Companies increasingly deploy artificial intelligence (AI) technologies in their personnel
recruiting and selection process to streamline it, making it faster and more efficient. AI …

This study aims to address the research gap on algorithmic discrimination caused by AI-
enabled recruitment and explore technical and managerial solutions. The primary research …

Artificial Intelligence techniques powered by deep neural nets have achieved much success
in several application domains, most significantly and notably in the Computer Vision …

Face recognition (FR) systems have a growing effect on critical decision-making processes.
Recent works have shown that FR solutions show strong performance differences based on …

Despite being responsible for state-of-the-art results in several computer vision and natural
language processing tasks, neural networks have faced harsh criticism due to some of their …

In today's competitive and fast-evolving business environment, it is a critical time for
organizations to rethink how to make talent-related decisions in a quantitative manner …

Over the past two decades, biometric recognition has exploded into a plethora of different
applications around the globe. This proliferation can be attributed to the high levels of …

Prioritizing fairness is of central importance in artificial intelligence (AI) systems, especially
for those societal applications, eg, hiring systems should recommend applicants equally …

Deep Learning and its applications have cascaded impactful research and development
with a diverse range of modalities present in the real-world data. More recently, this has …

The use of artificial intelligence (AI) technologies in organizations' recruiting and selection
procedures has become commonplace in business practice; accordingly, research on AI …