This supercharging of extremist rhetoric will only amplify and encourage the antisemitism that is already surging on X and ...

Drug discovery has long been criticized for its slow, costly, and failure-prone nature. Traditional approaches, particularly ...

Explainable AI begins with people. AI engineers can work with subject matter experts and learn about their domains, studying their work from an algorithm/process/detective perspective.

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.

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, ...

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, ...

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

Explainable AI has the added requirement of being able to explain to a human being how it arrived at a conclusion. We have already seen this as a mandate in medical diagnostic software, ...

In it, explainable AI is placed at the peak of inflated expectations. In other words, we have reached peak hype for explainable AI. To put that into perspective, a recap may be useful.

Breakthrough method detects subtle molecular signals in blood, allowing for diagnosis months or even years before symptoms appear, Australian scientists say.

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