First Bilbao Workshop on Algorithmic Fairness (FBWAF 2021)
Online, 21-23 June, 2021
Machine Learning and Artificial Intelligence have advanced rapidly in recent decades, and their use is becoming increasingly widespread, with applications ranging from disease detection or object recognition to the automated evaluation of résumés. Along with this increase, there has also been growing concern about the ethical issues that may arise from the adoption of these technologies as well as the impact on humans and society of decisions made based on automatic or semi-automatic systems. It has led to a great push for the emergence of multidisciplinary approaches for assessing and removing the presence of bias in machine learning-based decision support systems. From 21st to 23rd June 2021, BCAM will host an online workshop on the topic of algorithmic fairness. This event aims to give an overview of the problem, from its origin to the current state-of-the-art, discussing future research opportunities. During these three days, invited speakers will present some of the latest methodological developments in this area as well as different applications in several domains.
Short Course"Mathematical models for fairness in machine learning" by Jean-Michel Loubes and Laurent Risser (Université Toulouse Paul Sabatier & Artificial and Natural Intelligence Toulouse Institute (ANITI), France) on Monday June 21, 2021.
Invited Speakers (confirmed)
- Silvia Chiappa (DeepMind, United Kingdom)
- Nello Cristianini (University of Bristol, United Kingdom)
- Mohamed Hebiri (Université Gustave Eiffel, France)
- Jean-Michel Loubes (Université Toulouse Paul Sabatier & Artificial and Natural Intelligence Toulouse Institute (ANITI), France)
- Helena Matute (Universidad de Deusto, Bilbao, Spain)
- Maryam Negahbani (Dartmouth College, United States)
- Novi Quadrianto (University of Sussex, United Kingdom)
- Laurent Risser (Université Toulouse Paul Sabatier & Artificial and Natural Intelligence Toulouse Institute (ANITI), France)