New publication: how transparent is AI in the workplace and in recruitment?
As artificial intelligence continues to transform recruitment and workplace practices, questions around transparency, fairness, and trust are becoming increasingly urgent. A new article sheds light on how workers and job applicants across Europe experience and perceive AI-driven data practices, offering fresh empirical insights into one of the most pressing challenges in today’s datafied workplace.
Conducted as part of the BIAS project, this study by Carlotta Rigotti, Eduard Fosch-Villaronga, Daniel Alves Fernandes, and Antoni Mut Piña draws on a large-scale survey of 4,317 valid responses from a diverse sample across the European Union, Iceland, Norway, Switzerland, and Turkey. It investigates how job applicants and workers perceive AI systems, their awareness of AI use, and their experiences with data processing and transparency mechanisms, with particular attention to demographic patterns related to gender, age, and education.
As AI systems become increasingly embedded in the workplace and the datafication of recruitment and employment grows more pervasive, ensuring the trustworthiness of these technologies, from design to deployment, has emerged as a pressing concern, particularly within the EU’s evolving regulatory landscape. The GDPR and the AI Act play a central role in shaping the governance of AI in recruitment and employment.
Key findings:
- Transparency measures, while sometimes present, remain fragmented and largely procedural. Opt-out mechanisms are frequently unclear.
- AI systems in recruitment contexts collect substantially more data than those used in workplace settings — particularly on sensitive topics.
- In workplace settings, data collection is lower and differences between sensitive and non-sensitive information are less pronounced.
- Belonging to a socially marginalised group is the most consistent demographic predictor of a higher likelihood of data collection.
Building on these findings, the article critically assesses how transparency is — and should be — operationalised under the GDPR and the AI Act. It argues for aligning legal compliance with practices that centre the experiences of those most affected and address structural inequalities in recruitment and employment.
The article "Transparency in the datafied workplace: Law, workers, and job applicant perspectives" is available open access at the webiste of ScienceDirect, Technology in Society.