Despite increasing numbers of regulatory approvals, deep learning-based computational
pathology systems often overlook the impact of demographic factors on performance …

Artificial intelligence (AI) systems have increasingly achieved expert-level performance in
medical imaging applications. However, there is growing concern that such AI systems may …

While recent years have witnessed a rapid growth of research papers on recommender
system (RS), most of the papers focus on inventing machine learning models to better fit …

We provide a review of progress in the field of organizational justice, paying special
attention to articles published in Personnel Psychology. We begin by describing the …

Fairness approaches in machine learning should involve more than an assessment of
performance metrics across groups. Shifting the focus away from model metrics, we reframe …

A minimax framework for quantifying risk-fairness trade-off in regression Page 1 The Annals
of Statistics 2022, Vol. 50, No. 4, 2416–2442 https://doi.org/10.1214/22-AOS2198 © Institute …

Classification with abstention has gained a lot of attention in recent years as it allows to
incorporate human decision-makers in the process. Yet, abstention can potentially amplify …

Most works on the fairness of machine learning systems focus on the blind optimization of
common fairness metrics, such as Demographic Parity and Equalized Odds. In this paper …

Quantum information technologies, covering quantum computing, quantum communication
and quantum sensing, are among the most significant technologies to emerge in recent …

Artificial intelligence (AI) systems are being increasingly adopted by society, governments,
and organizations in various decision-making contexts. For example, organizations use AI …