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. Núria 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 Gútierrez  

Who is conducting this research?

The research is coordinated by: 

  • Dr. Jessica Pidoux (leading researcher), Prof. Núria Sánchez-Mirá (expert advisor) at University of Neuchâtel (CHE-192.771.761): A foundation supporting scientific research and higher education. More info at https://www.unine.ch. 

The main civic partner is: 

And the results of this project will allow us to conduct an international analysis with the following partners: 

  • Prof. Anna Ginès Fabrellas, Prof. Raquel Serrano (leading researchers) under the DigitalWORK project at Esade Foundation (CIF: G-59716761) within Ramon Llull University. 
  • Prof. Oscar Molina (leading researcher) under the project QUIT at Autonomous University of Barcelona (UAB) (NIF: Q-0818002-H). 
  • Prof. Francisca Gútierrez in Chile https://coes.cl/integrantes/francisca-gutierrez/, independent leading researcher for this project in Chile. She is professor, sociologist, at the Universidad Austral de Chile.  

According to the European General Data Protection Regulation, the University of Neuchâtel and PersonalData.IO are the co-responsible data controllers, and the other institutions act as authorised third parties processing data for analysis and reporting. 

📌 The University of Neuchâtel 
✔ The university is responsible for accessing and analysing your data recovered from platforms in their internal server CollectionHub, responsible for protecting your personal data and ensuring it is only used for research and tool development. 

📌 PersonalData.IO  
✔ Provides the technical infrastructure development and storage to process your data collected from platforms. The data will be stored in a secured OHV server once you upload it via digipower.academy, only for the purpose of transferring it to the researchers’ internal server. PersonalData.IO is responsible for protecting your personal data at this stage. The tools and software used in this project were developed based on specifications provided by the University of Neuchâtel according to a formal contract of cooperation. 
✔ Visualisations displayed on digipower.academy will never include personal data, and your identity will not be revealed outside your personal session. 

📌 Researchers from affiliated institutions 
✔ Will use the pseudonymised data for conducting the interviews and the workshops. Only anonymised and aggregated data will be used for research publications. 

Your data will be used in three ways: 

  1. Developing tools at digipower.academy
  • Your data will help create free, open-source tools that allow platform workers to analyse, aggregate, visualise and understand their own data. Rest assured: no identifying data will be published in the tool for the general public. 
  1. Research on platform workers’ conditions
  • Researchers will analyse your data to understand platform algorithms and analyse working time and income. You will be invited to discuss your experience through an individual interview and a collective workshop. 
  1. Data analysis with respect to labour law 
  • Researchers will assess how platform work aligns with national labour laws and results will be provided directly to you. At this point the data relates to your identity. Only aggregated, anonymised results will be used for research. 

Data storage duration: Personal or pseudonymised data for 4 years. It will be deleted by December 2028, but anonymous, aggregated data will be archived for research (as the process of publishing results and scientific publications is often long). 

🔹 Your contact details (email, phone, name, or pseudonym). 
🔹 Data recovered from platforms (file formats, data collection frequency). 
🔹 Interviews and workshops (audio recordings of your responses, researcher notes). 
🔹 Data visualisation to facilitate group analysis. 

Your data will be first pseudonymised for processing and analysis, and later anonymised for publications, meaning your name will never be used or published. 

For more information about the types of data recovered from platforms, check the privacy policies of each app you requested data from. According to those documents, it is possible that these files contain information such as date of birth, name, email, phone ID, geolocation, means of payment, and other sensitive information, such as photos. 

This is one of the reasons why we prioritise maximum protection in the design of this study and the tool that is made available to you (see How your data is protected section). 

The University of Neuchâtel will process and analyse your personal data collected from platforms. Only pseudonymised results of the files’ analysis will be shared with researchers from the project’s international partners. The analysis consists first in structuring and aggregating your data at different time levels (hourly, daily, weekly, yearly) and second, in performing additional calculations based on national labor laws (e.g., overtime work). 

Additionally, researchers will process locally the data from interviews and workshops they each respectively collected. Only anonymised results of the platform’s data and interview analysis will be shared with researchers at the international level. 

*The data analysis tools at https://digipower.academy/fr/experiences and the data spaces at https://digipower.academy/spaces will include a space dedicated to the platform where you work 

  • Your file with personal data is loaded only in your device’s memory (RAM) and disappears when you close the session if you do not provide consent to share your data. Your personal data is never transmitted over the internet or stored externally if you don’t provide consent. 
  • The tools convert data into a human-readable format (e.g., converting a .json file into a spreadsheet) so you can read it directly. We will also generate graphical visualisations that help you and researchers analyze your data. 
  • Your personal data is shared only if you explicitly provide consent. If so, your personal data is uploaded to OHV servers based in France, managed by PersonalData.IO, and is then pseudonymised, shared with researchers in Switzerland using the institutional server “CollectionHub” only for the specified purposes. 

📌 You can also decide to keep or delete the visualisations without sharing your data. If you don’t share your data and decide to delete the visualisations, refreshing the page will restart the session without storing any data. 

📌 The University of Neuchâtel and PersonalData.IO teams remain available to answer any questions at projecthome@unine.ch or projectdelivery@unine.ch 

During the Collaboration: 

✔ Your data is securely stored and managed by the University of Neuchâtel. All research data is hosted on the University of Neuchâtel’s secure server using the CollectionHub tool, which complies with institutional data protection and security standards. 

✔ PersonalData.IO is responsible only for the initial data collection. A dedicated server hosted by PersonalData.IO (at digipower.academy) on OVHcloud is used solely to allow workers to upload their files. Once uploaded, the data is securely transferred to the University of Neuchâtel. After the transfer, the original files are deleted from the OVH server. 

✔ Access is strictly limited. Only authorised staff from PersonalData.IO and the University of Neuchâtel can access the original data files. Partner researchers only access pseudonymised and pre-processed data, ensuring individual identities are protected. 

✔ Data is transferred securely. The OVH server is protected by industry-grade security protocols, including Anti-DDoS infrastructure. All data uploads are encrypted and authenticated using unique secret keys to ensure that only you and authorised personnel can access or transfer your files. 

✔ You stay in control of your data when using digipower.academy interface 

  • You choose whether or not to share your personal data with researchers 
  • If you don’t want to share your data, you can delete your file in the interface, so it’s not processed 

✔ Support is available. The team at PersonalData.IO, with expertise in exercising data access rights, is available to assist you in understanding and managing your data at every step of the process. Write them at contact@personaldata.io  

After the Collaboration: 

✔ All data is aggregated and anonymised. Once the data is analysed with pseudonyms, all personal identifiers are removed to ensure privacy. Only anonymised, aggregated information will be used in scientific publications or shared with partners. 

✔ Findings are non-identifying. Any published results are presented in an aggregated form that prevents the identification of individual participants. 

______________________________________________________________________________________ 

We thank all participants for their time and the experiences they shared, which enriched this research. The results will be made available on the project website for consultation. 

GET INVOLVED

Interested in contributing? You can get involved by:

For PLATFORM WORKERS

Join us to reclaim your data and understand how algorithms impact your work.

Write us at projecthome@unine.ch or projectdelivery@unine.ch
contact

For organisations

You can be our partner!
Your experience and knowledge are essential to better understand the impact of digitalisation and algorithms in the workplace.
contact

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.

funded by