This proposal aims to establish an international standard for the evaluation, ethical governance, and interoperability of Large Language Models (LLMs) in AI systems. The standard will define testing methodologies, performance assessment criteria, bias mitigation strategies, risk management protocols, and best practices for responsible deployment. It will also outline security considerations, industry-specific applications, and regulatory alignment to ensure the safe and effective integration of LLMs across various domains, including healthcare, finance, education, and public services.
This standard does not address the evaluation of non-language AI models or proprietary language models, and the focus is on open, general-purpose LLMs and their integration into AI systems.
Registration number (WIID)
92822
Scope
This proposal aims to establish an international standard for the evaluation, ethical governance, and interoperability of Large Language Models (LLMs) in AI systems. The standard will define testing methodologies, performance assessment criteria, bias mitigation strategies, risk management protocols, and best practices for responsible deployment. It will also outline security considerations, industry-specific applications, and regulatory alignment to ensure the safe and effective integration of LLMs across various domains, including healthcare, finance, education, and public services.
This standard does not address the evaluation of non-language AI models or proprietary language models, and the focus is on open, general-purpose LLMs and their integration into AI systems.
