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Growing datafication of work environments deployed by new technological capacities built on Big Data and Artificial Intelligence (AI) enhanced systems are disrupting the industrial relations scene in many ways. These technologies increase the possibilities of collecting, combining and using data on workplace and workers. However, the use of these technologies very often lacks transparency and is semiautonomous, thus jeopardising traditional forms of collective employee involvement, transparency or even data protection regulations. As AI and algorithmic decisions are increasingly widespread in employment relations, concerns are being raised about the impact of these practices on workers’ voice, influence and working conditions.

The spread of AI and the adoption of Algorithmic Management (AM) entail the digitalisation and automation of an increasing number of processes and decisions, ranging from work organisation, recruitment and dismissal to evaluation and performance appraisal, among others. However, there is still very little empirical evidence on how AI is impacting workplaces and labour markets across sectors and countries, thus hindering the development of a consistent framework for governing AM.


The overall aim of the INCODING project is to analyse the role of collective bargaining and other forms of employee involvement at workplace level in (co) governing the black box of AM with a view to identify the main challenges for workers and their representatives, and explore its contribution to Inclusive Algorithmic Management understood as the turn to more transparency in the design and implementation of AI based systems at company level and guaranteeing human oversight of automated processes


The overall objective translated into the following specific objectives:

  • Understand how AM is reframing the three principal dimensions of management control (direction, evaluation and discipline) within organisations.
  • Identify the key shop-floor labour management processes and decisions currently embedded in AM schemes.
  • Identify the main actors currently shaping the deployment and implementation of AM systems within organisations.
  • Map the emerging organisational and inter-organisational hierarchies underlying AM implementation: who provides the data? who checks the data? who analyses the data? who has access to data?
  • Analyse how the design of algorithms prefigures work organisation and the labour process.
  • Understand the potential impact of AM on workers’ collective voice, autonomy, independence and participation opportunities throughout organisations.


The aim of the INCODING project is to carry out a comparative analysis of the governance of AM at national and supra-national level. This will be implemented through a company case study methodology in four countries and two sectors. This analysis will shed light on the potential impact of the data-led reorganisation of workplaces which, promoted by software development and cloud provider companies, empowers AM schemes and has a multi-dimensional impact on employment relations and collective bargaining. Special attention in the analysis will be paid to the effects of these technologies on work intensification, standardisation and optimisation of the production process, etc. and how potential negative impacts are mediated by employee involvement structures.