Transparency and explainability are only way organizations can trust autonomous AI.

Scientists have developed and tested a deep-learning model that could support clinicians by providing accurate results and clear, explainable insights—including a model-estimated probability score for ...

AI pilots must prove measurable operational value. Many organisations are discovering that AI maturity now hinges on operational visibility rather than model capability. In financial services, where ...

Artificial intelligence has become central to business operations, from procurement to financial services to customer experience. But as adoption accelerates, one concern remains constant: trust.

When AI falters, it’s easy to blame the model. People assume the algorithm got it wrong or that the technology can’t be trusted. But here’s what I've learned after years of building AI systems at ...

NIMS has been developing chemical sensors as a key component of artificial olfaction technology (olfactory sensors), with the aim of putting this technology into practical use. In a new study, ...

Solution slashes case analysis time by 75%, eliminates alert fatigue and fragmented data, delivering certainty and empowering analysts to focus on high-priority incidents. BENGALURU, India and AUSTIN, ...

Patients worldwide are cautiously optimistic about the use of AI in healthcare. Most support it as a helpful assistant, but few trust it to replace doctors, according to a new study that reveals trust ...

With insurance sector AI solutions, explainability has become a roadblock to broader AI adoption. But that barrier is breaking.