Ethos Global Consulting

A successful first Global Dialogue on AI Governance would be one that moves beyond general agreement on principles and begins to clarify how responsible AI governance can be practiced by governments, institutions, companies, educators, and civil society. In my view, success would mean recognizing that AI governance is not only a technical, regulatory, or economic matter, but a question of human responsibility, institutional judgment, and public trust. The Dialogue should help identify a limited number of shared priorities where international cooperation is most urgent, including transparency, accountability, protection of human dignity, education, responsible public-sector use of AI, and the prevention of harm to vulnerable communities. Success would also require a practical bridge between global principles and institutional implementation. Many organizations already speak about responsible AI, but they often lack clear processes for deciding when, why, and how AI should be used. The Dialogue should therefore encourage tools and frameworks that help institutions clarify purpose, affected stakeholders, consequences, and accountability before AI systems are deployed. This would help ensure that governance is not limited to post-deployment correction, but begins earlier, at the level of ethical orientation and responsible design. A successful Dialogue should also ensure that ethical, cultural, educational, philosophical, religious, and civil society perspectives are not treated as secondary to technical and market-driven voices. AI governance must be globally inclusive, especially for communities and countries that may be deeply affected by AI systems without having equal power in their design or deployment. Finally, the Dialogue should lead to a continuing process, not only a conference outcome. A strong result would be the creation of structured workstreams, including one focused on ethical orientation and human responsibility in AI governance. The first Dialogue will be successful if it helps the international community move from abstract concern to responsible direction: not slowing innovation, but ensuring that innovation remains accountable to human dignity, justice, and the common good.

• 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 selections reflect the conviction that AI governance must begin with human responsibility, not only technical performance. The social, economic, ethical, cultural, linguistic, and technical implications of AI are urgent because AI systems do not operate in isolation; they reshape education, communication, work, public trust, culture, and institutional decision-making. These effects must be examined before deployment, not only after harm has occurred. The protection and promotion of human rights should remain central because AI can either strengthen human dignity or weaken it, especially when systems affect vulnerable communities, access to services, public administration, identity, expression, or participation. Governance must ensure that technological development remains accountable to the people and communities it affects. Transparency, accountability, and human oversight are also essential. Institutions need clear processes for deciding when AI should be used, who remains responsible, how decisions can be explained, and how affected persons can seek review or correction. Human judgment must not be displaced by automated systems, especially in consequential contexts. Finally, AI capacity-building is necessary because responsible governance depends not only on laws and standards, but on the ethical and practical capacity of leaders, educators, institutions, and civil society to understand AI's consequences. Without this capacity, principles remain abstract. The Global Dialogue can help build a shared culture of responsible AI use, where innovation is guided by dignity, justice, accountability, and the common good.

One cross-cutting issue that deserves greater attention is the formation of human judgment in the age of AI. Many AI governance discussions focus on systems, risks, standards, data, transparency, and accountability. These are essential, but they do not fully address the human and institutional capacities required to govern AI responsibly. In this context, Spiritual Intelligence can be understood not as a religious category, but as a human capacity for ethical orientation, meaning, self-awareness, responsibility, and wise judgment before action. As AI systems become more powerful, faster, and more persuasive, societies will need not only technical literacy, but deeper forms of human literacy: the ability to ask what should be done, who is affected, what kind of human dignity is involved, and what responsibility cannot be delegated to a machine. Another emerging issue is the protection of human interiority and attention. AI systems increasingly shape what people see, believe, desire, and decide. Governance should therefore address not only external harms, but also the gradual weakening of human agency, reflection, and moral attention. This is especially important for children, young people, educators, and communities whose cultural or linguistic identities may be shaped by AI-mediated environments. A further cross-cutting issue is institutional readiness. Many organizations adopt AI tools before developing the ethical culture, leadership capacity, or internal processes needed to use them responsibly. The Global Dialogue could therefore encourage frameworks that help institutions pause before deployment, clarify purpose, assess consequences, protect human oversight, and strengthen responsibility. In this sense, AI governance should not only regulate technology. It should also protect and cultivate the human capacities that make responsible governance possible.

In my sector, the main governance gap is the distance between AI principles and institutional practice. Many organizations now use the language of responsible AI, but they often lack the internal processes, ethical capacity, and leadership culture needed to decide when, why, and how AI should be used. This creates a risk that AI adoption becomes driven mainly by efficiency, competition, or institutional pressure, rather than by human responsibility and public trust. A significant challenge is the weakening of human oversight in consequential decisions. AI systems can influence education, communication, recruitment, administration, public services, and social participation. When institutions adopt these systems without clear accountability, affected people may not know who is responsible, how decisions were made, or how to challenge harm. This is especially important for vulnerable communities, young people, and those whose cultural, linguistic, or social contexts may not be properly represented by AI systems. At the same time, there is a major opportunity. AI governance can become a catalyst for renewing institutional responsibility. If developed well, governance frameworks can help organizations clarify purpose before deployment, assess consequences, strengthen human oversight, and build trust with the communities they serve. This requires not only technical expertise, but ethical formation, capacity-building, and practical tools for responsible decision-making. For the private sector and advisory field, the opportunity is to move from abstract commitments to operational frameworks that help institutions integrate ethics into the structure of decision-making. AI governance should not be treated as a compliance exercise alone. It should become a disciplined process through which innovation remains accountable to human dignity, justice, cultural diversity, and the common good.

