Subject:fairness

Source: https://projects.scss.tcd.ie/subject_area/fairness/ Parent: https://projects.scss.tcd.ie

This project focuses on the rich field of algorithmic fairness where the goal is to ensure that predictions are not biased against subgroups of the population whilst maximising predictive performance. One challenge is when we focus on multiple protected attributes.

Individual fairness concerns the ability of a machine learning model to not being affected in its predictions by one or more sensitive features, such as gender, race, age etc.Recent methods developed techniques for the formal analysis and approximation of fairness in the case of deep Neural Networks (NNs). However such techniques are restricted to simple … Read more

Deep learning, in particular Neural Networks (NNs), has achieved state-of-the-art results in many applications in the last decade. However, the way these models work and operate is still not fully understood, and in many ways they are approached as black-box when deployed in practice.Unfortunately, this raises several concerns about their suitability to deal with sensitive … Read more