Table of Contents

• Improving Fairness and Cybersecurity in the Artificial Intelligence ActGabriele Carovano, Alexander Meinke. [doi]
• 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. [doi]
• Living with Opaque Technologies: Insights for AI from Digital SimulationsEugenia Cacciatori, Enzo Fenoglio, Emre Kazim. [doi]
• What If? Using Multiverse Analysis to Evaluate the Influence of Model Design Decisions on Algorithmic FairnessJan Simson, Florian Pfisterer, Christoph Kern. [doi]
• Preface [doi]
• It's About Time: Counterfactual Fairness and Temporal DepthJoshua R. Loftus. [doi]
• Body Measurement Prediction FairnessAlex Loosley, Amrollah Seifoddini, Alessandro Canopoli, Meike Zehlike. [doi]
• Mitigating Diversity Biases of AI in the Labor MarketCarlotta Rigotti, Alexandre R. Puttick, Eduard Fosch Villaronga, Mascha Kurpicz-Briki. [doi]
• Pagerank Fairness in NetworksEvaggelia Pitoura. [doi]
• Classification Parity, Causal Equal Protection and Algorithmic FairnessMarcello Di Bello, Nicolò Cangiotti, Michele Loi. [doi]
• A Search Engine for Algorithmic Fairness DatasetsAlessandro Fabris, Fabio Giachelle, Alberto Piva, Gianmaria Silvello, Gian Antonio Susto. [doi]
• How Differential Robustness Creates Disparate Impact: A European Case StudyCharles Wan, Leid Zejnilovic, Susana Lavado. [doi]
• Social Influence for Societal Interest: A Pro-Ethical Framework for Improving Human Decision-Making Through Multi-Stakeholder Recommender SystemsMatteo Fabbri. [doi]
• A 'Little Ethics' for Algorithmic Decision-MakingTeresa Scantamburlo, Giovanni Grandi. [doi]
• 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 UnionMatteo Fabbri. [doi]
• Using Fairness Metrics as Decision-Making Procedures: Algorithmic Fairness and the Problem of Action-GuidanceOtto Sahlgren. [doi]
• Algorithmic Bias in the Context of European Union Anti-Discrimination DirectivesAhmet Bilal Aytekin. [doi]
• Towards a Framework for the Global Assessment of Sensitive Attribute Bias Within Binary Classification AlgorithmsAdrian Byrne, Ivan Caffrey, Quan Le. [doi]
• Certification Labels for Trustworthy AINicolas Scharowski, Michaela Benk, Swen J. Kühne, Léane Wettstein, Florian Brühlmann. [doi]
• Artificial Intelligence in Higher Education: Ethical Concerns for Students With DisabilitiesOriane Pierrès, Alireza Darvishy, Markus Christen. [doi]
• The Explanation Dialogues: Understanding How Legal Experts Reason About XAI MethodsLaura State, Alejandra Bringas Colmenarejo, Andrea Beretta, Salvatore Ruggieri, Franco Turini, Stephanie Law. [doi]
• Careful Explanations: A Feminist Perspective on XAILaura State, Miriam Fahimi. [doi]
• Fairness and Diversity in Information Access SystemsLorenzo Porcaro, Carlos Castillo 0001, Emilia Gómez, João Vinagre. [doi]
• Fair Machine Learning Through Post-processing: The Case of Predictive ParityJoachim Baumann 0002, Anikó Hannák, Christoph Heitz. [doi]
• An Open-Source Toolkit to Generate Biased DatasetsJoachim Baumann 0002, Alessandro Castelnovo, Riccardo Crupi, Nicole Inverardi, Daniele Regoli. [doi]
• Complex Equality and Algorithmic Fairness: A Social Goods Approach to Make Statistical Fairness Metrics Less AbstractBauke Wielinga. [doi]
• Unification, Extension, and Interpretation of Group Fairness Metrics for ML-Based Decision-MakingJoachim Baumann 0002, Corinna Hertweck, Michele Loi, Christoph Heitz. [doi]
• Arbitrary Decisions Are a Hidden Cost of Differentially Private TrainingBogdan Kulynych, Hsiang Hsu, Carmela Troncoso, Flávio P. Calmon. [doi]
