Employers are adopting algorithmic hiring technology throughout the recruitment pipeline.
Algorithmic fairness is especially applicable in this domain due to its high stakes and …

Disparities by race, gender, and other protected characteristics have been widely
documented in many important settings—such as employment, housing, criminal justice …

Abstract Machine learning algorithms are increasingly able to predict what goods and
services particular people will buy, and at what price. It is possible to imagine a situation in …

We run an online experiment to study the origins of algorithm aversion. Participants are in
the role of either workers or managers. Workers perform three real-effort tasks: task 1, task 2 …

Introduction Gender biases in hiring decisions remain an issue in the workplace. Also,
current gender balancing techniques are scientifically poorly supported and lead to …

This study aims to identify the level of attitudes of faculty members in Palestinian universities
regarding the opportunities and challenges of employing artificial intelligence applications in …

Throughout the world, women's labour force participation is lower than men's. But the gap
between men's and women's labour force participation varies strikingly across regions …

The promise of generative AI to increase human productivity relies on developing skills to
become proficient at it. There is reason to suspect that women and men use AI tools …

Purpose This study aims to investigate some individual factors that may positively/negatively
impact upon the willingness to use AI-assisted hiring procedures (AI-WtU). Specifically, the …

Abstract The use of Artificial Intelligence (AI) in hiring is becoming increasingly popular, but
little is known about the direct impact of its use on applicant decisions. In a series of novel …