Platform Workers in Europe Evidence from the COLLEEM Survey

The recent surge of digital labour platforms has led to new forms of work organisation and tasks distribution across the workforce. This has raised several questions about the functioning and the benefits deriving from the reorganisation of work that those platforms entail and the associated risks. The European Commission assessed online platforms in a May 2016 communication, focusing on both their innovation opportunities and regulatory challenges. In June 2016 the Commission also adopted its European Agenda for the Collaborative Economy, which clarified the concept and provided some guidance on the employment status of platform workers and the EU definition of worker. The European Pillar of Social Rights aims to address some of the policy challenges associated to new forms of employment, including platform work. As accompanying initiatives, the Commission presented in December 2017 a proposal for a new Directive on transparent and predictable working conditions, and in March 2018 a proposal for a Council Recommendation on access to social protection for workers and the self-employed. A crucial issue in designing the policy response to the emergence of digital labour platforms is the lack of reliable evidence. In 2017, the JRC conducted the COLLEEM pilot survey , an initial attempt to provide quantitative evidence on platform work, responding to calls by the European Council and the European Parliament. The survey provides a basis for an initial estimation of platform work in 14 Member States . How many platform workers are there in Europe? The COLLEEM survey contains a direct measure of service provision via platforms by the respondents in 14 EU Member States. It asks whether the respondent has ever gained income from different online sources, among which there are two corresponding to labour service platforms: "providing services via online platforms, where you and the client are matched digitally, payment is conducted digitally via the platform and the work is location-independent, web-based" and "providing services via online platforms, where you and the client are matched digitally, and the payment is conducted digitally via the platform, but work is performed on-location". Estimates indicate that on average 10% of the adult population has ever used online platforms for the provision of some type of labour services. However, less than 8% do this kind of work with some frequency, and less than 6% spend a significant amount of time on it (at least 10 hours per week) or earn a significant amount of income (at least 25% of the total). Main platform workers are defined as those who earn 50% or more of their income via platforms and/or work via platforms more than 20 hours a week. They account for about 2% of the adult population on average. There are significant differences across countries: the UK has the highest incidence of platform work. Other countries with high relative values are Germany, the Netherlands, Spain, Portugal and Italy. By contrast, Finland, Sweden, France, Hungary and Slovakia show very low values compared to the rest. Who are the platform workers? The typical European platform worker is a young male, educated to a degree level. The proportion of women decreases as the intensity of platform work increases. There is, however, substantial heterogeneity across countries. The fact that most platform workers are highly educated is not surprising given that to be able to provide services via platform one needs to be a savvy internet user, and internet use tends to be correlated with higher education. Despite conventional wisdom, a typical platform worker is likely to have a family and kids. Furthermore, regardless of age, platform workers tend to have fewer years of labour market experience than the average worker. Employment status of platform workers The employment status of platform workers is a controversial issue and one of the most relevant from a policy perspective. Estimates from the COLLEEM survey reveal that when asked about their current employment situation, 75.7 % of the platform workers claimed to be an employee (68.1%) or self-employed (7.6%). A first possibility is that platform workers also have a regular job as employees or self-employed (in a more traditional sense) and are therefore covered by standard employment legislation. A second possibility is that platform workers are not really sure of their employment status and may see themselves as employees, only because they provide a certain type of service with regularity through the same platform. This is surprising because in most cases the providers of labour services via platforms are formally independent contractors rather than employees, but it also reflects the uncertainty surrounding this issue in policy and even legal debates around Europe. In short, the labour market status of platform workers remains unclear, even to themselves. Interviewed platform workers declared themselves to be self-employed (as main or side job) in 54% of the cases, while a large minority (38 %) claim to be an employee. What types of services are provided and coordinated via labour platforms? Labour services provided by digital labour platforms can be broadly distinguished as services performed digitally (i.e. micro tasks, clerical and data entry, etc.) or services performed on-location (i.e. transport, delivery, housekeeping, etc.). On average half of the overall platform workers perform both digital and on-location services. According to the