OECD Working Party and Network of Experts on AI

The Working Party on Artificial Intelligence Governance oversees the OECD's work on AI policy. The OECD.AI Network of Experts provides policy, technical and business expert input to inform OECD analysis and recommendations.

Working Group on Tools & Accountability

An AI system that is trustworthy is inclusive and benefits people and planet; respects human rights and is unbiased/fair; transparent and explainable; robust, secure and safe; and accountable.

The OECD.AI expert group on implementing Trustworthy AI aims to highlight how tools and approaches may vary across different operational contexts.

The expert group’s mission is to identify practical guidance and standard procedural approaches for policies that lead to trustworthy AI. These tools will serve AI actors and decision-makers in implementing effective, efficient and fair AI-related policies.

The expert group developed a practical framework that provides concrete examples of tools to help implement each of the five values-based AI Principles. Based on the framework, the expert group is developing a catalogue of tools that help actors to ensure their AI systems are trustworthy.

The OECD Framework for Implementing Trustworthy AI Systems serves as a reference for AI actors in their implementation efforts and includes:

  1. process-related approaches such as codes of conduct, guidelines or change management processes, governance frameworks, risk management frameworks, documentation processes for data or algorithms, and sector-specific codes of conduct;
  2. technical tools including software tools, technical research and technical standards[1], tools for bias detection, for explainable AI, for robustness; and,
  3. educational tools such as those to build awareness and new capacities.

Co-chairs and members

Nozha Boujemaa, Global Digital Ethics and Responsible AI Director, IKEA Retail (Ingka Group).

Andrea Renda, Senior Research Fellow and Head of Global Governance, Regulation, Innovation and the Digital Economy (GRID), Centre for European Policy Studies.

Barry O’Brien, Government and Regulatory Affairs Executive, IBM.

The group meets virtually every 4 to 5 weeks.

See Working Group participants

Blog post



Putting the OECD AI Principles into practice: progress and future perspectives – Event summary

Session summary of this high-level panel discussion from the OECD MCM 2021 More than two years after the adoption of the OECD AI Principles, this discussion will highlight how countries are implementing policies for trustworthy, human-centric AI. The session will focus on: - Lessons learned to date implementing AI policies to steer the transformation of our economies and societies for inclusive growth and addressing global challenges. - Risk-based approaches to AI governance and soft and hard law, including the proposed EU AI Act that is triggering discussions around the world. - How to ensure that our policies and legal frameworks for AI are interoperable globally. And the priorities for international cooperation on AI moving forward.June 17, 2022


The technological readiness level (TRL) of 66 initiatives grouped based on the clustering framework described in Responsible AI in Pandemic Response

The technological readiness level (TRL) of 66 initiatives. Initiatives are grouped based on the clustering framework described in Responsible AI in Pandemic Response (The Future Society, 2020). Visualization by Bruno Kunzler, TFS Affiliate.April 6, 2022

OECD Framework for Classifying AI Systems: two page overview

The framework classifies AI systems along five dimensions: People & Planet, Economic Context, Data & Input, AI Model and Task & Output. Each one has its own properties and attributes that help assess policy considerations of particular AI systems. Stakeholders are involved in or affected by AI systems, while AI actors play active roles according to each dimension and throughout an AI system’s lifecycle. The framework allows users to zoom in on specific risks that are typical of AI, such as bias, explainability and robustness yet it is generic in nature. It facilitates nuanced and precise policy debate. The framework can also help develop policies and regulations since AI system characteristics influence the technical and procedural measures they need for implementation. The framework promotes a common understanding of AI by identifying the features of AI systems that matter most. Both in and out of government, the framework can inform registries or inventories by guiding work to describe systems and the basic characteristics of algorithms or automated decision systems. February 18, 2022


The OECD Framework for the Classification of AI systems

Key dimensions structure AI system characteristics and interactions The framework classifies AI systems and applications along the following dimensions: People & Planet, Economic Context, Data & Input, AI Model and Task & Output. Each one has its own properties and attributes or sub-dimensions relevant to assessing policy considerations of particular AI systems. February 17, 2022

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