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 ...

Explainable Artificial Intelligence (XAI) seeks to render the operation and decisions of complex machine learning systems transparent and interpretable to users, regulators and other stakeholders. As ...

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

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 ...

When AI falters, it’s easy to blame the model. People assume the algorithm got it wrong or that the technology can’t be trusted. But here’s what I've learned after years of building AI systems at ...

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 ...

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 ...

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 ...