As increasing use cases of AI in insurance add urgency to the need for explainability and transparency, experts are recommending "explainable AI" best practices to follow and key challenges to ...

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.

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

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 ...

HACARUS’ Sparse Modeling is a cutting-edge technology that enables AI to deliver fast, explainable results. It is energy efficient, can bring AI to embedded low-power applications and can ...