Algorithmic fairness: why it’s hard and why it’s interesting
CVPR 2022 Tutorial
JUNE 19 PM 1:30-5pm
Room r06-09 and virtually
In only a few years, algorithmic fairness has grown from a niche topic to a major component of computer vision, machine learning and artificial intelligence research and practice. As a field, we have had some embarrassing mistakes, yet our understanding of the core issues, potential impacts, and mitigation approaches has grown. This tutorial presents a range of recent findings, discussions, questions, and partial answers in the space of algorithmic fairness in recent years. While this tutorial will not attempt a comprehensive overview of this rich area, we aim to provide the participants with some tools and insights and to explore the connections between algorithmic fairness and a broad range of ongoing research efforts in the field. We will tackle some of the hard questions that you may have about algorithmic fairness, and hopefully address some misconceptions that have become pervasive.
The tutorial is designed to be accessible to a broad audience of computer vision and artificial intelligence researchers and practitioners.