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AI language models are a key component of natural language processing (NLP), a field of artificial intelligence (AI) focused on enabling computers to understand and generate human language. Language models and other NLP approaches involve developing algorithms and models that can process, analyse and generate natural language text or speech trained on vast amounts of data using techniques ranging from rule-based approaches to statistical models and deep learning. The application of language models is diverse and includes text completion, language translation, chatbots, virtual assistants and speech recognition. This report offers an overview of the AI language model and NLP landscape with current and emerging policy responses from around the world. It explores the basic building blocks of language models from a technical perspective using the OECD Framework for the Classification of AI Systems. The report also presents policy considerations through the lens of the OECD AI Principles.

This report analyses the use of artificial intelligence (AI) in firms across 11 countries. Based on harmonised statistical code (AI diffuse) applied to official firm-level surveys, it finds that the use of AI is prevalent in ICT and Professional Services and more widespread across large – and to some extent across young – firms. AI users tend to be more productive, especially the largest ones. Complementary assets, including ICT skills, high-speed digital infrastructure, and the use of other digital technologies, which are significantly related to the use of AI, appear to play a critical role in the productivity advantages of AI users.

National Statistical Offices face a growing policy demand for better statistics on digital platform employment and work. New statistical definitions are needed to avoid undercounting the number of people involved in these jobs. In addition, new sources of data, including non-official ones, may be needed to meet the statistical challenges of measuring digital platform employment and work. The OECD, the International Labour Organisation and the European Commission have joined forces to produce this Handbook on Measuring Digital Platform Employment and Work, which assesses measurement options and provides first recommendations on these issues. The Handbook first proposes a general definition of digital platform work and a conceptual framework that helps identify the key features of digital platform employment and work, which statisticians should bear in mind when designing their research objectives and operational protocol. The Handbook then reviews the main statistical vehicles used for measuring digital platform employment, and discusses previous statistical initiatives by National Statistical Offices through the lens of its conceptual framework.

The OECD Public Governance Review of the Czech Republic identifies priority governance areas for reform in the Czech Republic and offers recommendations to strengthen the effectiveness, agility and responsiveness of the country’s public sector. The review first provides a snapshot on the effectiveness of the public administration and its capacity to address contemporary governance challenges, such as digitalisation and climate change. It then analyses a number of critical and priority public governance areas including citizen engagement, centre-of-government-led co-ordination and strategic planning, evidence-informed policy making in the Czech public administration, public administration at the local and regional level, human resources management in the public administration, and digital government. It also includes a case study on governance arrangements and regulations during the COVID-19 pandemic. The review provides recommendations for the Czech public administration to help it implement its Public Administration Reform Strategy: Client-oriented Public Administration 2030 (PAR), achieve the objectives of the PAR, and, ultimately, realise its longer-term sustainable development vision and commitments.

New OECD surveys of employers and workers in the manufacturing and finance sectors of seven countries shed new light on the impact that Artificial Intelligence has on the workplace —an under-researched area to date due to lack of data. The findings suggest that both workers and their employers are generally very positive about the impact of AI on performance and working conditions. However, there are also concerns, including about job loss—an issue that should be closely monitored. The surveys also indicate that, while many workers trust their employers when it comes to the implementation of AI in the workplace, more can be done to improve trust. In particular, the surveys show that both training and worker consultation are associated with better outcomes for workers.

As societies become increasingly digital, cyber security has become a priority for individuals, companies and nations. The number of cyber attacks is exceeding defence capabilities, and one reason for this is the lack of an adequately skilled cyber security workforce. This report analyses the demand for cyber security professionals in Australia, Canada, New Zealand, the United Kingdom and the United States using information contained in online job postings. The analysis looks at recent trends in the demand for workers in different types of cyber security roles, the geographical distribution of cyber security job postings, and the changing skill requirements for professionals in this field. The report also looks at the supply side, zooming in on the landscape of cyber security education and training programmes in England (United Kingdom). It describes the different types of programmes provided in further and higher education, the profile of learners in these programmes and their outcomes. Finally, the report also looks at policies and initiatives adopted in England to make cyber security education and training programmes more accessible and relevant. This report is part of a larger initiative examining the evolution of policies and experiences in the cyber security profession around the world.

This report examines privacy-enhancing technologies (PETs), which are digital solutions that allow information to be collected, processed, analysed, and shared while protecting data confidentiality and privacy. The report reviews recent technological advancements and evaluates the effectiveness of different types of PETs, as well as the challenges and opportunities they present. It also outlines current regulatory and policy approaches to PETs to help privacy enforcement authorities and policy makers better understand how they can be used to enhance privacy and data protection, and to improve overall data governance.

The automotive sector is important across OECD countries in terms of value-added and R&D, but is also heavily affected by the green and the digital transformations. This paper offers a novel and holistic view of the automotive sector and its surrounding ecosystem based on a combination of Inter-Country Input-Output (ICIO) tables, patent data, mergers and acquisitions (M&A) transactions, cross-country micro-distributed data and firm-level balance sheet data. It identifies the boundaries of this industrial ecosystem including connected sectors (e.g. upstream and downstream) as well as knowledge and technology providers (e.g. universities or the digital industry). The paper documents emerging trends at the geographical and technological levels and provides a comprehensive assessment of the ecosystem’s changing microstructure, with a growing role of young and digital-intensive companies. Finally, it provides recommendations for effective public policies to support the automotive ecosystem, with a focus on innovation, competition and the growth of young firms.

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 study responds to six key questions about the impact that the demand for Artificial Intelligence (AI) skills is having on labour markets. What are the occupations where AI skills are most relevant? How do different AI-relevant skills combine in job requirements? How quickly is the demand for AI-related skills diffusing across labour markets and what is the relationship between AI skill demands and the demand for cognitive skills across jobs? Finally, are AI skills leading to a wage premium and how different are the wage returns associated with AI and routine skills? To shed light on these aspects, this study leverages Natural Language Processing (NLP) algorithms to analyse the information contained in millions of job postings collected from the internet.