| Vol-3442 urn:nbn:de:0074-3442-0 Copyright © 2023 for the individual papers by the papers' authors. Copyright © 2023 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).

# EWAF 2023
European Workshop on Algorithmic Fairness

### Proceedings of the 2nd European Workshop on Algorithmic Fairness

### Winterthur, Switzerland, June 7th to 9th, 2023.

Edited by

### Jose M. Alvarez, Scuola Normale Superiore, Pisa, Italy
Alessandro Fabris, Max Planck Institute for Security and Privacy, Bochum, Germany
Christoph Heitz, Zurich University of Applied Sciences, Switzerland
Corinna Hertweck, Zurich University of Applied Sciences and University of Zurich, Switzerland
Michele Loi, Polytechnic University of Milan, Italy
Meike Zehlike, Zalando, Berlin, Germany

## Table of Contents

- Preface
  Jose M. Alvarez, Alessandro Fabris, Christoph Heitz, Corinna Hertweck, Michele Loi, Meike Zehlike

### Computer Science Track

- Approximate Inference for the Bayesian Fairness Framework
  Andreas Nikolaos Athanasopoulos, Amanda Belfrage, David Berg Marklund, Christos Dimitrakakis
- An Open-Source Toolkit to Generate Biased Datasets
  Joachim Baumann, Alessandro Castelnovo, Riccardo Crupi, Nicole Inverardi, Daniele Regoli
- Fair Machine Learning Through Post-processing: The Case of Predictive Parity
  Joachim Baumann, Anikó Hannák, Christoph Heitz
- Provable Fairness for Neural Network Models Using Formal Verification
  Giorgian Borca-Tasciuc, Xingzhi Guo, Stanley Bak, Steven Skiena
- Towards a Framework for the Global Assessment of Sensitive Attribute Bias Within Binary Classification Algorithms
  Adrian Byrne, Ivan Caffrey, Quan Le
- The Case for Correctability in Fair Machine Learning
  Mattia Cerrato, Alesia Vallenas Coronel, Marius Köppel
- A Search Engine for Algorithmic Fairness Datasets
  Alessandro Fabris, Fabio Giachelle, Alberto Piva, Gianmaria Silvello, Gian Antonio Susto
- Affinity Clustering Framework for Data Debiasing Using Pairwise Distribution Discrepancy
  Siamak Ghodsi, Eirini Ntoutsi
- Explainability Methods to Detect and Measure Discrimination in Machine Learning Models
  Sofie Goethals, David Martens, Toon Calders
- Model-Agnostic Auditing: A Lost Cause?
  Sakina Hansen, Joshua Loftus
- FairnessLab: A Consequence-Sensitive Bias Audit and Mitigation Toolkit
  Corinna Hertweck, Joachim Baumann, Michele Loi, Christoph Heitz
- Is a Fairness Metric Score Enough to Assess Discrimination Biases in Machine Learning?
  Fanny Jourdan, Ronan Pons, Nicholas Asher, Jean-Michel Loubes, Laurent Risser
- Breaking Bias: How Optimal Transport Can Help to Tackle Gender Biases in NLP Based Job Recommendation Systems?
  Fanny Jourdan, Titon Tshiongo-Kaninku, Nicholas Asher, Jean-Michel Loubes, Laurent Risser
- Arbitrary Decisions Are a Hidden Cost of Differentially Private Training
  Bogdan Kulynych, Hsiang Hsu, Carmela Troncoso, Flavio Calmon
- It's About Time: Counterfactual Fairness and Temporal Depth
  Joshua Loftus
- Body Measurement Prediction Fairness
  Alex Loosley, Amrollah Seifoddini, Alessandro Canopoli, Meike Zehlike
- Closing the Loop: Feedback Loops and Biases in Automated Decision-Making
  Nicolò Pagan, Joachim Baumann, Ezzat Elokda, Giulia De Pasquale, Saverio Bolognani, Anikó Hannák
- Pagerank Fairness in Networks
  Evaggelia Pitoura
- Fairness and Diversity in Information Access Systems
  Lorenzo Porcaro, Carlos Castillo, Emilia Gómez, João Vinagre
- Formally Verified Algorithmic Fairness Using Information-Flow Tools
  Samuel Teuber, Bernhard Beckert
- How Differential Robustness Creates Disparate Impact: A European Case Study
  Charles Wan, Leid Zejnilović, Susana Lavado

