Many past machine learning approaches to microplastic detection have been criticised for relying on idealised datasets ...

His work reflects how AI-native platforms address singular challenges in financial data handling, fraud detection, and risk ...

Mortgage servicing is a serious challenge for institutions striving for operational efficiency, regulatory compliance, and ...

As customer expectations evolve, businesses are seeking more advanced AI solutions that can bridge the gap between automated ...

While AI can improve how legal practitioners function and how people access the justice system, Carla L. Reyes, a recognized ...

Gade explains, “for AI to be successfully implemented at scale, people need to learn to rely on similar abstractions, and AI needs to amplify trust. People need to understand how the machine is ...

In my previous article, I discussed the importance of AI explainability and the different categories of AI explainability, explainable predictions, explainable algorithms and interpretable ...

It is important that organizations understand who trains their AI systems, what data was used and, just as importantly, what went into their algorithms’ recommendations. A high-quality explainable AI ...

Explainable AI Article by Karen B. Roberts Photo illustration by Jeffrey C. Chase | Photos by Evan Krape January 29, 2024 UD researchers leverage trustworthy AI to improve seafloor data intelligence ...

In an era where AI adoption frequently outpaces regulatory readiness, Archana Pattabhi, Senior Vice President at a leading global bank, led a forward-looking transformation that redefined how ...