About 90% of employers use AI to some extent in hiring, yet research on how this is impacting job seekers is virtually nonexistent. In one of the first studies to analyze AI hiring tools, Stanford researchers have discovered that for many job applications, the algorithms were making racially biased decisions.

Humans have been successfully trained to spot AI-generated faces in a study led by researchers at the Australian National University (ANU) Emotions and Faces Lab. The study, "Training Humans to Detect AI-generated Faces," is published in PNAS.

As AI systems become increasingly powerful, policymakers around the world are grappling with a difficult question: How can society encourage innovation—and the now-plausible race to truly intelligent AI—while managing potentially catastrophic risks?

A new development in data science has given one popular machine learning tool an improved sense of place, enabling it to make more accurate predictions based on data linked to locations. Researchers from the University of Glasgow and Florida State University have found a way to overcome a key limitation of TabPFN, one of a class of AI tools known as foundation models.

What if your smartwatch could tell when you were struggling emotionally and offer support before you even thought to ask? That's the idea behind a new AI-powered system developed by researchers at the University of Ottawa, one that could change how people access mental health care outside a clinical setting.