level of skills required by different services we can distinguish between: i) professional services (high skills); ii) non-professionals services (medium skills) and iii) on-location services (low skills). The majority of platform workers provide more than one type of services, and are active on two or more platforms, often combining high- and low skilled activities, suggesting that some platform workers may be reducing income risk (and possibly increasing variety in work). The most common labour service provided is 'online clerical and data entry'. However, the largest proportion of platform workers provides professional services. Gender also influences the type of services provided: 'software development' and 'transport' are the most male dominated services. By contrast, 'translation' and 'on-location services' are the mostly female dominated ones. The market for digital services is global and this may lead to some specialisation on services provided for some countries. The majority of the services do not show much variety across countries; however some country patterns could be identified. Slovakia and Croatia appear to specialise in services that require a low-medium level of education. Romania is amongst the top countries for the provision of non-professionals services The Netherlands mostly provides services that require high digital skills such as software and interactive. One third of platform workers have a mismatch between the lower-skilled tasks they perform and their high level of education/skills. What are the motivations and conditions of platform work? Flexibility and autonomy are frequently mentioned motivations for platform work, but these results should be interpreted cautiously: the lack of alternatives is also mentioned as an important motive for working on platforms. The conditions of platform work are more polarised than those of regular workers. Working conditions for platform workers appear to be flexible, but also intense. Platform work can be arduous and, for some workers, involving long hours. Key policy implications The implications of digital labour platforms for work and employment are ambivalent. On the one hand, they can lower the entry barriers to the labour market, facilitate work participation through better matching procedures and ease the working conditions of specific groups (i.e. workers with strong family responsibilities, people with disabilities or health conditions, youth, people not in education, employment or training – NEETs -, older workers, long-term unemployed, people with a migrant background). On the other hand, digital labour platforms typically rely on a workforce of independent contractors whose conditions of employment, representation and social protection are at best unclear, at worst clearly unfavourable. The status of platform workers is probably the most complex policy issue at stake. The actual nature of the employment relationship is nebulous in most cases. This is particularly problematic because employment status is key for access to social security, training entitlements and coverage by legislation on working conditions. Therefore the need for a clarification of the employment status of platform workers appears obvious. The findings presented in this report suggest an emerging phenomenon of increasing importance but still modest in size. If platform work remains significant but small in the future, a two-pronged policy response is likely to suffice, focusing on (i) fully grasping its job creation and innovation opportunities and (ii) adjusting existing labour market institutions and welfare systems to the new reality and mitigating its potentially negative consequences for working careers and working conditions. Examples of this are the proposal for a directive on transparent and predictable working conditions, and the proposal for a Council Recommendation on access to social protection for workers and the self-employed in the social fairness package adopted by the Commission on 13 March 2018 as well as the targeted legislative measures adopted by some countries. However, if platform work continues to grow in size and importance to become a more significant reality in our labour markets, or if some of the key features of platform work spread across other forms of employment as already seem to be happening in some cases, policy interventions may need to be of a more ambitious nature. Indeed, a scenario of general "platformisation" of labour markets and working conditions would require a profound rethinking of labour market institutions and welfare systems. Furthermore, a scenario in which there would be a significant increase in the provision of digitally performed platform work - people providing professional and non-professional labour services from their own places of origin - might lead to more opportunities for people to provide professional and non-professional labour services from their own places of origin – on-location services excluded - through a digital single market. A serious challenge in this scenario is the increased exposure of workers to global competition. From the regulatory point of view, the categories catering for the specificities of platform workers might be in need for a review. In a labour market with more unstable working careers, a wider use of schemes based on personal accounts for workers' entitlements might be required. From the social protection point of view, progress towards insurance models not based on employment status could be necessary.JRC.B.4-Human Capital and Employmen

