Artificial Intelligence (AI)‐based systems are widely employed nowadays to make decisions
that have far‐reaching impact on individuals and society. Their decisions might affect …

Objectives: Discussions of fairness in criminal justice risk assessments typically lack
conceptual precision. Rhetoric too often substitutes for careful analysis. In this article, we …

Investigations of facial analysis (FA) technologies-such as facial detection and facial
recognition-have been central to discussions about Artificial Intelligence's (AI) impact on …

As calls for fair and unbiased algorithmic systems increase, so too does the number of
individuals working on algorithmic fairness in industry. However, these practitioners often do …

Decisions based on algorithmic, machine learning models can be unfair, reproducing biases
in historical data used to train them. While computational techniques are emerging to …

Purpose The purpose of this study is to contribute to the knowledge on the opportunities and
risks in the use of artificial intelligence (AI) in recruitment and selection by exploring the …

Society is increasingly relying on data-driven predictive models for automated decision
making. This is not by design, but due to the nature and noisiness of observational data …

Can satisfactory explanations for complex machine learning models be achieved in high-risk
automated decision-making? How can such explanations be integrated into a data …

Abstract Background Big Data analytics such as credit scoring and predictive analytics offer
numerous opportunities but also raise considerable concerns, among which the most …

Organizations often employ data-driven models to inform decisions that can have a
significant impact on people's lives (eg, university admissions, hiring). In order to protect …