Workshop Schedule

A multidomain approach to institutional AI research and adoption

Vincent Straub, Deborah Morgan, Youmna Hashem, John Francis, Saba Esnaashari and Jonathan Bright

Addressing Automation Bias through Verifiability

Lukas Hondrich and Hannah Ruschemeier

How Differential Robustness Creates Disparate Impact: A European Case Study

Charles Wan, Leid Zejnilović and Susana Lavado

Improving fairness and cybersecurity in the Artificial Intelligence Act

Gabriele Carovano and Alexander Meinke

Pagerank Fairness in Networks

Evaggelia Pitoura

Closing the Loop: Feedback Loops and Biases in Automated Decision-Making

Nicolò Pagan, Joachim Baumann, Ezzat Elokda, Giulia De Pasquale, Saverio Bolognani and Anikó Hannák

Through the sands of time: a reliabilistic account of justified credence in the trustworthiness of AI systems

Andrea Ferrario

A Causal Analysis of Harm

Sander Beckers, Hana Chockler and Joseph Y. Halpern

Affinity Clustering Framework for Data Debiasing using Pairwise Distribution Discrepancy

Siamak Ghodsi and Eirini Ntoutsi

Formally Verified Algorithmic Fairness using Information-Flow Tools

Samuel Teuber and Bernhard Beckert

Model-Agnostic Auditing: A Lost Cause?

Sakina Hansen and Joshua Loftus

A Search Engine for Algorithmic Fairness Datasets

Alessandro Fabris, Fabio Giachelle, Alberto Piva, Gianmaria Silvello and Gian Antonio Susto

An Open-Source Toolkit to Generate Biased Datasets

Joachim Baumann, Alessandro Castelnovo, Riccardo Crupi, Nicole Inverardi and Daniele Regoli

Qualification and quantification of fairness for sustainable mobility policies

Camilla Quaresmini, Eugenia Villa, Valentina Breschi, Viola Schiaffonati and Mara Tanelli

From digital nudging to users' self-determination: explainability as a framework for the effective implementation of the transparency requirements for recommender systems set by the Digital Services Act of the European Union

Matteo Fabbri

Compatibility of Fairness Metrics with EU Non-Discrimination Law: A legal and technical case study

Yasaman Yousefi, Lisa Koutsoviti-Koumeri, Magali Legast, Christoph Schommer, Koen Vanhoof and Axel Legay

The BIAS project: Mitigating diversity biases of AI in the labor market

Carlotta Rigotti, Alexandre Puttick, Eduard Fosch-Villaronga and Mascha Kurpicz-Briki

Is a fairness metric score enough to assess discrimination biases in machine learning?

Jourdan Fanny, Ronan Pons, Nicholas Asher, Jean-Michel Loubes and Laurent Risser

The Case for Correctability in Fair Machine Learning

Mattia Cerrato, Alesia Vallenas Coronel and Marius Köppel

A 'Little Ethics' for Algorithmic Decision-Making

Teresa Scantamburlo and Giovanni Grandi

FairnessLab: A Consequence-Sensitive Bias Audit and Mitigation Toolkit

Corinna Hertweck, Joachim Baumann, Michele Loi and Christoph Heitz

It's about time: counterfactual fairness and temporal depth

Joshua Loftus

Social influence for societal interest: a pro-ethical framework for improving human decision making through multi-stakeholder recommender systems

Matteo Fabbri

Living with Opaque Technologies: Insights for AI from Digital Simulation Models

Eugenia Cacciatori, Enzo Fenoglio and Emre Kazim

AI in Higher Education: Ethical Concerns for Students with Disabilities

Oriane Pierrès, Alireza Darvishy and Markus Christen

Approximate Inference for the Bayesian Fairness Framework

Andreas Nikolaos Athanasopoulos, Amanda Belfrage, David Berg Marklund and Christos Dimitrakakis

Provable Fairness for Neural Network Models using Formal Verification

Giorgian Borca-Tasciuc, Xingzhi Guo, Stanley Bak and Steven Skiena

How optimal transport can help to tackle gender biases in NLP based job recommendation systems?

