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Singapore’s New Governance Framework for Generative AI


Singapore Proposes New Governance Framework for Generative AI

Singapore, a country known for its technological advances, is now setting the pace in regulating generative artificial intelligence (AI). The country has proposed a new governance framework for generative AI, extending from its existing AI governance framework last revised in 2024. This initiative aims to address the distinct challenges presented by generative AI technologies.

Model AI Governance Framework for Generative AI

The Model AI Governance Framework for Generative AI is designed to provide a systematic and balanced approach. It considers the concerns related to generative AI while still fostering and encouraging innovation. This initiative is led by Singapore’s Artificial Intelligence and Data Industry Office (AIVF) and the Infocomm Media Development Authority (IMDA). Key stakeholders, including policymakers and the research community, are being involved, highlighting the importance of a collective effort in shaping this framework.

International Input and Completion Date

The international community’s feedback on the proposed framework is currently being sought. The intention is to incorporate this input into the final version of the framework, aiming for a comprehensive and effective governance structure. The completion of this framework is expected by mid-2024.

The Necessity of Regulation

A recent report by cybersecurity leader ExtraHop underscores the necessity of such regulation. The report found that 81% of Singaporean organizations report their employees are using generative AI in the workplace. However, only 40% have invested in monitoring tools and merely 38% are training employees in the responsible use of AI. The report highlights the risks associated with the use of generative AI, such as the leakage of sensitive information and security threats. It recommends that governments should take the lead in setting clear regulations for businesses to follow, particularly in defining the ethical use of personal information and mitigating bias in AI models.



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