Does AI Qualify for the Job?: A Bidirectional Model Mapping Labour and AI Intensities

[EN] In this paper we present a setting for examining the relation between the distribution of research intensity in AI research and the relevance for a range of work tasks (and occupations) in current and simulated scenarios. We perform a mapping between labour and AI using a set of cognitive abilities as an intermediate layer. This setting favours a two-way interpretation to analyse (1) what impact current or simulated AI research activity has or would have on labour-related tasks and occupations, and (2) what areas of AI research activity would be responsible for a desired or undesired effect on specific labour tasks and occupations. Concretely, in our analysis we map 59 generic labour-related tasks from several worker surveys and databases to 14 cognitive abilities from the cognitive science literature, and these to a comprehensive list of 328 AI benchmarks used to evaluate progress in AI techniques. We provide this model and its implementation as a tool for simulations. We also show the effectiveness of our setting with some illustrative examples.This material is based upon work supported by the EU (FEDER), and the Spanish MINECO under grant RTI2018-094403-B-C3, the Generalitat Valenciana PROMETEO/2019/098. F. Martínez-Plumed was also supported by INCIBE (Ayudas para la excelencia de los equipos de investigación avanzada en ciberseguridad), the European Commission (JRC) HUMAINT project (CT-EX2018D335821-101), and UPV (PAID-06-18). J. H-Orallo is also funded by an FLI grant RFP2-152.Martínez-Plumed, F.; Tolan, S.; Pesole, A.; Hernández-Orallo, J.; Fernández-Macías, E.; Gómez, E. (2020). Does AI Qualify for the Job?: A Bidirectional Model Mapping Labour and AI Intensities. Association for Computing Machinery (ACM). 94-100. https://doi.org/10.1145/3375627.3375831S9410

Measuring the Occupational Impact of AI: Tasks, Cognitive Abilities and AI Benchmarks

[EN] In this paper we develop a framework for analysing the impact of Artificial Intelligence (AI) on occupations. This framework maps 59 generic tasks from worker surveys and an occupational database to 14 cognitive abilities (that we extract from the cognitive science literature) and these to a comprehensive list of 328 AI benchmarks used to evaluate research intensity across a broad range of different AI areas. The use of cognitive abilities as an intermediate layer, instead of mapping work tasks to AI benchmarks directly, allows for an identification of potential AI exposure for tasks for which AI applications have not been explicitly created. An application of our framework to occupational databases gives insights into the abilities through which AI is most likely to affect jobs and allows for a ranking of occupations with respect to AI exposure. Moreover, we show that some jobs that were not known to be affected by previous waves of automation may now be subject to higher AI exposure. Finally, we find that some of the abilities where AI research is currently very intense are linked to tasks with comparatively limited labour input in the labour markets of advanced economies (e.g., visual and auditory processing using deep learning, and sensorimotor interaction through (deep) reinforcement learning).Tolan, S.; Pesole, A.; Martínez-Plumed, F.; Fernández-Macías, E.; Hernández-Orallo, J.; Gómez, E. (2021). Measuring the Occupational Impact of AI: Tasks, Cognitive Abilities and AI Benchmarks. Journal of Artificial Intelligence Research. 71:191-236. https://doi.org/10.1613/jair.1.12647S1912367

The organisational and geographic diversity and innovation potential of EU‑funded research networks

Public funding of research improves the systemic conditions of entrepreneurial ecosystems. It provides early-stage financing to technologies that form the basis for new products and services. In addition to financial support, instruments as the EC Framework Programmes (FP) facilitate the creation of research networks. By bringing together organisations of various types and geographic origins and increasing the diversity of their interactions, the instrument seeks to accelerate a discovery process in which organisations attempt to bring desired innovations to the market and society. In this paper, we examine the impact of organisational and geographic diversity of partnerships in EU-funded research networks on the commercial potential of their innovations. We explore a sample of 603 collaborative research projects supported by European FPs. We use data from the Innovation Radar, a unique survey database developed by DG CONNECT to assess the innovation outcomes of FP projects in ICT. We show that innovations developed by research networks with a higher organisational diversity have more commercial potential. This finding supports the idea that policies improving systemic conditions of entrepreneurship ecosystems through the creation of institutionally diverse research networks can have beneficial effects on the commercialisation potential of innovations developed in FP projects. In contrast, research networks with a wider range of internationally dispersed research partners are likely to have less innovation potential. This may suggest the existence of coordination and communication difficulties in FP projects where geographic diversity is greater.JRC.B.6-Digital Econom

