Transfer: European Review of Labour and Research

This article addresses the challenges raised by the introduction of algorithmic management and artificial intelligence in the world of work, focusing on the risks that new managerial technologies present for fundamental rights and principles, such as non-discrimination, freedom of association and the right to privacy. The article argues that collective bargaining is the most suitable regulatory instrument for responding to these challenges, and that current EU legislative initiatives do not adequately recognise the role of collective bargaining in this area. It also maps current initiatives undertaken by national trade union movements in Europe to govern algorithmic management.

In this article, we consider the legal frameworks that enable workers to influence the deployment of new workplace technologies in the United Kingdom and the future of worker voice and algorithmic management in a post-Brexit Britain. The article demonstrates how the legal mechanisms that facilitate voice at work, primarily collective bargaining via trade unions, can be leveraged to influence employers’ choices regarding algorithmic management. However, it also identifies both familiar and novel challenges regarding using these routes to ‘negotiate the algorithm’. The article then outlines major regulatory proposals emerging from the EU that would establish greater co-determination in this context and assesses their relevance to the UK labour market. It concludes by considering whether specific regulatory measures are necessary in the UK context to enhance the exercise of worker voice regarding the deployment of algorithmic management and close the widening gap between the position of UK and EU workers.

The use of artificial intelligence (AI) is changing the world of work. For trade unions, the issue of how to regulate the use of AI is a central but difficult topic because the technology is still at an early stage and experience on its use limited. Focusing on Germany, this article addresses the following questions: (1) what areas of application and use cases for AI are relevant for trade unions and works councils?, (2) what role do trade union positions and demands play in the political discussion on regulating the use of AI?, (3) what strategies are trade unions using to influence the regulation and use of AI in the workplace?, and (4) what experiences are they gaining during this process? Reviewing trade union strategies, this article shows which concepts of human-centred AI the trade unions are trying to promote, how they try to ensure that works councils and trade unionists get appropriate training to understand the new technologies, and how dealing with AI is changing the way works councils work. The article also shows how the characteristics of the German system of industrial relations influence discussions on AI and the processes of implementing it in the workplace.

This article discusses the risks that artificial intelligence (AI) poses for work. It classifies risks into two types, direct and indirect. Direct risks are AI-induced forms of discrimination, surveillance and information asymmetries at work. Indirect risks are enhanced workplace automation and the increasing ‘fissurisation’ of work. Direct and indirect risks are illustrated using the example of the transport and logistics sector. We discuss policy responses to both types of risk in the context of the German economy and argue that the policy solutions need to differ according to the type of risk. Direct risks can be addressed by European and national regulation against discrimination, surveillance and information asymmetries. As for indirect risks, the first step is to monitor the risks so as to gain an understanding of sector-specific transformations and establish relevant expertise and competence. This way of addressing AI-induced risks at work will help to improve the prospects of decent work, fair remuneration and adequate social protection for all.

The extension of artificial intelligence (AI) and algorithmic management mechanisms by companies has led to growing trade union demands to regulate their use. This article explores the role of collective bargaining and employee participation mechanisms in regulating the use by companies of AI and algorithms. This is done through a comparative analysis of institutional developments at EU level, as well as in four countries with different industrial relations models (Denmark, Germany, Hungary and Spain). The article shows that there are remarkable differences between countries in the roles of social partners and in the combination of protective and participative mechanisms used to respond to the challenges of AI and algorithmic management. However, the analysis also serves to highlight the limits of existing institutions and practices to cope with the complexity of challenges associated with AI and algorithmic management. This calls for institutional adaptation and additional regulatory efforts at EU and national levels to support collective bargaining.

Artificial intelligence (AI)-based algorithms are increasingly used to monitor employees and to automate management decisions. In this article, we ask how worker representatives adapt traditional collective voice institutions to regulate the adoption and use of these tools in the workplace. Our findings are based on a comparative study of union and works council responses to algorithmic management in contact centres from two similar telecommunications companies in Germany and Norway. In both case studies, worker representatives mobilised collective voice institutions to protect worker privacy and discretion associated with remote monitoring and workforce management technologies. However, they relied on different sources of institutional power, connected to co-determination rights, enforcement of data protection laws, and labour cooperation structures.

This article examines union strategies towards the twin digital and green transitions, comparing the German and Belgian automotive industries. The drive towards net-zero and more digital economies is manifested through the move from fossil fuel-powered cars to electric cars, engendering a reorganisation of production, work and employment among car manufacturers. We identified two strategic union response patterns. While German unions are developing proactive strategies and proposals to influence and shape the ongoing transition of the automotive industry, Belgian unions are more passive, reacting primarily to management proposals and focusing narrowly on employment and working conditions without a broader strategy on how to influence the transformation of the automotive industry. We explain the observed cross-national differences by two factors: the importance of national institutions, i.e., the varying integration of labour into management decision-making, and the role of union knowledge regimes. The latter refers to internal union organisations and structures such as research departments, research institutes and foundations tasked with providing own research and funding external research on change topics from a union perspective, publishing studies and developing programmatic agendas, and disseminating the knowledge to union members through training, workshops and conferences.

The digitalisation of work is associated with a range of technologies, including digital platforms and so-called artificial intelligence (AI), as well as ideas about how they will improve productivity and competitiveness. This article analyses how unions anticipate the consequences of digital technologies and how they mobilise to address their impact on employment, skills, and quality of work. Drawing on qualitative research conducted in aerospace manufacturing in Belgium (Wallonia), Denmark and Canada (Quebec), our findings suggest that unions are mobilising contrasting frames and repertoires of action, drawing on traditional institutions, and experimenting with new ones to shape the future of work in the aerospace industry.