Healthcare is a complex socio-technical system, not a purely technical environment. Clinical decisions are shaped not only by ...

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 ...

As enterprises shift from AI experimentation to scaled implementation, one principle will separate hype from impact: explainability. This evolution requires implementing 'responsible AI' frameworks ...

Deep learning neural networks, exemplified by models like Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs) and Generative Adversarial Networks (GANs), have achieved remarkable ...

Artificial intelligence is seeing a massive amount of interest in healthcare, with scores of hospitals and health systems already have deployed the technology – more often than not on the ...

Would you blindly trust AI to make important decisions with personal, financial, safety, or security ramifications? Like most people, the answer is probably no, and instead, you’d want to know how it ...

NEW YORK--(BUSINESS WIRE)--Last week, leading experts from academia, industry and regulatory backgrounds gathered to discuss the legal and commercial implications of AI explainability. The industry ...

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 ...