Transparency and explainability are only way organizations can trust autonomous AI.

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 ...

Building and scaling AI with trust and transparency is crucial for any organization. For explainable AI (XAI) to be effective, it must enable transparency, explain the predictions and algorithm and ...

MIT researchers introduce a technique that improves how AI systems explain their predictions, helping users assess trust in ...

Artificial intelligence is seeing a massive amount of interest in healthcare, with scores of hospitals and health systems already have deployed the technology – more often than not on the ...

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 ...

Leaders who align artificial intelligence strategy with clinical priorities, provide education, and measure impact transparently will be best positioned to scale the technology responsibly and ...