AI systems have tremendous potential, but the average user has little visibility and knowledge on how the machines make their decisions. AI explainability can build trust and further push the ...

Artificial intelligence (AI) may have more to offer science than accurate predictions. The patterns it learns could point ...

AI explainability and AI interpretability are notions often used interchangeably, despite immense differences in intention and practical application. This can be fine for high-level conversations ...

Every technology leader I speak with is under the same pressure. Board members want AI. Regulators want transparency. Customers and the business want speed. Somewhere in the middle, the technology ...

Two of the biggest questions associated with AI are “why does AI do what it does”? and “how does it do it?” Depending on the context in which the AI algorithm is used, those questions can be mere ...

Richard Jones, VP of product at ExpenseIn, argues that black box AI cannot police expense fraud and finance teams need ...

An area of great hope and promise for applied artificial intelligence (AI) deep learning is at the intersection of neuroscience and oncology, both challenging fields known for their inherent ...

SALT LAKE CITY, UTAH – Researchers at the University of Utah's Department of Psychiatry and Huntsman Mental Health Institute today published a paper introducing RiskPath, an open source software ...

In past roles, I’ve spent countless hours trying to understand why state-of-the-art models produced subpar outputs. The underlying issue here is that machine learning models don’t “think” like humans ...

Found in knee replacements and bone plates, aircraft components, and catalytic converters, the exceptionally strong metals known as multiple principal element alloys (MPEA) are about to get even ...