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Responses
In your opinion, what outcomes would make the first Global Dialogue on AI Governance a success?
The outcomes of this event would be valuable if it can suggest the AI governance principles. These principles must be a guidance for every parties in terms of developing AI capabilities. A successful first Global Dialogue on AI Governance would produce outcomes that are practical, inclusive, and capable of building trust across borders. Rather than broad statements, it should deliver a shared baseline of principle
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
- AI capacity-building
- Social, economic, ethical, cultural, linguistic and technical implications of AI
- Interoperability of governance approaches
Please briefly explain your selection.
9
Without shared approaches to managing high-risk AI (e.g., misuse, systemic bias, autonomous decision-making), trust will erode quickly. I think how AI development benefit and reduce the drawbacks is only possible if the AI is developed under standardised principles. AI governance must not be dominated by a few countries or companies. Supporting developing nations, including Indonesia, through skills development, infrastructure access, and policy support is critical to ensuring fair participation and preventing a widening digital divide.
In your opinion, are there any cross-cutting or emerging issues not captured by the listed themes above? If so, please explain.
2
AI Audit & Assurance Governance frameworks and interoperability
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.
In Indonesia, governance gaps in AI audit and assurance and inclusion and capacity-building are already shaping both risks and opportunities. On AI audit and assurance, the most significant challenge is the absence of standardized, locally adapted frameworks and skilled auditors. On inclusion and capacity-building, the challenge lies in unequal access to digital infrastructure, talent, and AI literacy across regions. Without targeted investment, AI adoption risks widening the gap between urban and rural areas, as well as between large enterprises and smaller institutions