Date: June 3-6, 2019
Location: Mila Auditorium, 6650 Saint-Urbain, Montréal, QC, H2S 3G9
Government and industry employees: $1500
Non-profit organizations (NPO): $400
It is with great pleasure that we invite you to participate in the first edition of our IVADO-Mila Summer School on Bias and Discrimination in Artificial Intelligence!
Algorithms, and the data they process, play an increasingly important role in decisions with significant consequences for human welfare. While algorithmic decision-making processes have the potential to lead to fairer and more objective decisions, emerging research suggests that they can also lead to unequal and unfair treatments and outcomes for certain groups or individuals.
This Summer School is an attempt to engage multi-disciplinary teams of researchers and practitioners to explore the social and technical dimensions of bias, discrimination and fairness in machine learning and algorithm design. The course focuses specifically (although not exclusively) on gender, race and socioeconomic based bias and data-driven predictive models leading to decisions.
Emre Kiciman is a Principal Researcher at Microsoft Research AI in the information and data sciences group.
Margaret Mitchell is a Senior Research Scientist in Google's Research & Machine Intelligence group, where she leads the Ethical Artificial Intelligence team.
Pedro Saleiro is a researcher at the University of Chicago working. He is a member of the Aequitas project, an open source bias audit toolkit to audit machine learning models for discrimination and bias
Golnoosh Farnadi is an IVADO post-doctoral fellow working on fairness-aware sequential decision making under uncertainty.