AIMMES 2025
AI bias: Measurements, Mitigation, Explanation Strategies

Table of Contents

• Summary: There were 27 papers submitted for peer-review to this workshop. Out of these, 8 papers were accepted for this volume, 8 as regular papers and 0 as short papers.

Papers

• A Survey on Human Resource Management Under the AI Act: Ethical, Practical, and Regulatory Perspectives
  Nicola Alboré, Alessandro Castelnovo, Matteo Della Valle, Andrea Ermellino;, Luca Puggini, Silvia Tessaro
• Assessing Discrimination Risk from Generated Content in the Wild
  Iris S. Bore, Robindra Prabhu, Jacob Sjødin
• Measuring Bias in German Prompts to GPT Models Using Contact Hypothesis
  Catherine Ikae, Mascha Kurpicz-Briki
• The COMPAS Case: An Educational Journey for Explaining Fairness in AI-based Applications
  Antonio Rodà
• Fairness and Accountability in AI-Driven Corporate Social Responsibility: Insights from Small and Medium-Sized Enterprises
  Dorleta Urrutia-Onate, Julen Bollain, Enrique Onieva, Asier Perallos
• Algorithmic Imaginary of AI for Recruitment: Perceptions and Experiences of AI Use from HR Practitioners
  Silvia Ecclesia
• Shifting Paradigms: Value Sensitive Design for Fair AI Recruitment
  Alexandre Puttick, Carlotta Rigotti, Ahmed Abouzeid, Eduard Fosch-Villaronga, Mascha Kurpicz-Briki, Pinar Øztürk
• Addressing Bias and Data Scarcity in AI-Based Skin Disease Diagnosis with Non-Dermoscopic Images
  Chiara Bellatreccia, Daniele Zama, Arianna Dondi, Luca Pierantoni, Andreozzi Laura, Iria Neri, Marcello Lanari, Andrea Borghesi, Roberta Calegari