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Collaborative Discussions on AI Governance in Thailand

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The hybrid format of the second IPAP advisory panel meeting took place at ETDA and involved the participation of experts in AI Governance from both domestic and international participants. Prof Dr Urs Gasser presided over the meeting as the Chairman. Network agencies and Dr Sak Sekkunthod (ETDA Consultant) also contributed their perspectives and opinions during the meeting.

The second meeting served as a platform for an extensive knowledge and experience exchange centred around the crucial topic of AI Governance, with a specific focus on the governance of AI within the realm of digital healthcare. The participants, comprising experts in the field nationally and internationally, came together to engage in an insightful discussion session.

The overarching goal was to provide valuable recommendations and guidance for the management of AI Governance, particularly concerning the draft framework that had already received approval from the  AI Governance Committee (AIGC) Centre.

Recognising the significance of diverse perspectives, the meeting aimed to foster an inclusive environment where stakeholders from various backgrounds could contribute their opinions, insights, and expertise. By actively listening to these valuable inputs, the intention was to enhance the draft framework, making it more comprehensive, robust, and reflective of the evolving needs and challenges in AI Governance.

The meeting participants included prominent network agencies such as the National Electronics and Computer Technology Centre (NECTEC), the Office of the Civil Service Commission (Sor Sor Sor), and the Department of Medical Services, alongside Dr Sak Sekkunthod, a consultant from Electronic Transactions Development Agency (ETDA). Their involvement further enriched the discussions by providing unique insights and perspectives from their respective areas of expertise.

By fostering knowledge sharing, brainstorming, and collaborative discussions, the meeting aimed to collectively shape and strengthen the AI Governance framework, ensuring it aligns with the dynamic nature of the digital healthcare landscape. The commitment to actively seek input from stakeholders reflected a commitment to inclusivity and a desire to create a governance framework that addresses all relevant parties’ diverse needs and concerns.

The second meeting held significant importance as one of its key agendas was to address the complete draft of AI Governance for management prepared by the AIGC (AI Governance Committee) Center. This draft was a crucial guideline for executives and team leaders, providing them with a comprehensive framework to apply AI technology within their respective domains effectively. The primary objective was to facilitate the development and maintaining dependable and ethical AI systems throughout the organisational landscape.

The drafted AI Governance framework comprises three essential components: the AI Governance Structure, AI Strategy and AI Operation. Each component plays a crucial role in ensuring the organisation’s responsible and effective utilisation of AI technology. The AI Governance Structure aims to establish an accountable framework that outlined roles, responsibilities, and decision-making processes concerning AI initiatives. This structure served as the backbone of the governance framework, providing clarity and ensuring proper oversight.

The AI Strategy component focuses on formulating a comprehensive and forward-thinking strategy for integrating AI technology into the organisation’s overall vision and goals. It involved identifying key areas where AI can drive innovation, improve efficiency, and deliver value. The AI Strategy component aimed to align AI initiatives with the organisation’s broader objectives, ensuring a cohesive and purposeful integration of AI technology.

The AI Operation component encompasses implementing AI initiatives within the organisation. It entailed defining best practices, ethical guidelines, and quality standards to ensure reliable and trustworthy AI systems’ development, deployment, and ongoing operation. Organisations could foster an environment of ethical and responsible AI implementation by incorporating robust governance measures at every stage of the AI lifecycle.


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