The workshop takes place online on September 13th, 8:55 - 14:45. Registered participants will be provided with an access link.
8:55 - 9:00 Welcome Opening by the workshop chairs
09:00 - 09:50 Keynote What's fair about fair ML? (slides)
Linnet Taylor
09:50 -10:10 Contributed paper Algorithmic Factors Influencing Bias in Machine Learning
William Blanzeisky and Padraig Cunningham
10:10 - 10:30 Contributed paper Desiderata for Explainable AI in statistical production systems of the European Central Bank,
Carlos Mougan, Georgios Kanellos and Thomas Gottron
10:30-10:50 Coffee break
10:50-11:40 Keynote The Fairness-Accuracy tradeoff revisited (slides)
Toon Calders
11:40 - 12:00 Contributed paper Robustness of Fairness: An Experimental Analysis,
Serafina Kamp, Andong Luis Li Zhao and Sindhu Kutty
12:00 - 12:20 Contributed paper Co-clustering for fair recommendation,
Gabriel Frisch, Jean-Benoist Leger and Yves Grandvalet
12:20 - 13:00 Lunch break
13:00 - 13:50 Keynote Strengths and weaknesses of European legal protection against discriminatory AI (slides)
Frederik Zuiderveen Borgesius
13:50 -14:10 Contributed paper Learning a Fair Distance Function for Situation Testing
Daphne Lenders and Toon Calder
14:10-14:30 Contributed paper Towards Fairness Through Time
Alessandro Castelnovo, Lorenzo Malandri, Fabio Mercorio,
Mario Mezzanzanica and Andrea Cosentini
14:30 - 14:45 Closing discussion