OECD Network of Experts on AI (ONE AI)

The OECD Network of Experts on AI (ONE AI) provides policy, technical and business expert input to inform OECD analysis and recommendations. It is a multi-disciplinary and multi-stakeholder group.

Compute & Climate

Why focus on AI compute?

Alongside data and algorithms, AI computing capacity (“AI compute”) is a key enabler for AI and related economic growth and competitiveness (Figure 1). While data and machine learning algorithms receive significant attention in policy circles, the computational infrastructure that makes AI possible gets less. Yet understanding domestic AI compute capacity is critical for policy makers who want to formulate effective AI policies and make intelligent national AI investment choices.

Figure 1. AI Enablers

The OECD.AI Expert Group on AI Compute and Climate is helping the OECD to create a basic framework for understanding, measuring and benchmarking domestic AI computing capacity by country and region.

The expert group is working with key AI compute players and has begun a data-gathering exercise that will continue over time. In doing so, the expert group is mindful that the AI compute landscape is in a constant state of evolution.

The targeted focus of the ONE AI task force on AI compute complements the activities of the three expert groups.

Co-chairs and Members

The Expert Group on AI Compute and Climate is co-chaired by:

Participants in the expert group include policy makers and entities in charge of public computing infrastructures as well as key industry players: hardware providers; cloud service providers; original equipment manufacturers; academia engaged in AI compute; major data centre operators; major consulting firms; and other experts on computing performance.

Participants

49 results

Blog post

Documents

Business

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

Intergovernmental

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

Business

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