ISO-IEC-23053

ISO/IEC 23053 AI safety + governance framework.

Definition

ISO/IEC 23053:2022 (Framework for Artificial Intelligence (AI) systems using Machine Learning (ML)) is the international standard published June 2022 by ISO/IEC JTC 1/SC 42 defining framework + concepts + processes for AI systems using machine learning, foundational for ML systems lifecycle understanding (data + algorithm + training + inference + deployment + monitoring), complement ISO/IEC 23894 risk management standard. Framework + standard + guidance objectives AI safety + governance + risk management + transparency + fairness + accountability + explainability + multiple AI ethics principles adoption multi-stakeholder process + voluntary adoption industry + emerging regulation alignment EU AI Act + US Executive Orders + multiple national jurisdictions + private sector adoption Microsoft + Google + Meta + OpenAI + Anthropic + other major AI labs + corporate compliance teams 2020s+.

Origin

ISO/IEC 23053:2022 published juin 2022 ; ISO/IEC JTC 1/SC 42 AI subcommittee.

Example in context

Healthcare AI startup developing diagnostic ML model: uses ISO/IEC 23053 framework structuring ML system lifecycle phases (data collection + preprocessing + algorithm selection + training + validation + deployment + monitoring) ensuring consistent professional approach throughout development + aligned international standards complementing later regulatory submission requirements EU AI Act high-risk medical AI category compliance.

Related terms

• ISO/IEC 23894 — complementary AI risk standard.