Democracy at Work through Transparent and Inclusive Algorithmic Management

Project Details

Description

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 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 AIbased systems at company level and guaranteeing human oversight of automated processes. Moreover, the project also aims to learn from best practices, develop collective bargaining strategies and provide recommendations for trade unions, workers’ representatives and employers negotiate the conditions under which AM and AI systems are used.
AcronymINCODING
StatusFinished
Effective start/end date1/09/2129/02/24

Collaborative partners

  • Universitat Autònoma de Barcelona (UAB) (lead)
  • University of Copenhagen (UCPH) (Project partner)
  • Wissenschaftszentrum Berlin fur Sozialforschung gGmbH (Social Science Research Center Berlin Ltd.-Non commercial) (Project partner)
  • Centre for Social Sciences (Project partner)
  • Zentrum für Soziale Innovation (Centre for Social Innovation - ZSI) (Project partner)

UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):

  • SDG 8 - Decent Work and Economic Growth

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