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  • 30-May-2024

    English

    Artificial intelligence and the changing demand for skills in Canada - The increasing importance of social skills

    Most workers who will be exposed to artificial intelligence (AI) will not require specialised AI skills (e.g. machine learning, natural language processing, etc.). Even so, AI will change the tasks these workers do, and the skills they require. This report provides first estimates for Canada on the effect of artificial intelligence on the demand for skills in jobs that do not require specialised AI skills. The results show that the skills most demanded in occupations highly exposed to AI are management, communication and digital skills. These include skills in budgeting, accounting, written communication, as well as competencies in basic word processing and spreadsheet software. The results also show that, in Canada, demand for social and language skills have increased the most over the past decade in occupations highly exposed to AI. Using a panel of establishments confirms the increasing demand for social and language skills, as well as rising demand for production and physical skills, which may be complementary to AI. However, the establishment panel also finds evidence of decreasing demand for business, management and digital skills in establishments more exposed to AI.

  • 17-May-2024

    English

    Occupational reallocation and mismatch in the wake of the Covid-19 pandemic - Cross-country evidence from an online job site

    Employment has recovered strongly from the COVID-19 pandemic despite large structural changes in labour markets, such as the widespread adoption of digital business models and remote work. We analyse whether the pandemic has been associated with labour reallocation across occupations and triggered mismatches between occupational labour demand and supply using novel data on employers’ job postings and jobseekers’ clicks across 19 countries from the online job site Indeed. Findings indicate that, on average across countries, the pandemic triggered large and persistent reallocation of postings and clicks across occupations. Occupational mismatch initially increased but was back to pre-pandemic levels at the end of 2022 as employers and workers adjusted to structural changes. The adjustment was substantially slower in countries that resorted to short-time work schemes to preserve employment during the pandemic.

  • 14-mai-2024

    Français

    La croissance de l’économie numérique dépasse celle de l’économie dans son ensemble dans les pays de l’OCDE

    Le secteur des technologies de l’information et des communications (TIC) a progressé en moyenne de 6.3 % entre 2013 et 2023, soit près de trois fois plus rapidement que l’ensemble de l’économie, dans les 27 pays de l’OCDE couverts par l’analyse.

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  • 6-May-2024

    English

    Defining AI incidents and related terms

    As AI use grows, so do its benefits and risks. These risks can lead to actual harms ('AI incidents') or potential dangers ('AI hazards'). Clear definitions are essential for managing and preventing these risks. This report proposes definitions for AI incidents and related terms. These definitions aim to foster international interoperability while providing flexibility for jurisdictions to determine the scope of AI incidents and hazards they wish to address.

  • 3-mai-2024

    Français

    Face aux évolutions technologiques rapides, l’OCDE met à jour les Principes sur l’IA

    Lors de la Réunion du Conseil au niveau des Ministres (RCM) de 2024 a été adoptée la version révisée des Principes de l’OCDE sur l’intelligence artificielle (IA), instrument qui a fait date dans ce domaine.

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  • 24-avril-2024

    Français

    Les politiques transformatives et la gouvernance anticipative jouent un rôle clé pour optimiser les avantages et maîtriser les risques liés aux technologies émergentes

    Les Ministres de la science et de la technologie l’ont souligné lors de leur réunion au niveau des Ministres à l’OCDE : il est crucial que les pouvoirs publics développent des approches coordonnées afin de tirer profit des opportunités offertes par les technologies nouvelles et émergentes, et de mieux gérer les risques futurs qui leur sont liés.

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  • 19-April-2024

    English

    Scientometrics

    This page provides information on OECD work on scientometrics and bibliometrics. This field has has evolved over time from the study of indices for improving information retrieval from peer-reviewed scientific publications (commonly described as the “bibliometric” analysis of science) to cover other types of documents and information sources relating to science and technology.

    Related Documents

  • 16-April-2024

    English

    The impact of Artificial Intelligence on productivity, distribution and growth - Key mechanisms, initial evidence and policy challenges

    This paper explores the economics of Artificial Intelligence (AI), focusing on its potential as a new General-Purpose Technology that can significantly influence economic productivity and societal wellbeing. It examines AI's unique capacity for autonomy and self-improvement, which could accelerate innovation and potentially revive sluggish productivity growth across various industries, while also acknowledging the uncertainties surrounding AI's long-term productivity impacts. The paper discusses the concentration of AI development in big tech firms, uneven adoption rates, and broader societal challenges such as inequality, discrimination, and security risks. It calls for a comprehensive policy approach to ensure AI's beneficial development and diffusion, including measures to promote competition, enhance accessibility, and address job displacement and inequality.

  • 10-April-2024

    English

    Artificial intelligence and the changing demand for skills in the labour market

    Most workers who will be exposed to artificial intelligence (AI) will not require specialised AI skills (e.g. machine learning, natural language processing, etc.). Even so, AI will change the tasks these workers do, and the skills they require. This report provides first estimates for the effect of artificial intelligence on the demand for skills in jobs that do not require specialised AI skills. The results show that the skills most demanded in occupations highly exposed to AI are management and business skills. These include skills in general project management, finance, administration and clerical tasks. The results also show that there have been increases over time in the demand for these skills in occupations highly exposed to AI. For example, the share of vacancies in these occupations that demand at least one emotional, cognitive or digital skill has increased by 8 percentage points. However, using a panel of establishments (which induces plausibly exogenous variation in AI exposure), the report finds evidence that the demand for these skills is beginning to fall.

  • 10-April-2024

    English

    Artificial intelligence and wage inequality

    This paper looks at the links between AI and wage inequality across 19 OECD countries. It uses a measure of occupational exposure to AI derived from that developed by Felten, Raj and Seamans (2019) – a measure of the degree to which occupations rely on abilities in which AI has made the most progress. The results provide no indication that AI has affected wage inequality between occupations so far (over the period 2014-2018). At the same time, there is some evidence that AI may be associated with lower wage inequality within occupations – consistent with emerging findings from the literature that AI reduces productivity differentials between workers. Further research is needed to identify the exact mechanisms driving the negative relationship between AI and wage inequality within occupations. One possible explanation is that low performers have more to gain from using AI because AI systems are trained to embody the more accurate practices of high performers. It is also possible that AI reduces performance differences within an occupation through a selection effect, e.g. if low performers leave their job because they are unable to adapt to AI tools by shifting their activities to tasks that AI cannot automate.
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