The AI Dialogue can play an important role by becoming a trusted international space where governments, the private sector, civil society, academia, and cultural and educational institutions can move from fragmented approaches to shared responsibility. AI governance cannot be shaped only by technological competition or national regulation. It requires international cooperation because AI systems cross borders, influence societies unevenly, and affect human rights, public trust, education, work, security, and culture. The Dialogue can help identify common priorities while respecting different legal systems, cultural contexts, and levels of technological capacity. Its value should not be only to repeat general principles, but to help translate them into practical guidance for institutions. This includes clearer expectations on transparency, accountability, human oversight, capacity-building, and protection of vulnerable communities. The Dialogue can also give visibility to voices that are often secondary in AI governance debates, including educators, civil society, faith and philosophical traditions, cultural institutions, and communities affected by AI but not involved in its design. This would strengthen the legitimacy of international cooperation and ensure that AI governance reflects more than market and technical perspectives. Most importantly, the AI Dialogue can help create continuity. It should not be a single event, but a structured process that gathers lessons learned, identifies gaps, supports capacity-building, and encourages practical tools for responsible AI use. Its role should be to help the international community develop a shared culture of governance where innovation remains accountable to human dignity, justice, and the common good.

The AI Dialogue should build upon existing international efforts such as the UNESCO Recommendation on the Ethics of Artificial Intelligence, the work of the UN system on digital cooperation, the Global Digital Compact, regional AI governance initiatives, human rights mechanisms, and existing standards developed by technical and policy bodies. It should also connect with academic institutions, civil society networks, educational organizations, cultural and faith-based dialogue platforms, and private-sector initiatives working on responsible AI. The added value of the AI Dialogue should be its capacity to bring these efforts together in a broader, inclusive, and human-centered framework. Many existing initiatives are valuable, but they often remain separated by sector, region, discipline, or institutional mandate. The Dialogue can help connect technical standards with ethical reflection, legal frameworks with institutional practice, and innovation policy with human rights and social responsibility. It can also add value by ensuring that voices from countries and communities with less technological power are not excluded from shaping the future of AI governance. International cooperation must not be limited to those who design and own the most advanced systems. It must include those who are affected by them. Finally, the Dialogue should contribute by creating practical continuity: shared learning, capacity-building, case studies, ethical tools, and workstreams that help institutions move from principles to implementation. Its strongest contribution would be to make AI governance not only a matter of compliance or technical safety, but a common effort to protect human dignity, strengthen public trust, and guide innovation toward the common good.

Different stakeholders can contribute by bringing their specific responsibilities and lived experience into a shared governance process. Governments can provide legal frameworks, public-interest priorities, and safeguards. The private sector can contribute technical knowledge, implementation experience, and accountability for the systems it develops and deploys. Civil society can represent affected communities and identify risks that may not be visible from institutional or commercial perspectives. Academia, educators, cultural institutions, and ethical or faith-based dialogue platforms can help deepen the human, social, and philosophical dimensions of AI governance. The AI Dialogue should combine plenary sessions with smaller thematic workstreams focused on practical outcomes. These could include human oversight, education and capacity-building, ethical orientation before deployment, vulnerable communities, public-sector use of AI, and institutional accountability. The format should allow not only formal statements, but structured exchange, case studies, regional perspectives, and concrete recommendations. The Dialogue should be designed as a continuing process, not only a conference.

Several voices remain underrepresented in global AI governance discussions. These include communities from countries with limited technological power, educators, young people, vulnerable groups, linguistic minorities, cultural and religious communities, and civil society actors working close to affected populations. Many of these communities may be deeply shaped by AI systems without having meaningful influence over their design, deployment, or governance. They could be included through regional consultations, multilingual submissions, youth and educator panels, civil society roundtables, and dedicated spaces for cultural, ethical, philosophical, and faith-based perspectives. Inclusion should not be symbolic. These voices should help define risks, priorities, and governance questions from the beginning. AI governance will be more legitimate if it listens not only to those who build AI, but also to those who live with its consequences.

The AI Dialogue could foster more meaningful engagement through formats that move beyond formal speeches. Useful formats could include scenario-based workshops, where participants examine real AI use cases in education, public administration, employment, health, culture, or security and identify governance responsibilities before deployment. This would help connect principles with practical judgment. Another valuable format would be cross-sector roundtables bringing together governments, private sector actors, educators, civil society, youth representatives, cultural institutions, and ethical or faith-based voices around specific dilemmas. Short case-study laboratories could also allow participants to compare lessons from different regions and sectors. The Dialogue could also include listening sessions for underrepresented communities, youth assemblies, and multilingual digital consultations before and after the Geneva meeting. Finally, a continuing online repository of case studies, tools, and recommendations would allow the Dialogue to become a living process rather than a one-time event. Meaningful engagement requires not only participation, but structured reflection, practical learning, and continuity.

One good practice is to treat AI governance not only as compliance, but as a structured process of ethical orientation before deployment. Through ETHOS, I work on approaches that help institutions clarify human purpose, affected stakeholders, possible consequences, and lines of accountability before decisions involving AI are made. This upstream process can complement technical standards, legal frameworks, and risk-management tools. A practical example is the use of ethical decision-support instruments, such as ETHOS Compass, that guide leaders and organizations through disciplined reflection before action. Such tools should not replace human judgment or automate ethics. Their purpose is to strengthen responsible judgment by asking the right questions early: Why is this system being used? Who may be affected? What responsibility remains human? How will oversight, review, and correction be ensured? Effective AI governance also requires training and institutional capacity-building. Policies alone are not enough if leaders and teams do not have the ethical literacy to apply them in real situations. ETHOS contributes to this need by supporting ethical orientation, responsible leadership, and institutional decision-making before action is taken.