Libyan Authority for Scientific Research

Global Dialogue on AI Governance to be a success, it must move beyond rhetoric toward an interoperable and inclusive framework. Success is defined by three outcomes: Universal Red Lines Establishing a global consensus on non-negotiable boundaries, specifically regarding autonomous weapons and mass surveillance. Success means creating a shared charter that prevents "regulatory arbitrage," ensuring companies cannot bypass safety standards by moving to less regulated regions. Bridging the AI Divide Shifting from a digital divide to a knowledge partnership. Success requires concrete mechanisms for technology transfer and infrastructure access, ensuring the Global South moves from being mere consumers to active participants in setting global standards. Institutionalized Agility Since AI outpaces traditional law, success means creating a Permanent Coordination Center. This body would standardize algorithmic transparency and "watermarking" protocols to combat deepfakes and misinformation in real-time. Success is the transition from diagnosing risks to proactive collective action. It is the moment we build a bridge of trust between developers and society to ensure AI serves the common good rather than fueling global inequality.

• Open-source software, open data and open AI models
• Social, economic, ethical, cultural, linguistic and technical implications of AI
• Safe, secure and trustworthy AI
• Interoperability of governance approaches

My selection focuses on creating a practical and equitable foundation for global AI development.

Cognitive Sovereignty: As AI becomes more persuasive, we must protect mental integrity. This involves preventing "neuro-manipulation" where algorithms bypass human reasoning to influence behavior or preference formation. Data Sovereignty & Cultural Rights: Beyond open data, we need frameworks for Indigenous and community data rights. This ensures that training data isn't just extracted from marginalized groups without their consent or benefit-sharing. To be future-proof, the dialogue must address the planetary and psychological impacts of AI, ensuring it respects both our natural resources and our mental autonomy.

The current governance gaps create a critical tension between dependency and empowerment: Challenges The Dependency Gap: Lack of local infrastructure leads to digital and algorithmic colonialism, where we rely on foreign proprietary models, risking data sovereignty. Regulatory Friction: Fragmented global rules create a "compliance wall" for local startups, making it difficult to scale innovations across borders. The Trust Deficit: Opaque "black box" algorithms in public services fuel distrust and potential bias without clear accountability standards. Opportunities Sovereign Innovation: Prioritizing Open-Source allows us to build AI tailored to our specific cultural and linguistic needs, bypassing traditional barriers. Localized Solutions: Capacity-building enables local talent to apply AI to regional crises like water scarcity or food security. Global Integration: Interoperable standards allow our tech sector to compete globally, moving us from passive consumers to active architects. The challenge is vulnerability, but the opportunity is self-determination through inclusive and transparent governance.

The AI Dialogue acts as a vital bridge between fragmented national policies and a cohesive global framework. It advances international cooperation through three primary roles: Harmonizing Standards: By fostering interoperability, the Dialogue prevents a patchwork of conflicting regulations. It provides a platform to align safety protocols and transparency requirements, ensuring that developers face consistent expectations across borders, which reduces market friction and enhances global safety. Democratizing Governance: It ensures that AI oversight is not an exclusive club of tech-dominant nations. By including the Global South, the Dialogue shifts the focus toward capacity-building and resource sharing. This transforms governance from a restrictive exercise into an inclusive partnership that addresses the digital divide. Building Collective Security: The Dialogue facilitates the establishment of shared Red Lines and monitoring mechanisms. It serves as a rapid-response network for emerging threats - such as deepfakes or biosecurity risks - allowing nations to act in concert rather than in isolation. The Core Impact: The AI Dialogue moves the world from unilateral competition to multilateral trust, ensuring that AI development remains a transparent, human-centered endeavor that benefits all of humanity.

The AI Dialogue should act as a system integrator, scaling existing technical work into a globally legitimate framework. Initiatives to Connect With UN Global Digital Compact: To implement the International Scientific Panel on AI. G7 Hiroshima Process:To transform voluntary codes of conduct into global transparency standards. OECD & GPAI: To leverage their data-driven policy metrics and safety benchmarks. Regional Bodies (AU, EU, UfM and etc): To ensure global rules reflect diverse economic and cultural realities. Added Value of the AI Dialogue ▪︎ Universal Legitimacy: Unlike "clubs" of wealthy nations, it gives the Global South an equal seat in policy-making. ▪︎Regulatory Interoperability: It acts as a hub to align fragmented national laws into a coherent global system. ▪︎ Political Momentum: It converts technical recommendations into high-level international commitments. The Dialogue's unique value is its ability to turn exclusive technical agreements into an inclusive and actionable global architecture.

