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

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 ...

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.

Researchers from chemistry, biology, and medicine are increasingly turning to AI models to develop new hypotheses. However, it is often unclear on which basis the algorithms come to their conclusions ...

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.