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

Two of the biggest questions associated with AI are “why does AI do what it does”? and “how does it do it?” Depending on the context in which the AI algorithm is used, those questions can be mere ...

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 ...

What does it mean to trust AI? According to AI expert Ron Brachman, “it’s when technology demonstrates consistent behavior over time.” Trust is a cornerstone of any successful AI deployment. Without ...

Artificial intelligence is deeply embedded in the daily workings of financial institutions, whether analyzing credit risk, automating underwriting, flagging fraud, or generating investment insights.

The key to enterprise-wide AI adoption is trust. Without transparency and explainability, organizations will find it difficult to implement success-driven AI initiatives. Interpretability doesn’t just ...

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 ...

Liberate AI, an interdisciplinary project uniting researchers from the medical domain, computer science, and trustworthy artificial intelligence (AI), aims to develop an AI model capable of supporting ...

Radiation Oncology has evolved rapidly in recent decades in terms of innovations in treatment equipment, volumetric imaging, information technology and increased knowledge in cancer biology. New ...

You’ve heard the maxim, “Trust, but verify.” That’s a contradiction—if you need to verify something, you don’t truly trust it. And if you can verify it, you probably don’t need trust at all! While ...