• When Small Decisions Have Big Impact: Fairness Implications of Algorithmic Profiling SchemesChristoph Kern, Ruben L. Bach, Hannah Mautner, Frauke Kreuter. [doi]
• A Causal Analysis of HarmSander Beckers, Hana Chockler, Joseph Y. Halpern. [doi]
• Fairness After Intervention: Towards a Theory of Substantial Fairness for Machine LearningSebastian Zezulka. [doi]
• FairnessLab: A Consequence-Sensitive Bias Audit and Mitigation ToolkitCorinna Hertweck, Joachim Baumann 0002, Michele Loi, Christoph Heitz. [doi]
• Ethnic Classifications in Algorithmic Decision-Making ProcessesSofia Jaime, Christoph Kern. [doi]
• Closing the Loop: Feedback Loops and Biases in Automated Decision-MakingNicolò Pagan, Joachim Baumann 0002, Ezzat Elokda, Giulia De Pasquale, Saverio Bolognani, Anikó Hannák. [doi]
• Provable Fairness for Neural Network Models Using Formal VerificationGiorgian Borca-Tasciuc, Xingzhi Guo, Stanley Bak, Steven Skiena. [doi]
• Formally Verified Algorithmic Fairness Using Information-Flow ToolsSamuel Teuber, Bernhard Beckert. [doi]
• Through the Sands of Time: A Reliabilistic Account of Justified Credence in the Trustworthiness of AI SystemsAndrea Ferrario. [doi]
• Model-Agnostic Auditing: A Lost Cause?Sakina Hansen, Joshua R. Loftus. [doi]
• Approximate Inference for the Bayesian Fairness FrameworkAndreas Nikolaos Athanasopoulos, Amanda Belfrage, David Berg Marklund, Christos Dimitrakakis. [doi]
• How Data Quality Determines AI Fairness: The Case of Automated InterviewingLou Therese Brandner, Philipp Mahlow, Anna Wilken, Annika Wölke, Hazar Harmouch, Simon David Hirsbrunner. [doi]
• Fairness in Machine Learning as 'Algorithmic Positive Action'Jan-Laurin Müller. [doi]
• A Reflection on How Cross-Cultural Perspectives on the Ethics of Facial Analysis AI Can Inform EU PolicymakingChiara Ullstein, Severin Engelmann, Orestis Papakyriakopoulos, Jens Grossklags. [doi]
• Addressing Automation Bias through VerifiabilityLukas Hondrich, Hannah Ruschemeier. [doi]
• Affinity Clustering Framework for Data Debiasing Using Pairwise Distribution DiscrepancySiamak Ghodsi, Eirini Ntoutsi. [doi]
• Is a Fairness Metric Score Enough to Assess Discrimination Biases in Machine Learning?Fanny Jourdan, Ronan Pons, Nicholas Asher, Jean-Michel Loubes, Laurent Risser. [doi]
• Compatibility of Fairness Metrics With EU Non-Discrimination Law: A Legal and Technical Case StudyYasaman Yousefi, Lisa Koutsoviti Koumeri, Magali Legast, Christoph Schommer, Koen Vanhoof, Axel Legay. [doi]
• Algorithmic Unfairness Through the Lens of EU Non-Discrimination LawHilde J. P. Weerts, Raphaële Xenidis, Fabien Tarissan, Henrik Palmer Olsen, Mykola Pechenizkiy. [doi]
• Assessing the Legality of Using the Category of Race and Ethnicity in Clinical Algorithms - the EU Anti-Discrimination Law PerspectiveMalwina Anna Wojcik. [doi]
• The Case for Correctability in Fair Machine LearningMattia Cerrato, Alesia Vallenas Coronel, Marius Köppel. [doi]
• A Multidomain Relational Framework to Guide Institutional AI Research and AdoptionVincent J. Straub, Deborah Morgan, Youmna Hashem, John Francis, Saba Esnaashari, Jonathan Bright. [doi]
• Qualification and Quantification of Fairness for Sustainable Mobility PoliciesCamilla Quaresmini, Eugenia Villa, Valentina Breschi, Viola Schiaffonati, Mara Tanelli. [doi]
• Explainability Methods to Detect and Measure Discrimination in Machine Learning ModelsSofie Goethals, David Martens, Toon Calders. [doi]