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Aureus Leadership

Private Sector Western Europe and Other States

Responses

In your opinion, what outcomes would make the first Global Dialogue on AI Governance a success?

1. Competency-Based Standards (The Action) Outcome-First Design: Focus on "Entrustable Professional Activities" (EPAs). If a learner can safely perform a task (e.g., drawing blood or triaging), the method of learning is secondary to the mastery of the skill. Modular Learning Units: Break complex medical roles into "micro-credentials." This allows learners to stack specific skills rather than waiting years for a full degree. Standardized Assessment (OSCEs): Use objective, hands-on clinical exams as the gatekeeper for practice, ensuring everyone meets the same high bar regardless of their background. 2. Flexible Pathways (The Access) Work-Integrated Learning: Legitimize on-the-job training. Hours spent in clinics under mentorship are treated with the same academic weight as classroom hours. Recognition of Prior Learning (RPL): A formal "fast-track" system that assesses existing skills from military, volunteer, or international experience to prevent redundant training. Peer-to-Peer Networks: Create "Communities of Practice" where knowledge is shared informally in the workplace but captured via digital logs. 3. Regulatory Safeguards (The Accountability) Independent Accreditation: Shift oversight from "approving courses" to "auditing outcomes." Regulators verify that the result of the training meets safety standards. Digital E-Portfolios: A mandatory, blockchain-verified digital record of a learner's skills, feedback, and certifications that stays with them throughout their career. Dynamic Re-validation: Instead of one-time licensing, practitioners must periodically demonstrate mastery of evolving competencies to maintain their "regulated" status.

From your perspective, which of the following thematic areas identified by the General Assembly Resolution 79/325 for the AI Dialogue reflect your priorities for urgent action and active engagement?

  • Safe, secure and trustworthy AI
  • Interoperability of governance approaches
  • Protection and promotion of human rights
  • Transparency, accountability, and human oversight

Please briefly explain your selection.

15

Foundations of Responsible AI Safe, Secure, and Trustworthy AI: Governance must prioritize technical robustness and security to prevent unauthorized access or malicious attacks. Systems are designed to be reliable and function as intended throughout their lifecycle. Protection of Human Rights: AI actors must respect international law and human dignity. This involves proactive safeguards against bias, discrimination, and privacy violations to protect individual freedoms. Transparency and Human Oversight: To build public trust, AI systems should be explainable and interpretable. Maintaining human control over critical decisions prevents over-reliance on automation and ensures accountability for outcomes. OECD OECD +8 Global and Societal Integration Capacity-Building: Global governance seeks to bridge digital divides by investing in local talent, data frameworks, and reliable infrastructure. This ensures that all nations, particularly developing ones, can benefit from AI innovation. Comprehensive Implications: Frameworks must address the social, economic, and ethical impacts of AI, including potential workforce disruptions and linguistic exclusion. Ethical guidelines aim to align AI development with cultural values and environmental sustainability. Interoperability of Governance: As AI development is global but regulation is often local, interoperability is vital to reduce market fragmentation. Standardized protocols allow different national frameworks to work together, fostering shared growth and safety. ITU

How are the governance gaps and related developments/advances in the thematic areas you selected above affecting your country, region, or sector? Please highlight the most significant challenges.

Students can use AI and we cannot address it unless it is so obvious, that they even cannot pronounce the words they "used". Handing an assignment like that does not support their learning. An AI which will teach them and help them to achieve the goal might be way forward.

What role can the AI Dialogue play in advancing international cooperation on AI governance?

It can supervise and advise rather than to be in control. In ideal world it will be used for analytical purposes only.

What are some of the existing initiatives, partnerships, or mechanisms that the AI Dialogue should build upon or connect with, and what added value could the AI Dialogue bring?

With the speed of current development, there must be enforcement of professional bodies with research bodies to restrict mal-efficience.

How can different stakeholders contribute to the AI Dialogue? Please share recommendations for the format and structure of the AI Dialogue.

Share the experience, to pick and address issues from the real life.

Which voices, communities, or perspectives are currently underrepresented in global discussions on AI governance? How could they be included?

Elderly, poor and uneducated.

What innovative engagement formats could most effectively foster meaningful and dynamic engagement during the AI Dialogue?

To begin with organisations who lead on it, combined with academia and professional body to ensure beneficence.

Please share examples of policies, practices, platforms, or approaches that promote effective AI governance or offer concrete solutions to addressing its challenges.

Use of mobile phone evolvement, use of computers and internet.