International Institute For The Analysis Of Legal And Administrative Mutations

A successful Global Dialogue on AI Governance should deliver concrete, coordinated, and forward-looking outcomes grounded in a human-centric approach to artificial intelligence and firmly anchored in the protection of human rights, as emphasized in United Nations General Assembly Resolution 79/325. First, the Dialogue should advance a shared global understanding of AI governance principles that prioritize human dignity, fundamental rights, democratic values, and the rule of law. In particular, the protection of privacy and personal data should be recognized as central pillars of human-centric AI, ensuring that technological development remains aligned with democratic values. Second, success should be reflected in strengthened international cooperation and interoperability between regulatory frameworks. Given the global nature of AI systems and cross-border data flows, coordinated governance is essential to avoid fragmentation and ensure consistent protection of rights across jurisdictions. Third, the Dialogue should function as an anticipatory governance platform capable of identifying emerging risks, including those related to large-scale data processing, surveillance, and the erosion of private life in AI-driven societies. Finally, inclusion, literacy, and transparency should be key indicators of success, ensuring that diverse stakeholders contribute to shaping AI governance in a manner that supports democratic institutions and reinforces public trust.

• Protection and promotion of human rights
• Transparency, accountability, and human oversight
• Safe, secure and trustworthy AI
• Open-source software, open data and open AI models

The selected priorities reflect the core objectives of Resolution 79/325, particularly the centrality of human rights, transparency and accountability in AI governance. A human-centric approach to AI requires that systems be designed, deployed and governed in a manner that respects fundamental rights, including the right to privacy and the protection of personal data. As AI increasingly relies on large-scale data processing, risks to individual autonomy, dignity and private life become significant. Transparency and accountability are components of the rule of law in digital environments, ensuring that AI systems remain subject to human oversight and legal responsibility. Without these safeguards, there is a risk of undermining democratic institutions and exacerbating power imbalances. Safe and trustworthy AI is directly linked to the effective protection of fundamental rights. Public trust in AI systems depends on their compliance with legal standards and ethical principles, particularly in relation to data governance and privacy protection. Finally, addressing the broader social and ethical implications of AI allows for a comprehensive governance approach that considers the impact of AI on democratic processes, social cohesion and human agency.

An emerging issue not sufficiently addressed in current frameworks is the growing tension between data-intensive AI systems and the protection of fundamental rights, particularly privacy and personal data protection. AI systems increasingly operate through continuous data collection, profiling, and predictive analytics, which can significantly interfere with individuals' private lives and challenge traditional data protection principles. These developments raise concerns regarding surveillance, loss of autonomy, and the potential misuse of personal data. Furthermore, the convergence between AI and other emerging technologies introduces new dimensions of risk, including challenges related to access to AI systems, the protection of privacy, algorithmic transparency and explainability, protection against algorithmic bias and unfairness, the right to human oversight and decision-making, and accountability for harms caused by AI systems. These developments highlight the need to expand existing legal frameworks and to consider new categories of rights within the broader human rights system. Addressing these issues is essential to ensure that AI governance remains aligned with human dignity, democratic values, and the rule of law.

Governance gaps in AI have a direct impact on the protection of human rights, democratic values and the rule of law. The lack of harmonized global standards leads to fragmentation, inconsistent protections and legal uncertainty. In jurisdictions with advanced regulatory frameworks, such as the European Union, strong protections for privacy and personal data exist. However, global interoperability remains a challenge, particularly in the context of cross-border data flows and multinational AI systems. In regions with less developed regulatory capacity, individuals are more vulnerable to data exploitation, surveillance and misuse of AI technologies. These disparities risk deepening global inequalities and weakening trust in digital systems. At the same time, these challenges create opportunities for strengthening international cooperation and developing coherent governance frameworks that place fundamental rights—especially privacy and data protection—at their core.

The AI Dialogue can play an important role in advancing global cooperation by promoting a human-centric and rights-based approach to AI governance. It can serve as a platform for aligning governance models, facilitating interoperability, and supporting the development of shared standards that protect fundamental rights across jurisdictions. Importantly, the Dialogue can contribute to strengthening the rule of law in the digital age by ensuring that AI systems are governed in a transparent, accountable, and legally grounded manner. By fostering transparency, literacy, and inclusion, the Dialogue can also support the integration of emerging issues—such as privacy risks, data protection challenges, and new forms of digital vulnerability—into global governance discussions.

The AI Dialogue should build upon existing international and regional initiatives that promote human-centric and rights-based AI governance. These include frameworks that emphasize privacy, data protection, transparency and accountability as core principles of AI governance. While these initiatives provide important foundations, they remain fragmented and unevenly implemented at the global level. The added value of the AI Dialogue lies in its ability to connect these initiatives, promote interoperability and ensure that fundamental rights—particularly the right to privacy and the protection of personal data—are consistently upheld across jurisdictions.