### Philosophy Track

- Unification, Extension, and Interpretation of Group Fairness Metrics for ML-Based Decision-Making
  Joachim Baumann, Corinna Hertweck, Michele Loi, Christoph Heitz
- A Causal Analysis of Harm
  Sander Beckers, Hana Chockler, Joseph Y. Halpern
- How Data Quality Determines AI Fairness: The Case of Automated Interviewing
  Lou Therese Brandner, Philipp Mahlow, Anna Wilken, Annika Wölke, Hazar Harmouch, Simon David Hirsbrunner
- Classification Parity, Causal Equal Protection and Algorithmic Fairness
  Marcello Di Bello, Nicolo Cangiotti, Michele Loi
- Social Influence for Societal Interest: A Pro-Ethical Framework for Improving Human Decision-Making Through Multi-Stakeholder Recommender Systems
  Matteo Fabbri
- Through the Sands of Time: A Reliabilistic Account of Justified Credence in the Trustworthiness of AI Systems
  Andrea Ferrario
- Qualification and Quantification of Fairness for Sustainable Mobility Policies
  Camilla Quaresmini, Eugenia Villa, Valentina Breschi, Viola Schiaffonati, Mara Tanelli
- Using Fairness Metrics as Decision-Making Procedures: Algorithmic Fairness and the Problem of Action-Guidance
  Otto Sahlgren
- A 'Little Ethics' for Algorithmic Decision-Making
  Teresa Scantamburlo, Giovanni Grandi
- A Multidomain Relational Framework to Guide Institutional AI Research and Adoption
  Vincent Straub, Deborah Morgan, Youmna Hashem, John Francis, Saba Esnaashari, Jonathan Bright
- Complex Equality and Algorithmic Fairness: A Social Goods Approach to Make Statistical Fairness Metrics Less Abstract
  Bauke Wielinga
- Fairness After Intervention: Towards a Theory of Substantial Fairness for Machine Learning
  Sebastian Zezulka

### Social Sciences Track

- Ethnic Classifications in Algorithmic Decision-Making Processes
  Sofia Jaime, Christoph Kern
- When Small Decisions Have Big Impact: Fairness Implications of Algorithmic Profiling Schemes
  Christoph Kern, Ruben Bach, Hannah Mautner, Frauke Kreuter
- Artificial Intelligence in Higher Education: Ethical Concerns for Students With Disabilities
  Oriane Pierrès, Alireza Darvishy, Markus Christen
- What If? Using Multiverse Analysis to Evaluate the Influence of Model Design Decisions on Algorithmic Fairness
  Jan Simson, Florian Pfisterer, Christoph Kern
- Careful Explanations: A Feminist Perspective on XAI
  Laura State, Miriam Fahimi
- A Reflection on How Cross-Cultural Perspectives on the Ethics of Facial Analysis AI Can Inform EU Policymaking
  Chiara Ullstein, Severin Engelmann, Orestis Papakyriakopoulos, Jens Grossklags

### Law & Policy Track

- Algorithmic Bias in the Context of European Union Anti-Discrimination Directives
  Ahmet Bilal Aytekin
- Living with Opaque Technologies: Insights for AI from Digital Simulations
  Eugenia Cacciatori, Enzo Fenoglio, Emre Kazim
- Improving Fairness and Cybersecurity in the Artificial Intelligence Act
  Gabriele Carovano, Alexander Meinke
- 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
- Addressing Automation Bias through Verifiability
  Lukas Hondrich, Hannah Ruschemeier
- Fairness in Machine Learning as 'Algorithmic Positive Action'
  Jan-Laurin Müller
- Mitigating Diversity Biases of AI in the Labor Market
  Carlotta Rigotti, Alexandre Puttick, Eduard Fosch-Villaronga, Mascha Kurpicz-Briki
- Certification Labels for Trustworthy AI
  Nicolas Scharowski, Michaela Benk, Swen Kühne, Léane Wettstein, Florian Brühlmann
- The Explanation Dialogues: Understanding How Legal Experts Reason About XAI Methods
  Laura State, Alejandra Bringas Colmenarejo, Andrea Beretta, Salvatore Ruggieri, Franco Turini, Stephanie Law
- Algorithmic Unfairness Through the Lens of EU Non-Discrimination Law
  Hilde Weerts, Raphaële Xenidis, Fabien Tarissan, Henrik Palmer Olsen, Mykola Pechenizkiy
- Assessing the Legality of Using the Category of Race and Ethnicity in Clinical Algorithms - the EU Anti-Discrimination Law Perspective
  Malwina Anna Wojcik
- 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, Axel Legay

2023-07-05: submitted by Alessandro Fabris, metadata incl. bibliographic data published under Creative Commons CC0
2023-07-16: published on CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073) |valid HTML5|