e.g., human rights, capacity-building, transparency) to develop concrete outputs Regional consultations to capture diverse perspectives, especially from the Global South Interactive formats such as roundtables and workshops to encourage open exchange and collaboration To ensure impact, the Dialogue should produce clear deliverables, such as policy recommendations, roadmaps, or voluntary commitments. It should also establish follow-up mechanisms, like annual meetings or progress reviews, to track implementation and maintain continuity. Overall, a structured yet flexible approach grounded in inclusivity, transparency, and action will enable stakeholders to contribute meaningfully and drive forward global AI governance.

Several voices remain underrepresented in global AI governance discussions. First, Global South countries, including many in Southeast Asia and Africa, often lack equal representation despite being heavily impacted by AI deployment. Second, local and marginalized communities—such as rural populations, informal workers, Indigenous peoples, and persons with disabilities—are rarely included, even though AI can significantly affect their livelihoods and rights. Third, youth voices are still underutilized, despite being both major users and future leaders in AI governance. Additionally, non-English-speaking and culturally diverse groups are often excluded due to language and accessibility barriers. To address this, participation must be made more accessible and intentional. This includes providing financial support, travel funding, and digital access to enable broader engagement. Regional consultations and decentralized dialogues can ensure local perspectives are captured and reflected in global processes. Language inclusivity is also key—through interpretation, multilingual documentation, and culturally relevant engagement methods. Creating dedicated spaces or quotas for underrepresented groups can further ensure their voices are not overshadowed. Finally, integrating these perspectives into decision-making processes, not just consultations, is essential. This means giving underrepresented stakeholders real influence over outcomes, not merely symbolic participation. A more inclusive approach will lead to AI governance that is not only fairer, but also more effective and globally legitimate.

To foster meaningful and dynamic engagement, the AI Dialogue should move beyond traditional panels and adopt more interactive, inclusive formats. First, co-creation labs or policy sprints can bring diverse stakeholders together to collaboratively develop concrete outputs—such as draft guidelines or solutions—within a short timeframe. This encourages practical, action-oriented outcomes. Second, scenario-based simulations (e.g., AI crisis or governance role-play) can help participants explore real-world challenges, trade-offs, and decision-making under pressure, making discussions more grounded and engaging. Third, multistakeholder roundtables with equal voice design—where participants are intentionally balanced and moderated to ensure inclusivity—can prevent dominance by a few actors and elevate underrepresented perspectives. Fourth, regional and community-led sessions can create space for localized insights, feeding directly into global discussions and ensuring diverse contexts are reflected. Fifth, digital participatory platforms (e.g., live polling, collaborative documents, and open comment tools) can enable broader, real-time input, including from remote participants. Finally, "reverse panels" or open-floor dialogues, where policymakers and industry leaders respond directly to questions from youth and civil society, can strengthen accountability and trust. Combining these formats with clear outputs and follow-up mechanisms will make the AI Dialogue more inclusive, interactive, and impactful.

Several existing policies and initiatives offer practical models for effective AI governance. The European Union AI Act is a leading example, introducing a risk-based approach that classifies AI systems and sets clear obligations for high-risk applications. It provides a concrete regulatory framework that can be adapted by other regions. The UNESCO Recommendation on the Ethics of AI offers a global standard grounded in human rights, guiding countries in developing inclusive and ethical AI policies. From a technical and industry perspective, tools like algorithmic impact assessments (AIAs)-used in countries such as Canada-help evaluate risks before deployment, improving accountability and transparency. Multi-stakeholder platforms such as the Global Partnership on AI (GPAI) and the OECD AI Policy Observatory support knowledge-sharing, best practices, and international coordination. At the organizational level, practices like AI ethics review boards, model audits, and transparency reports from companies provide concrete mechanisms to operationalize responsible AI. Additionally, regulatory sandboxes-adopted in several countries-allow safe testing of AI innovations under regulatory supervision, balancing innovation with risk management. Together, these examples demonstrate that effective AI governance requires a combination of binding regulation, ethical frameworks, technical tools, and collaborative platforms to address complex and evolving challenges.