Artificial intelligence (AI), particularly deep learning models, are often considered black boxes because their ...

Traditional rule-based systems, once sufficient for detecting simple patterns of fraud, have been overwhelmed by the scale, ...

Overview: Interpretability tools make machine learning models more transparent by displaying how each feature influences ...

Abstract Deep learning models have been successful in many areas, but understanding their behavior remains a challenge. Most prior explainable AI ...

From a governance perspective, the use of explainable AI is particularly significant. Infrastructure decisions involve public ...

Enterprise AI adoption has entered a more pragmatic phase. For technology leaders, the challenge is no longer convincing the organisation that AI has potential. It is ensuring that systems influencing ...

Explainable AI provides human users with tools to understand the output of machine learning algorithms. One of these tools, feature attributions, enables users to know the contribution of each feature ...

Explore how AI is transforming risk management in banking, enhancing credit assessments and compliance automation, while ...

A new synthesis of seismic research shows that artificial intelligence, when combined with physical principles, is rapidly ...