Workshop Schedule
Day 1
June 8, 2022
All times are in Zurich time (UTC + 2)
12:30–13:00
Arrival
13:00–13:30
Opening remarks
13:30–14:15
Invited speaker: Krishna Gummadi
Foundations for Fair Social Computing
14:15–15:15
Lightning round 1
A Representative Swiss Population Survey on Algorithmic Fairness Reveals Positive Attitudes towards AI but Bias in Gender Discrimination Perception (Markus Christen)
Fairness-Aware Dimensionality Reduction (Amaya Nogales-Gómez, Luc Pronzato and Maria-João Rendas)
Fairness metrics for visual privacy preservation (Sophie Noiret, Siddharth Ravi, Martin Kampel and Francisco Florez-Revuelta)
A Process Model for fair AI development (Sarah Cepeda, Fabian Eberle, Lena Müller-Kress, Rania Wazir, Magdalene Kunze, Jakob Hirtenlehner, Andreas Rauber, Christiane Wendehorst and Gertraud Leimüller)
Policy Fairness in Sequential Allocations under Bias Dynamics (Meirav Segal, Anne-Marie George and Christos Dimitrakakis)
Exploitation and Algorithmic Pricing (Arianna Dini)
Understanding and Explainable AI (Will Fleisher)
15:15–15:45
Break
15:45–17:15
Lightning round 2
Algorithmic Fairness and Secure Information Flow (Bernhard Beckert, Michael Kirsten and Michael Schefczyk)
Autonomous Vehicles, Business Ethics, and Risk Distribution in Hybrid Traffic (Brian Berkey)
Algorithmic fairness as a path: start measuring your current process fairness (Jesus Salgado Criado)
Can Algorithms be Decent?: Developing Value Frameworks for Artificial Intelligence (Darby Vickers)
Corporate influence in public education through data extractive systems for student profiling (Velislava Hillman)
Towards a faithfull assessment of fairness (In alphabetical order: Bilel Benbouzid, Ruta Binkyte-Sadauskiene, Karima Makhlouf, Catuscia Palamidessi, Carlos Pinzon and Sami Zhioua)
Demographic Parity's Not Dead (Nicolas Schreuder and Evgenii Chzhen)
Counterfactual reasoning for meaningful situation testing (Jose M. Alvarez and Salvatore Ruggieri)
What's Ideal about Fair Machine Learning? (Otto Sahlgren)
The Fairness in Algorithmic Fairness (Sune Holm)
Automatic Fairness Testing of Machine Learning Models (Arnab Sharma and Heike Wehrheim)
Unfair World. Fair Decisions. Knowledge transport data pre-processing method for fair AI (Ruta Binkyte-Sadauskiene and Catuscia Palamidessi)
Algorithmic Fairness in Biomedical Research and Practice: A Use-Case Study on Alzheimer's Dementia Prediction (Derya Şahin, Frank Jessen and Joseph Kambeitz)
17:15–17:45
Break
17:45–18:30
Invited speaker: Hoda Heidari
Local Justice and ML: Modeling and Inferring Dynamic Ethical Preferences toward the Allocation of Scarce Resources
20:00–23:00
Joint dinner
Day 2
June 9, 2022
All times are in Zurich time (UTC + 2)
9:00–9:45
Invited speaker: Kasper Lippert-Rasmussen
Moral Objections to Discrimination and Unfairness-Based Objections to Algorithms: How Are They (Not) Related?
9:45–10:30
In-depth 1
Track A: Predictions Are Not Decisions. Why Algorithmic Fairness Is Not Enough for Real-World Decision-Making (Maël Pégny and Julien Gossa)
Track B: Algorithmic Audit of Italian Car Insurance: Evidence of Unfairness in Access and Pricing (Alessandro Fabris, Alan Mishler, Stefano Gottardi, Mattia Carletti, Matteo Daicampi, Gian Antonio Susto and Gianmaria Silvello)
10:30–11:00
Break
11:00–11:45
In-depth 2
Track A: Arbitrariness in Automated Decision-Making as a Moral Problem: A reply to Creel and Hellman (Conny Knieling)
Track B: Perceptions of Efficiency vs. Fairness Tradeoffs in Algorithm-based HR Selection: Insights from Two Online Experiments (Serhiy Kandul and Ulrich Leicht-Deobald)
11:45–12:30
In-depth 3
Track A: Definitions of Fairness are Biased: Inclusive Definitions of Fairness (Eva Yiwei Wu and Karl Reimer)
Track B: Data-Centric Factors in Algorithmic Fairness (Nianyun Li, Naman Goel and Elliott Ash)
12:30–13:00
Closing remarks