The COVID confinement measures and EU labour markets

This paper assesses the potential impact of the early 2020 COVID confinement measures on EU labour markets, on the basis of an analysis of the restrictions on economic activity imposed in three EU Member States (Italy, Spain and Germany). Following the legislative measures adopted, we classify all economic sectors into different categories according to the likely impact of the COVID crisis, and compare the share of employment that is likely to be strongly affected in each country. Once this is done, we apply these categories of sectors to recent data on EU employment and estimate the groups of workers that would be more or less affected by the economic lockdown measures. Finally, we use all this information to speculate about possible mid-term developments and broader socio-economic implications of the COVID crisis in Europe.JRC.B.4-Human Capital and Employmen

CAS: Centre for advanced studies

An introduction to the Centre for Advanced Studies.JRC.A.5-Scientific Developmen

Artificial Intelligence: A European Perspective

We are only at the beginning of a rapid period of transformation of our economy and society due to the convergence of many digital technologies. Artificial Intelligence (AI) is central to this change and offers major opportunities to improve our lives. The recent developments in AI are the result of increased processing power, improvements in algorithms and the exponential growth in the volume and variety of digital data. Many applications of AI have started entering into our every-day lives, from machine translations, to image recognition, and music generation, and are increasingly deployed in industry, government, and commerce. Connected and autonomous vehicles, and AI-supported medical diagnostics are areas of application that will soon be commonplace. There is strong global competition on AI among the US, China, and Europe. The US leads for now but China is catching up fast and aims to lead by 2030. For the EU, it is not so much a question of winning or losing a race but of finding the way of embracing the opportunities offered by AI in a way that is human-centred, ethical, secure, and true to our core values. The EU Member States and the European Commission are developing coordinated national and European strategies, recognising that only together we can succeed. We can build on our areas of strength including excellent research, leadership in some industrial sectors like automotive and robotics, a solid legal and regulatory framework, and very rich cultural diversity also at regional and sub-regional levels. It is generally recognised that AI can flourish only if supported by a robust computing infrastructure and good quality data: • With respect to computing, we identified a window of opportunity for Europe to invest in the emerging new paradigm of computing distributed towards the edges of the network, in addition to centralised facilities. This will support also the future deployment of 5G and the Internet of Things. • With respect to data, we argue in favour of learning from successful Internet companies, opening access to data and developing interactivity with the users rather than just broadcasting data. In this way, we can develop ecosystems of public administrations, firms, and civil society enriching the data to make it fit for AI applications responding to European needs. We should embrace the opportunities afforded by AI but not uncritically. The black box characteristics of most leading AI techniques make them opaque even to specialists. AI systems are currently limited to narrow and well-defined tasks, and their technologies inherit imperfections from their human creators, such as the well-recognised bias effect present in data. We should challenge the shortcomings of AI and work towards strong evaluation strategies, transparent and reliable systems, and good human-AI interactions. Ethical and secure-by-design algorithms are crucial to build trust in this disruptive technology, but we also need a broader engagement of civil society on the values to be embedded in AI and the directions for future development. This social engagement should be part of the effort to strengthen our resilience at all levels from local, to national and European, across institutions, industry and civil society. Developing local ecosystems of skills, computing, data, and applications can foster the engagement of local communities, respond to their needs, harness local creativity and knowledge, and build a human-centred, diverse, and socially driven AI. We still know very little about how AI will impact the way we think, make decisions, relate to each other, and how it will affect our jobs. This uncertainty can be a source of concern but is also a sign of opportunity. The future is not yet written. We can shape it based on our collective vision of what future we would like to have. But we need to act together and act fast.JRC.B.6-Digital Econom

Market power and artificial intelligence work on online labour markets. Bruegel Working Paper December 2021.

We investigate three alternative but complementary indicators of market power on one of the largest online labour markets (OLMs) in Europe: (1) the elasticity of labour demand, (2) the elasticity of labour supply, and (3) the concentration of market shares. We explore how these indicators relate to an exogenous change in platform policy. In the middle of the observation period, the platform made it mandatory for employers to signal the rates they were willing to pay, as given by the level of experience required to perform a project: entry, intermediate or expert level. We find a positive labour supply elasticity ranging between 0.06 and 0.15, which is higher for expert-level projects. We also find that the labour demand elasticity increased while the labour supply elasticity decreased after the policy change. Based on this, we argue that market-designing platform providers can influence the labour demand and supply elasticities on OLMs with the terms and conditions they set for the platform. We also explore the demand for and supply of AI-related labour on the OLM under study. We provide evidence of a significantly higher demand for AI-related labour (ranging from +1.4 percent to +4.1 percent) and a significantly lower supply of AI-related labour (ranging from -6.8 percent to -1.6 percent) than for other types of labour. We also find that workers on AI projects receive 3.0 percent to 3.2 percent higher wages than workers on non-AI projects

The changing nature of work and skills in the digital age

This report aims to shed light on some of the key drivers which are worth taking into account when assessing the effect of new technologies on the future of work and skills. It combines a synthesis of the most recent and robust scientific evidence available with original JRC research on issues which have been often overlooked by existing studies. In particular, the report provides new insights on the interplay between automation and work organisation, the extent and nature of platform work, and the patterns of occupational changes across EU regions. The first chapter discusses the impact of technology on employment. It overviews the most recent estimates on technology-induced job creation and destruction, and provides new insights on the role of workplace organisation in shaping the effect of new technologies on labour markets. The second chapter discusses how skills needs are shifting towards digital and non-cognitive skills, showing evidence of an increasing shortage of these skills in the EU, which education systems are not fully tackling yet. The third chapter reviews the opportunities and challenges related to the recent upwards trend in new forms of employment in the EU, focusing on the results of the second wave of the COLLEEM survey on platform work in the EU. The final chapter presents results from a new JRC-Eurofound study on the patterns of occupational change in EU regions in the last 15 years which shows that low-wage jobs have increasingly concentrated in peripheral regions while higher-wage jobs are becoming more and more concentrated in capital regions, leading to increasing territorial disparities, both across and within EU Member States.JRC.B.7-Knowledge for Finance, Innovation and Growt

Artificial Intelligence at the JRC: 2nd workshop on Artificial Intelligence at the JRC, Ispra 5th July 2019

This document presents the contributions discussed at the second institutional workshop on Artificial Intelligence (AI), organized by the Joint Research Centre (JRC) of the European Commission. This workshop was held on 05th July 2019 at the premises of the JRC in Ispra (Italy), with video-conference to all JRC's sites. The workshop aimed to gather JRC specialists on AI and Big Data and share their experience, identify opportunities for meeting EC demands on AI, and explore synergies among the different JRC's working groups on AI. In comparison with the first event, according to the JRC Director General Vladimír Šuchav, the activities and results presented in this second workshop demonstrated a significant development of AI research and applications by JRC in different policy areas. He suggested to think about replicating the event at the premises of diverse policy DGs in order to present and discuss the clear opportunities created by JRC activities. After the opening speech by the JRC Director General Vladimír Šuchav, the research and innovation presentation were anticipated by two presentations by Alessandro Annoni and Stefano Nativi. The first presentation dealt with the results of one year of AI@JRC and six months of fully operational AI&BD community of practice1. The second presentation reported the results of the AI competences survey at JRC. The research and innovation contributions consisted in flash presentations (5 minutes) covering a wide range of areas. This report is structured according to the diverse domain areas addressed by the presenters. While the first part of the workshop was mainly informative, in the second part we collectively discussed about how to move on and evolve the AI&BD community of practice.JRC.B.6-Digital Econom