activity
20232026
most citedFairness and Bias in Algorithmic Hiring: a Multidisciplinary Survey

91 citations · 91 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CY2026

Click, Branch, Audit: A Decision-Tree Toolkit for Assessing Fundamental Rights Impacts under the Digital Services Act of Very Large Platforms & Search Engines

Marie-Therese Sekwenz, Till Winkler, Maria-Lucia Rebrean +4

The EU Digital Services Act (DSA) requires Very Large Online Platforms and Search Engines (VLOPs/VLOSEs) to assess and mitigate systemic risks, including actual or foreseeable nega…

cs.AI2026

Vertical Standardisation for High-Risk AI Systems under the EU AI Act: A Domain-Specific Framework for Algorithmic Hiring

Anna Gatzioura, Vrettos Moulos, Nina Baranowska

According to the recent European legislation, high-risk AI systems will have to adapt in order to comply with requirements related to specific areas, like risk management, data qua…

cs.CL2026

WorkRB: A Community-Driven Evaluation Framework for AI in the Work Domain

Matthias De Lange, Warre Veys, Federico Retyk +16

Today's evolving labor markets rely increasingly on recommender systems for hiring, talent management, and workforce analytics, with natural language processing (NLP) capabilities…

cs.CY2026

Co-designing for Compliance: Multi-party Computation Protocols for Post-Market Fairness Monitoring in Algorithmic Hiring

Changyang He, Nina Baranowska, Josu Andoni Eguiluz Castaneira +5

Post-market fairness monitoring is now mandated to ensure fairness and accountability for high-risk employment AI systems under emerging regulations such as the EU AI Act. However,…

cs.CY2024

Non-discrimination law in Europe: a primer for non-lawyers

Frederik Zuiderveen Borgesius, Nina Baranowska, Philipp Hacker +1

This brief paper provides an introduction to non-discrimination law in Europe. It answers the questions: What are the key characteristics of non-discrimination law in Europe, and h…

cs.CY2023★ 91 cited

Fairness and Bias in Algorithmic Hiring: a Multidisciplinary Survey

Alessandro Fabris, Nina Baranowska, Matthew J. Dennis +5

Employers are adopting algorithmic hiring technology throughout the recruitment pipeline. Algorithmic fairness is especially applicable in this domain due to its high stakes and st…