Different stakeholders can contribute to the AI Dialogue by bringing diverse perspectives, expertise, and experiences, particularly those of underrepresented communities most affected by AI systems. Ensuring the inclusion of voices from regions with limited legal protections, as well as experts in data protection, human rights, and interdisciplinary fields, is essential for developing equitable and context-sensitive governance frameworks. In addition, stakeholders can contribute by sharing good practices and policy approaches grounded in a human-centric and rights-based perspective. These include frameworks that promote transparency in data processing, accountability mechanisms, and strong protections for privacy and personal data, helping to build trustworthy and responsible AI systems. Regarding format and structure, the AI Dialogue should be designed as an inclusive and multi-stakeholder platform, combining plenary discussions with thematic working groups focused on key issues such as data protection, governance models, and emerging risks. It should also include participatory mechanisms, such as public consultations and expert panels, to ensure continuous input from diverse actors. Finally, the Dialogue should adopt a flexible and iterative structure, enabling ongoing exchange, knowledge-sharing, and anticipatory governance, while ensuring that outcomes are translated into concrete policy recommendations and internationally coordinated actions.

Underrepresented voices in global discussions on AI governance include individuals and communities most affected by data-driven technologies, particularly in regions with limited legal protections. This also includes civil society organizations, vulnerable groups, and experts from interdisciplinary fields such as data protection and human rights, whose perspectives are often insufficiently integrated into global policy debates. Additionally, perspectives from the Global South and from communities experiencing the social and economic impacts of AI are frequently underrepresented, despite being directly affected by the deployment of these technologies. These voices could be better included through more inclusive and participatory governance mechanisms, such as public consultations, multi-stakeholder forums, and regional representation in global initiatives. It is also essential to promote interdisciplinary collaboration and ensure that human rights and data protection expertise are systematically integrated into AI governance processes. Strengthening digital literacy and access to participation mechanisms can further support meaningful engagement, ensuring that AI governance frameworks reflect diverse experiences and are responsive to real-world impacts on private life, democratic institutions, and fundamental rights.

Innovative engagement formats are essential for fostering meaningful and dynamic participation in the AI Dialogue, particularly in a global and multi-stakeholder context. First, the Dialogue could incorporate hybrid and interactive formats, combining high-level plenary sessions with smaller, thematic working groups focused on specific issues such as data protection, governance models, and emerging risks. This would allow for both strategic discussions and in-depth, solution-oriented exchanges. Second, participatory formats such as multi-stakeholder roundtables and deliberative workshops can facilitate dialogue between policymakers, industry representatives, civil society, and academic experts. These formats encourage the inclusion of diverse perspectives and support more balanced and inclusive decision-making processes. Third, digital engagement tools, including online consultation platforms and collaborative forums, can enhance accessibility and allow broader participation across regions, particularly for underrepresented communities. These tools can also support continuous engagement beyond formal meetings. Additionally, scenario-based exercises and policy simulations can provide innovative ways to explore the implications of AI governance choices, helping stakeholders better understand risks and trade-offs in a dynamic and practical manner. Finally, the Dialogue should adopt an iterative and transparent structure, where feedback mechanisms are embedded throughout the process and outcomes are clearly communicated. This approach would strengthen trust, promote accountability, and ensure that the Dialogue remains responsive to evolving technological and societal challenges.

Effective AI governance practices are those grounded in a human-centric approach and aligned with the protection of fundamental rights, democratic values, and the rule of law. Key examples include regulatory frameworks such as the EU AI Act, which adopts a risk-based approach and introduces obligations related to transparency, accountability, and human oversight. Similarly, data protection regimes like the GDPR provide strong safeguards for privacy and personal data, which remain central to trustworthy AI systems. In addition to binding regulations, soft law instruments and international guidelines-such as OECD AI Principles and UNESCO's Recommendation on the Ethics of Artificial Intelligence-play an important role in promoting shared standards and responsible innovation. Practical approaches also include the development of impact assessments, such as fundamental rights impact assessments for high-risk AI systems, as well as transparency mechanisms and explainability tools that enhance accountability in AI deployment. Furthermore, collaborative platforms and multi-stakeholder initiatives support knowledge-sharing and the exchange of best practices, contributing to more coherent and coordinated global governance. These examples demonstrate that robust and multi-layered governance frameworks are essential for building trustworthy AI systems and ensuring that technological innovation supports, rather than undermines, human rights, democratic values, and the rule of law.