|  | Vol-4147 urn:nbn:de:0074-4147-x Copyright © 2026 for the individual papers by the papers' authors. Copyright © 2025 for the volume as a collection by its editors. This volume and its papers are published under the Creative Commons License Attribution 4.0 International (CC BY 4.0).

# AEQUITAS 2025
Fairness and Bias in AI

## Proceedings of the 3rd Workshop on Fairness and Bias in AI
co-located with 28th European Conference on Artificial Intelligence (ECAI 2025)

### Bologna, Italy, October 26th, 2025.

Edited by

### Roberta Calegari *
Payal Arora **
Virginia Dignum ***

* University of Bologna, Department of Computer Science and Engineering, Bologna, Italy
** Utrecht University, Utrecht, Netherlands
*** Umeå University, Umeå, Sweden

## Table of Contents

- Summary: There were 27 papers submitted for peer-review to this workshop. Out of these, 14 papers were accepted for this volume, 14 as regular papers and 0 as short papers.

### Papers

- Modeling Fairness in Recruitment AI via Information Flow
  Mattias Brännström, Themis Dimitra Xanthopoulou, Lili Jiang
- VB-Mitigator: An Open-source Framework for Evaluating and Advancing Visual Bias Mitigation
  Ioannis Sarridis, Christos Koutlis, Symeon Papadopoulos, Christos Diou
- Transparency and Proportionality in Post-Processing Algorithmic Bias Correction
  Juliett Suárez-Ferreira, Marija Slavkovik, Jorge Casillas
- Causal Synthetic Data Generation in Recruitment
  Andrea Iommi, Antonio Mastropietro, Riccardo Guidotti, Anna Monreale, Salvatore Ruggieri
- A Fairness-Oriented Visual Extension for the PSyKE Platform
  Federico Sabbatini
- Is Reasoning All You Need? Probing Bias in the Age of Reasoning Language Models
  Riccardo Cantini, Nicola Gabriele, Alessio Orsino, Domenico Talia
- First Ask Then Act (FATA): A Community-Centered Inclusive Approach for Hate Speech Detection
  Chiara Ferrando, Lia Draetta, Andrea Marra, Angela Zottola, Cristina Bosco, Viviana Patti
- How do doctors perceive AI in their medical practice?
  Laura Sartori, Chiara Binelli, Francesca Lizzi, Andrea Chincarini, Francesco Sensi, Alessandra Retico
- On the Correlation between Individual Fairness and Predictive Accuracy in Probabilistic Models
  Alessandro Antonucci, Eric Rossetto, Ivan Duvnjak
- Towards a Partial Coverage of Neural Network Explanations Using Approximation Networks
  Mathieu Brassart, Laurent Simon
- Visual Model Selection using Feature Importance Clusters in Fairness-Performance Similarity Optimized Space
  Sofoklis Kitharidis, Cor J. Veenman, Thomas Bäck, Niki van Stein
- Evaluating and Mitigating Fairness Risks in Machine Learning under Structured Missing Data
  Tim Kochs, Andrea Castellani, Felix Lanfermann, Barbara Hammer
- Mechanistic Interpretability with SAEs: Probing Religion, Violence, and Geography in Large Language Models
  Katharina Simbeck, Mariam Mahran
- Bias Detection in Cultural Heritage Metadata: Preliminary Results from the IMAGES Project
  Angelo Oddi, Gianmauro Romagna, Riccardo Rasconi, Paola Panarese, Paolo De Gasperis

2025-12-22: submitted by Roberta Calegari, metadata incl. bibliographic data published under Creative Commons CC0
2026-01-07: published on CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073) |valid HTML5|