AEQUITAS 2023
Fairness and Bias in AI

Table of Contents

• Preface
  Summary: There were 13 papers submitted for peer-review to this workshop. Out of these, 12 papers were accepted for this volume, 12 as regular papers and 0 as short papers.

Papers

• Causal Fair Machine Learning via Rank-Preserving Interventional Distributions
  Ludwig Bothmann , Susanne Dandl , Michael Schomaker
• Visualizing Bias in Activations of Deep Neural Networks as Topographic Maps
  Valerie Krug , Christopher Olson , Sebastian Stober
• Recommendations for Bias Mitigation Methods: Applicability and Legality
  Madeleine Waller , Odinaldo Rodrigues , Oana Cocarascu
• Reasoning With Bias
  Chiara Manganini , Giuseppe Primiero
• FAiRDAS: Fairness-Aware Ranking as Dynamic Abstract System
  Eleonora Misino , Roberta Calegari , Michele Lombardi , Michela Milano
• EXTRACT: Explainable Transparent Control of Bias in Embeddings
  Zhijin Guo , Zhaozhen Xu , Martha Lewis , Nello Cristianini
• Fairness in job recommendations: estimating, explaining, and reducing gender gaps
  Guillaume Bied , Christophe Gaillac , Morgane Hoffmann , Philippe Caillou , Bruno Crépon , Solal Nathan , Michèle Sebag ,
• Gender Bias in Multimodal Models: A Transnational Feminist Approach Considering Geographical Region and Culture
  Abhishek Mandal , Suzanne Little , Susan Leavy
• A geometric framework for fairness
  Alessandro Maggio , Luca Giuliani , Roberta Calegari , Michele Lombardi , Michela Milano
• Symbolic AI (LFIT) for XAI to handle biases
  Javier Tello , Marina de la Cruz , Tony Ribeiro , Julian Fierrez , Aythami Morales , Ruben Tolosana , César Luis Alonso , Alfonso Ortega
• Bias Mitigation for Large Language Models using Adversarial Learning
  Jasmina S. Ernst , Sascha Marton , Jannik Brinkmann , Eduardo Vellasques , Damien Foucard , Martin Kraemer , Marian Lambert
• Impact based fairness framework for socio-technical decision making
  Mattias Brännström , Lili Jiang , Andrea Aler Tubella , Virginia Dignum