Fanny Jourdan, Titon Tshiongo, Nicholas Asher, Jean-Michel Loubes and Laurent Risser

What If? Using Multiverse Analysis to Evaluate the Influence of Model Design Decisions on Algorithmic Fairness

Jan Simson, Florian Pfisterer and Christoph Kern

Algorithmic Bias in the Context of European Union Anti-Discrimination Directives

Ahmet Bilal Aytekin

Fair Machine Learning Through Post-processing: The Case of Predictive Parity

Joachim Baumann, Anikó Hannák and Christoph Heitz

Body Measurement Prediction Fairness

Alex Loosley, Amrollah Seifoddini, Alessandro Canopoli and Meike Zehlike

Careful Explanations: A Feminist Perspective on XAI

Laura State and Miriam Fahimi

Fairness in Machine Learning as 'Algorithmic Positive Action'

Jan-Laurin Müller

Using Fairness Metrics as Decision-Making Procedures: Algorithmic Fairness and The Problem of Action-Guidance

Otto Sahlgren

Complex Equality and Algorithmic Fairness: A Social Goods Approach to Make Statistical Fairness Metrics Less Abstract

Bauke Wielinga

Explainability methods to detect and measure discrimination in machine learning models

Sofie Goethals, David Martens and Toon Calders

Track A (room TS O1.19)

How data quality determines AI fairness: The case of automated interviewing

Lou Therese Brandner, Frauke Rostalski, Philipp Mahlow, Anna Wilken, Annika Wölke, Hazar Harmouch and Simon David Hirsbrunner

Towards a framework for the global assessment of sensitive attribute bias within binary classification algorithms

Adrian Byrne, Ivan Caffrey and Quan Le

Track B (room TN O1.46)

Assessing the legality of using the category of race and ethnicity in clinical algorithms - the EU anti-discrimination law perspective

Malwina Anna Wojcik

Ethnic Classifications in Algorithmic Decision-Making Processes

Sofia Jaime and Christoph Kern

Track A (room TS O1.19)

Unification, Extension, and Interpretation of Group Fairness Metrics for ML-Based Decision-Making

Joachim Baumann, Corinna Hertweck, Michele Loi and Christoph Heitz

Augmenting Fairness with Welfare: A Framework for Algorithmic Justice

Sílvia Casacuberta, Isaac Robinson and Connor Wagaman

Track B (room TN O1.46)

The Fallacy of Algorithms in Reading Humans: European Views from Within the Struggles for a Fairer AI

Philip Di Salvo

The Explanation Dialogues: Understanding how legal experts reason about XAI methods

Laura State, Alejandra Bringas Colmenarejo, Andrea Beretta, Salvatore Ruggieri, Franco Turini and Stephanie Law

Track A (room TS O1.19)

When Small Decisions Have Big Impact: Fairness Implications of Algorithmic Profiling Schemes

Christoph Kern, Ruben Bach, Hannah Mautner and Frauke Kreuter

Fairness by Intervention: Towards a theory of substantial fairness for machine learning

Sebastian Zezulka

Track B (room TN O1.46)

Certification Labels for Trustworthy AI

Nicolas Scharowski, Michaela Benk, Swen Kühne, Léane Wettstein and Florian Brühlmann

Arbitrary Decisions are a Hidden Cost of Differentially-Private Training

Bogdan Kulynych, Hsiang Hsu, Carmela Troncoso and Flavio Calmon

Track A (room TS O1.19)

Classification Parity, Causal Equal Protection and Algorithmic Fairness

Marcello Di Bello, Michele Loi and Nicolo Cangiotti

Algorithmic Unfairness through the Lens of EU Non-Discrimination Law. Or Why the Law is not a Decision Tree

Hilde Weerts, Raphaële Xenidis, Henrik Palmer Olsen, Fabien Tarissan and Mykola Pechenizkiy

Track B (room TN O1.46)

Fairness and Diversity in Information Access Systems

Lorenzo Porcaro, Carlos Castillo, Emilia Gomez and João Vinagre

A Reflection on How Cross-Cultural Perspectives on the Ethics of Facial Analysis AI Can Inform EU Policymaking

Chiara Ullstein, Severin Engelmann, Orestis Papakyriakopoulos and Jens Grossklags

Track A (room TS O1.19)

Data Access for Researchers in the context of the Digital Services Act: technical and scientific considerations

João Vinagre, Lorenzo Porcaro, Emilia Gómez

Track B (room TN O1.46)

Lost in translation? How computer science and philosophy reflect local morals and societal peculiarities.

Michele Loi