Publications & Documents

Artificial intelligence (AI) is transforming economies and promising new opportunities for productivity, growth, and resilience. Countries are responding with national AI strategies to capitalise on these transformations. However, no country today has data on, or a targeted plan for, national AI compute capacity. This policy blind-spot may jeopardise domestic economic goals. This report provides the first blueprint for policy makers to help assess and plan for the national AI compute capacity needed to enable productivity gains and capture AI’s full economic potential. It provides guidance for policy makers on how to develop a national AI compute plan along three dimensions: capacity (availability and use), effectiveness (people, policy, innovation, access), and resilience (security, sovereignty, sustainability). The report also defines AI compute, takes stock of indicators, datasets, and proxies for measuring national AI compute capacity, and identifies obstacles to measuring and benchmarking national AI compute capacity across countries.

This report provides representative, cross-country estimates of the artificial intelligence (AI) workforce across OECD countries. The AI workforce is defined as the subset of workers with skills in statistics, computer science and machine learning who could actively develop and maintain AI systems. For countries that wish to be at the forefront of AI development, understanding the AI workforce is crucial to building and nurturing a talent pipeline, and ensuring that those who create AI reflect the diversity of society. This report uses data from online job vacancies to measure the within-occupation intensity of AI skill demand. The within-occupation AI intensity is then weighted to employment by occupation in labour force surveys to provide estimates of the size and growth of the AI workforce over time.

This report presents research and findings on accountability and risk in AI systems by providing an overview of how risk-management frameworks and the AI system lifecycle can be integrated to promote trustworthy AI. It also explores processes and technical attributes that can facilitate the implementation of values-based principles for trustworthy AI and identifies tools and mechanisms to define, assess, treat, and govern risks at each stage of the AI system lifecycle. This report leverages OECD frameworks – including the OECD AI Principles, the AI system lifecycle, and the OECD framework for classifying AI systems – and recognised risk-management and due-diligence frameworks like the ISO 31000 risk-management framework, the OECD Due Diligence Guidance for Responsible Business Conduct, and the US National Institute of Standards and Technology’s AI risk-management framework.

Artificial Intelligence (AI) scoring for constructed-response items, using recent advancements in multilingual, deep learning techniques utilising models pre-trained with a massive multilingual text corpus, is examined using international large-scale assessment data. Historical student responses to Reading and Science literacy cognitive items developed under the PISA analytical framework are used as training data for deep learning together with multilingual data to construct an AI model. The trained AI models are then used to score and the results compared with human-scored data. The score distributions estimated based on the AI-scored data and the human-scored data are highly consistent with each other; furthermore, even item-level psychometric properties of the majority of items showed high levels of agreement, although a few items showed discrepancies. This study demonstrates a practical procedure for using a multilingual data approach, and this new AI-scoring methodology reached a practical level of quality, even in the context of an international large-scale assessment.

Widespread supply disruptions in the wake of the COVID-19 pandemic and the Russian Federation’s large-scale aggression against Ukraine have raised concerns among policy makers that globalised value chains expose domestic production to shocks from abroad. This paper uses new indicators of global value chain dependencies and exogenous pandemic shocks to econometrically estimate the effects of supply disruptions abroad on domestic output. The results suggest that the adverse effects of supply disruptions are particularly large when concentration of supplying countries and supplying firms is high. Counterfactual simulations of the econometric model suggest that diversification of suppliers would have sizeable benefits in terms of shielding domestic production against country-specific supply shocks, with partial onshoring of production having only small additional benefits. Technological innovation that reduces foreign dependencies, such as the substitution of renewable energies for fossil fuels, can have similar benefits as diversification.

Open banking allows users to access financial information and services through consent-based data portability. This paper brings together the views of private and public experts from a wide variety of countries to explore opportunities and challenges of open banking for financial regulation, privacy protection, and competition. It discusses the different approaches taken by jurisdictions across the globe, and the importance of regulation and standards. While open banking empowers users in sharing and re-using their data across digital services, online platforms, sectors and borders, uncertainty in the interactions with data protection and privacy regimes remains challenging. This paper informs OECD work to consider how cross-sectoral cooperation between financial, competition and data protection authorities could help further open banking.

The paper presents a comprehensive assessment of the strengths and limitations of the intellectual property (IP) system in Poland. It offers policy recommendations to fully exploit the potential of IP to support an innovation-based economy. It finds that the key components of an effective IP strategy in Poland should include the promotion of IP use among economic actors and other stakeholders as well as information campaigns and training programmes to raise awareness and knowledge about the advantages of IP. Recommendations also include reducing barriers to IP use by lowering the costs of and simplifying IP-related procedures, and promoting the valorisation of IP held by universities to enhance technology transfer to the business sector.

This paper uses information collected and provided by GlassAI to analyse the characteristics and activities of companies and universities in Canada, Germany, the United Kingdom and the United States that mention keywords related to Artificial Intelligence (AI) on their websites. The analysis finds that those companies tend to be young and small, mainly operate in the information and communication sector, have AI at the core of their business, and aim to provide customer solutions. It is noteworthy that the types of AI-related activities reported by them vary across sectors. Additionally, although universities are concentrated in and around large cities, this is not necessarily reflected in the intensity of AI-related activities. Taken together, this novel and timely evidence informs the debate on the most recent stages of digital transformation of the economy.

The OECD Policy Framework on Digital Security charts the economic and social dimension of cybersecurity, highlights the OECD approach to digital security policy and equips policymakers to use OECD digital security Recommendations in developing better policies. The Framework also identifies linkages with other policy areas addressed through existing OECD standards and tools. The OECD has been at the forefront of international efforts on guiding policy makers in the area of digital security since 1990 and has become the primary international standard setter in this area. OECD Recommendations on digital security support stakeholders in developing digital security policies for economic and social prosperity, in line with the OECD’s mandate to help governments develop 'better policies for better lives'.

As our online and offline lives become increasingly interwoven, policy makers have to consider how to protect individual interests and rights. This paper considers the impact of digital transformation on internationally recognised human rights, legal and constitutional rights, and domestically protected interests. It sets out three case studies, freedom of expression, privacy and Internet access, and provides a brief overview of current international and domestic initiatives to protect 'rights in the digital age'. The paper sets the scene for further discussion on the issue and supports policy makers in designing and achieving a rights-oriented and human-centric digital transformation.