There has been a recent resurgence of interest in explainable artificial intelligence (XAI) that
aims to reduce the opaqueness of AI-based decision-making systems, allowing humans to …

The increasing use of data-driven decision support systems in industry and governments is
accompanied by the discovery of a plethora of bias and unfairness issues in the outputs of …

Abstract Machine learning (ML) techniques have become pervasive across a range of
different applications, and are now widely used in areas as disparate as recidivism …

The need for responsible data management intensifies with the growing impact of data on
society. One central locus of the societal impact of data are Automated Decision Systems …

Quantifying systematic disparities in numerical quantities such as employment rates and
wages between population subgroups provides compelling evidence for the existence of …

Fairness is increasingly recognized as a critical component of machine learning systems.
However, it is the underlying data on which these systems are trained that often reflect …

Causal inference is fundamental to empirical scientific discoveries in natural and social
sciences; however, in the process of conducting causal inference, data management …

Algorithmic decision-making systems are successfully being adopted in a wide range of
domains for diverse tasks. While the potential benefits of algorithmic decision-making are …

The e-commerce platforms, such as Shopee, have accumulated a huge volume of time-
series relational data, which contains useful information on differentiating fraud users from …

In light of the growing popularity of Exploratory Data Analysis (EDA), understanding the
underlying causes of the knowledge acquired by EDA is crucial. However, it remains under …