AEQUITAS 2024
Fairness and Bias in AI

Table of Contents

• Summary: There were 35 papers submitted for peer-review to this workshop. Out of these, 17 papers were accepted for this volume, 17 as regular papers and 0 as short papers.

Papers

• Setting the AI Agenda – Evidence from Sweden in the ChatGPT Era
  Bastiaan Bruinsma , Annika Fredén , Kajsa Hansson , Moa Johansson , Pasko Kisić-Merino , Denitsa Saynova
• ProxiMix: Enhancing Fairness with Proximity Samples in Subgroups
  Jingyu Hu , Jun Hong , Mengnan Du , Weiru Liu
• Combining Fairness and Causal Graphs to Advance Both
  Lea Cohausz , Jakob Kappenberger , Heiner Stuckenschmidt
• Enhancing Algorithm Performance Understanding through tsMorph: Generating Semi-Synthetic Time Series for Robust Forecasting Evaluation
  Moisés Santos , André de Carvalho , Carlos Soares
• Leveraging Ontologies to Document Bias in Data
  Mayra Russo , Maria-Esther Vidal
• Measuring and Mitigating Bias for Tabular Datasets with Multiple Protected Attributes
  Manh Khoi Duong , Stefan Conrad
• Mitigating Toxicity in Dialogue Agents through Adversarial Reinforcement Learning
  Guillermo Villate-Castillo , Borja Sanz , Javier Del Ser
• Enforcing Fairness via Constraint Injection with FaUCI
  Matteo Magnini , Giovanni Ciatto , Roberta Calegari , Andrea Omicini
• Using Protected Attributes to Consider Fairness in Multi-Agent Systems
  Gabriele La Malfa , Jie M. Zhang , Michael Luck , Elizabeth Black
• Does spatio-temporal information benefit the video summarization task?
  Aashutosh Ganesh , Mirela Popa , Daan Odijk , Nava Tintarev
• Long-Term Fairness Strategies in Ranking with Continuous Sensitive Attributes
  Luca Giuliani , Eleonora Misino , Roberta Calegari , Michele Lombardi
• Data Quality Dimensions for Fair AI
  Camilla Quaresmini , Giuseppe Primiero
• Unmasking the Shadows: Leveraging Symbolic Knowledge Extraction to Discover Biases and Unfairness in Opaque Predictive Models
  Federico Sabbatini , Roberta Calegari
• Bias, Subjectivity and Norm in Large Language Models
  Thierry Poibeau
• From Inclusive Language to Inclusive AI: A Proof-of-Concept Study into Pre-Trained Models
  Marion Bartl , Susan Leavy
• FairX: A comprehensive benchmarking tool for model analysis using fairness, utility, and explainability
  Md Fahim Sikder , Resmi Ramachandranpillai , Daniel de Leng , Fredrik Heintz
• AI-fairness and equality of opportunity: a case study on educational achievement
  Angel S. Marrero , Gustavo A. Marrero , Carlos Bethencourt , Liam James , Roberta Calegari