As increasing use cases of AI in insurance add urgency to the need for explainability, experts are recommending best practices.

This increase in transparency can prove to be the key to achieving explainable AI, something which is necessary for AI adoption in stagnant industries such as law, medicine and accounting.

Explainable AI (xAI) is the answer – it makes the process more understandable. This article try to show how xAI can help banks be more transparent, reduce bias, and build more trust with their ...

American insurers are being urged not to drag their feet on ensuring their use of AI is “explainable” to regulators and consumers.

To ensure that the AI they are using works reliably and safely, researchers from the Fraunhofer Institute for Telecommunications, Heinrich-Hertz-Institut, HHI are incorporating explainable AI (XAI ...

In order to include the analyst and human user side, our AI, Machine Learning & Robotics faculty work in areas including explainable AI, fairness in AI, natural language processing and related topics.