Bias and Discrimination in AI l UMontrealX on edX.org

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, increasing observations and emerging research suggest that they can also lead to unequal and unfair treatments and outcomes for certain groups or individuals.

This Bias and Discrimination in AI MOOC involves the participation of multi-disciplinary international teams of academic researchers and practitioners from the civil society 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 as well as data-driven predictive models leading to decisions.

This MOOC is derived from the International School on Bias and Discrimination in AI, which took place in 2019 in Montreal, Canada, organized by IVADO and members of Mila. The school, as well as this MOOC, are primarily destined for industry professionals, subject matter experts and academics with basic knowledge in mathematics and programming (such as engineers, computer scientists, statisticians, technical project managers, product managers, systems engineers, etc.). However, the rich content will also be of great use to whomever uses, or is interested in, artificial intelligence in any other way. These social-technical subjects have proven to be great eye-openers to technical professionals.