A new explainable AI technique transparently classifies images without compromising accuracy. The method, developed at the University of Michigan, opens up AI for situations where understanding why a ...

Uptake of explainable artificial intelligence (XAI) methods in geoscience is currently limited. We argue that such methods that reveal the decision processes of AI models can foster trust in their ...

The mainstream adoption of machine learning in investment management has created a widening gap between predictive ...

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors ...

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 ...

Artificial intelligence systems are becoming increasingly powerful—but also harder to understand. A new study introduces ...

A team has developed an explainable AI model for automatic collision avoidance between ships. The Titanic sunk 113 years ago on April 14-15, after hitting an iceberg ...

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 ...

Artificial intelligence (AI) continues to transform industries—from finance and healthcare to marketing and logistics. Yet one persistent challenge remains: trust. Many organizations see AI models as ...

In todays fast evolving financial landscape, artificial intelligence and machine learning are changin how credit decisions get made. But the traditional “black box” models cause worry 'cause nobody ...

The terrestrial water cycle is a fundamental component of Earth's climate system, governing the exchange of water between land surfaces and the atmosphere.