An AI model trained to detect abnormalities on breast MR images accurately depicted tumor locations and outperformed ...

Explainable AI (XAI) is an emerging field in machine learning that aims to address how black box decisions of AI systems are made. This area inspects and tries to understand the steps and models ...

Explainability is now a requirement for institutions deploying AI in financial crime compliance. It supports better ...

In a major development, researchers have found compelling new evidence that artificial intelligence (AI) can significantly ...

As such, explainable AI is necessary to help companies pick up on the "subtle and deep biases that can creep into data that is fed into these complex algorithms.

Using artificial intelligence, researchers show how γ-secretase recognizes substrates - an important advance for fundamental ...

A Future with Explainable AI. Explainable AI is the future of business decision-making. Explainable decision making plays a role in every aspect of AI solutions from training, QA, deployment, ...

As tech writer Scott Clark noted on CMSWire recently, explainable AI provides necessary insight into the decision-making process to allow users to understand why it is behaving the way it is.

An explainable AI yields two pieces of information: its decision and the explanation of that decision. This is an idea that has been proposed and explored before. However, ...

Explainable AI addresses this limitation by providing insight into the model’s decision-making process,” the Virginia Tech team notes. The study authors actually created and tested an MPEA ...