• Contemporary AI systems are neither explainable nor interpretable: Due to the nature of these systems, they rely on non-linear algebra where all inputs get mixed up inextricably, thereby making it ...

Explainable AI (XAI) exists to close this gap. It is not just a trend or an afterthought; XAI is an essential product capability required for responsibly scaling AI. Without it, AI remains a powerful ...

AI shifts roles from data assembly to decision leadership. As AI handles mechanical planning work, supply chain professionals spend more time on strategy, scenario planning, and risk-based ...

As increasing use cases of AI in insurance add urgency to the need for explainability and transparency, experts are recommending "explainable AI" best practices to follow and key challenges to look ...

AI decisions are only defensible when the reasoning behind them is visible, traceable, and auditable. “Explainable AI” delivers that visibility, turning black-box outputs into documented logic that ...

In this week's "Five questions with" feature, meet Deepshikha Bhati, a Kent State University at Stark faculty member with a ...

As Artificial Intelligence (AI) becomes an indispensable tool in enterprise financial operations, businesses are swiftly adopting automated solutions for processing invoices, detecting fraud, and ...

While atmospheric turbulence is a familiar culprit of rough flights, the chaotic movement of turbulent flows remains an unsolved problem in physics. To gain insight into the system, a team of ...