Modes of ICT Innovation: Evidence from the Community Innovation Survey

This report analyses innovative activities by ICT producing firms and provides evidence on innovative activity of the ICT sector, compared to the overall economy. This analysis, based on a set of different indicators, aims at providing a deeper understanding of the modes of innovation adopted by ICT producing firms. In order to do so, we created a panel dataset matching the information collected by different Community Innovation Survey (CIS) waves from 2004 up to 2012 in twenty EU Member States and we investigated the major innovation patterns comparing the ICT sector to the whole economy. The main findings show that, in general, firms in the ICT sector tend to innovate more with respect to the total economy: both the shares of innovators and technological innovators are consistently higher within the ICT sector than in the total economy. Moreover, the ICT sector is characterized by a higher share of innovative firms performing R&D and a higher share of Framework Programme funded innovative firms. In order to capture the modes of innovation of ICT producing firms, we used "complex" indicators that condense information from more than one measure and allow making multi-dimensional phenomena uni-dimensional. These complex indicators indicate that the share of international and domestic innovators is higher among ICT firms than among the whole economy. In other words, ICT firms tend to have a higher than average in-house R&D capability and to be more likely to introduce new-to-the market product or process innovations in both international and domestic markets. Looking at international or domestic "modifiers" (i.e. firms that mainly adopt and/or modify innovation made by others) we do not find evidence that -relative to the average firm- ICT producing firms are more likely to modify or adopt innovations developed elsewhere

Modes of ICT Innovation: Evidence from the Community Innovation Survey

This report analyses innovative activities by ICT producing firms and provides evidence on innovative activity of the ICT sector, compared to the overall economy. This analysis, based on a set of different indicators, aims at providing a deeper understanding of the modes of innovation adopted by ICT producing firms. In order to do so, we created a panel dataset matching the information collected by different Community Innovation Survey (CIS) waves from 2004 up to 2012 in twenty EU Member States and we investigated the major innovation patterns comparing the ICT sector to the whole economy. The main findings show that, in general, firms in the ICT sector tend to innovate more with respect to the total economy: both the shares of innovators and technological innovators are consistently higher within the ICT sector than in the total economy. Moreover, the ICT sector is characterized by a higher share of innovative firms performing R&D and a higher share of Framework Programme funded innovative firms. In order to capture the modes of innovation of ICT producing firms, we used "complex" indicators that condense information from more than one measure and allow making multi-dimensional phenomena uni-dimensional. These complex indicators indicate that the share of international and domestic innovators is higher among ICT firms than among the whole economy. In other words, ICT firms tend to have a higher than average in-house R&D capability and to be more likely to introduce new-to-the market product or process innovations in both international and domestic markets. Looking at international or domestic "modifiers" (i.e. firms that mainly adopt and/or modify innovation made by others) we do not find evidence that -relative to the average firm- ICT producing firms are more likely to modify or adopt innovations developed elsewhere

Digital Labour Platforms in Europe: Numbers, Profiles, and Employment Status of Platform Workers

This report explores three issues related to the growing phenomenon of Digital Labour Platforms: firstly, how to measure platform work as a form of employment incorporating elements such as regularity of provision, time allocated and income generated; on this basis, and drawing on a new dedicated survey (COLLEEM), the article quantifies and categorises platform work into sporadic, secondary and main. Secondly, it provides an empirical investigation of the association between individual characteristics, such as gender, age, family composition, education and motivation, and the probability of carrying out particular types of platform work, such as microtasking, creative services, software development, transportation and so on. The analysis highlights substantial heterogeneity in the attributes and motivations of the workers performing different tasks. Finally, it discusses the employment status of platform workers and provides some descriptive statistics suggesting that a large share of platform workers perceive themselves as employees, even though they are in most cases legally considered self-employed.JRC.B.4-Human Capital and Employmen

When large companies build ecosystems, should small companies join? A role for open innovation

The rise of the open innovation paradigm has encouraged the creation of innovation networks (ecosystems) involving a mix of partners: universities, research laboratories, start-up companies, small and medium- sized enterprises (SMEs), multinationals and governments. Physical proximity is an essential driver of open innovation e ectiveness. It enables the exchange of ideas and inside/outside exploitation of knowledge and resources. This paper investigates how some large companies invested in key relationships with external innovation partners through the creation and the orchestration of open ecosystems (e.g. open research campuses). By contrast, small companies cannot a ord to create and orchestrate their own local research ecosystem, but they do have the option to join or co-locate within existing ecosystems. This paper draws lessons from two of 13 case studies we collected, and compares and contrasts the experience of ecosystem builders and ecosystem joiners