Data4Workers-Switzerland

Data4Workers-Switzerland🇨🇭: Participatory Methodology for AI Accountability in the Gig Economy: A Comparative Study of (Digital) Labour Conditions Between the French- and German-Speaking Cantons of Switzerland

Research Questions

  1. How do algorithms used by food delivery, cleaning, and care platforms define task allocation, working hours, and income for workers?
    1. 1. How do differences across sectors (food delivery, cleaning, care) and across linguistic regions (French- and German-speaking cantons) shape algorithmic management and its effects on working conditions?  
  2. How can existing legal frameworks for data access and algorithmic transparency rights be leveraged to generate algorithmic accountability? 

Summary

The use of algorithmic management in the gig economy has sparked international debate about working conditions. Whilst European countries are developing algorithmic transparency regulations, their practical implementation for protecting labour rights remains unclear—particularly in Switzerland. Furthermore, existing research tends to focus on male-dominated sectors such as delivery and ride-hailing, often overlooking female-dominated sectors.

This one-year project combines the sociology of work with data science to examine how data protection and algorithmic transparency regulations can improve platform workers’ livelihoods across Switzerland. Using computational methods, we will analyse platform data from both male-dominated (food delivery) and female-dominated (cleaning) sectors in Bern, Geneva, Vaud and Zurich.

This participatory research is being conducted in collaboration with workers, academics, civic organisations and legal experts to:

  • Analyse how algorithms automate task allocation, working time, and fare calculations
  • Develop data analysis tools for workers and unions
  • Study the impact of algorithmic management on working conditions across genders
  • Examine how different legal frameworks enable algorithmic transparency

This research will contribute to the global decent work agenda for platform workers by providing evidence-based insights into how algorithmic management affects working hours and income.

Sectors concerned: Food-delivery, cleaning and care.

#CalculativePower #GigEconomy #LabourRights #DecentWork #DigitalPlatforms #ParticipatoryScience #Research #AlgorithmicManagement #AIAccountability #Transparency

 
 
 

Key Goals

  • Analyse platform workers’ data to understand the impact of algorithmic management on wages and working hours
  • Compare how different regulatory frameworks influence worker-platform power dynamics
  • Create tools for workers to track their working time and recover their data

Funding
SPARK (Swiss National Science Foundation – SNSF)
Grant number: 228644

Research Leader

Dr Jessica Pidoux (UniNE)

Research Team

  • Prof. NĂşria Sánchez-Mira, Sofia Kypraiou, Julia Kopf, Mariame Tighanimine, Camille Budon, Prof. Jean-Philippe Dunand (UniNE)
  • Prof. Katarzyna Wac (UNIGE, Quality of Life Technologies Lab)

Partners
Local trade unions, technical partner Hestia.ai, NGO PersonalData.IO

Duration

January 2025 – December 2025

Outputs

  • Four regional workshops with workers on data access rights and data analysis
  • Analytics tool for algorithmic research
  • Statistical analysis of work schedules and income
  • Mathematical models for algorithmic accountability
  • Policy report with union recommendations
  • Two peer-reviewed publications
  • Public presentation event
 
 

Detailed information about the data processing during the project

Presentation of the project Data4Workers-Switzerland “Participatory Methodology for AI Accountability in the Gig Economy: A Comparative Study of (Digital) Labour Conditions Between the French- and German-Speaking Cantons of Switzerland” (Funded by FNS SPARK, ref.: U.03694: FN CRSK-1_228644). 

This Swiss project is led by the University of Neuchâtel in partnership with PersonalData.IO. 

The project collaborates with the international project Data4Workers “Decoding Algorithmic Management for Platform Workers’ Calculative Power” (Funded by the Internet Society Foundation) led by PersonalData.IO, and the research consortium: University of Neuchâtel, DigitalWORK project at ESADE University, QUIT project at Universitat Autònoma de Barcelona, and Prof. Francisca GĂştierrez  

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SUPPORT

This project is developed by the University of Neuchâtel in partnership with PersonalData.IO, funded by Swiss National Science Foundation, in collaboration with universities, local organisations and labor unions in Switzerland.