To be effective, the AI Dialogue must move from a government-only model to a multi-stakeholder ecosystem. Stakeholder Contributions Governments: Establish legal mandates and fund global capacity-building. Private Sector: Provide technical transparency and commit to safety "Red lines." Civil Society & Academia: Act as independent auditors for bias and human rights. Technical Community: Develop universal standards for watermarking and open-source protocols. Recommended Format & Structure The "Hub-and-Spoke" Model: A central UN plenary supported by regional technical working groups to ensure local nuances are captured. Rolling Regulatory Sandbox: A continuous digital platform for real-time policy sharing, rather than static annual meetings. Track 1.5 Diplomacy: Pairing formal sessions with informal workshops between developers and regulators for candid problem-solving. Inclusive Quotas: Mandated representation for the Global South and youth to ensure the dialogue isn't an exclusive "club." The Goal: A structure that mirrors the technology it governs, agile, transparent, and decentralized.

To ensure a truly global framework, we must move from symbolic presence to active agency for the following groups: Underrepresented Voices The Global South: Currently "technology takers" with limited compute or policy influence despite representing the global majority. ▪︎Indigenous Communities: Their data and traditional knowledge are often extracted for training without consent or benefit-sharing. ▪︎Youth & Future Generations: The primary long-term stakeholders whose digital legacy is rarely considered in current legislation. ▪︎Small Developers & Civil Society: Often overshadowed by "Big Tech" lobbying, yet essential for identifying bias and protecting human rights. How to Include Them ▪︎Decentralized Hubs: Host regional consultations to capture local economic and cultural nuances. ▪︎Mandated Seats: Establish quotas and provide financial grants for civil society and Global South researchers in all high-level sessions. ▪︎Digital "Open Mic": Use hybrid platforms for asynchronous submissions, ensuring participation isn't limited by geography or resources. ▪︎Co-Design Rights: Involve these groups in drafting the initial "governance roadmap," not just the final review. The Goal: Shift from consultation to co-creation, ensuring those most vulnerable to AI have a definitive hand in its oversight.

To ensure the AI Dialogue escapes the "talk shop" trap, it should adopt agile, data-driven formats: ▪︎Multilateral "Policy Sandboxes": Replace debate with action by "live-testing" governance frameworks on hypothetical AI models to see how they perform across different regions before finalizing laws. ▪︎Red Teaming Plenaries: Use adversarial workshops where human rights activists, youth, and technical experts work to "break" proposed regulations to identify loopholes or biases. ▪︎Live Digital Dashboards: Move from static reports to a real-time transparency platform. This allows for "evidence-based" sessions using current data on AI safety incidents and capacity-building. ▪︎Track 1.5 Lightning Rounds: Feature high-impact, five-minute talks from Global South researchers and grassroots innovators to ground diplomatic discussions in technical reality. ▪︎Reverse Mentoring: Formalize sessions where youth and digital-native creators mentor senior policymakers, ensuring the generation inheriting AI's consequences leads the conversation. The Goal: Transform the Dialogue from a static event into a continuous, collaborative laboratory for global AI governance.

Effective AI governance is shifting from high-level principles to standardized, technical frameworks: ▪︎The EU AI Act: A pioneering, risk-based model that categorizes AI by harm, enforcing strict transparency for "high-risk" systems and banning "unacceptable" risks like social scoring. ▪︎ISO/IEC 42001:2023: The first certifiable international standard for AI Management Systems, providing a common global language for risk assessment and documentation. ▪︎NIST AI Risk Management Framework: A widely adopted voluntary framework that helps organizations manage bias, security, and trustworthiness throughout the AI lifecycle. ▪︎The UK AI Safety Institute (UKAISI): A state-led model for testing "frontier" AI capabilities before large-scale deployment, setting a global precedent for proactive safety evaluations. ▪︎UNESCO's Recommendation on the Ethics of AI:The first global ethical framework adopted by 193 states, specifically empowering the Global South through AI readiness assessments. The Trend: Governance is moving toward "Policy-as-Code" integrating ethical and regulatory checks directly into the development pipeline.