Help us fight injustice in hiring!
Donate your CV to fight together against automated discrimination in job application procedures!
Companies are increasingly using automated systems to help select job applications. These systems rely on algorithms. We know from many examples that the implementation of automated systems can lead to unfair treatment of women, migrants, and other marginalized people. That means there is less chance of them getting a job compared to others. In other words: These algorithms can lead to discrimination on the job market.
We want to change that – by developing tools to detect and avoid injustices in job application processes! To do so, we need real CVs to test how such injustices creep into job selection algorithms. Based on those real CVs, we create artificial CVs and use them to develop methods against discrimination.
What can you do? Help us prevent discrimination in job application processes! It has to stop that people are singled out because of their gender identity, alleged “ethnicity”, or sexual orientation! Donate your (anonymized) CV and answer (optional) questions about sensitive data.
Who is behind this campaign? We are collaborating with a team of research institutions, civil society organizations, and companies under the name "FINDHR - Fairness and Intersectional Non-Discrimination in Human Recommendation": Universitat Pompeu Fabra (Barcelona), Universiteit van Amsterdam, Universitá di Pisa, Radboud Universiteit, Max Planck Institute for Security and Privacy, Erasmus Universiteit Rotterdam, Praksis, Randstad, Adevinta, ETUC, WIDE+, and AlgorithmWatch CH.
The project is funded by the European Union under the Horizon Europe funding program and supported by the Swiss State Secretariat for Education, Research and Innovation. It runs from November 2022 to October 2025.
This article is part of a project that has received funding from the European Union's Horizon Europe research and innovation program under grant agreement No 101070212.
Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union. Neither the European Union nor the granting authority can be held responsible for them.
This work is supported by the Swiss State Secretariat for Education, Research and Innovation (SERI) under contract number 22.00151.