Artificial intelligence (AI), particularly deep learning models, are often considered black boxes because their ...

Artificial intelligence (AI) has become a cornerstone of modern business operations, driving efficiencies and delivering insights across various sectors. However, as AI systems become more ...

Abstract Deep learning models have been successful in many areas, but understanding their behavior remains a challenge. Most prior explainable AI ...

Cognitive computing represents an innovative frontier within computer science, merging artificial intelligence, machine learning, and computational ...

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 ...

Building customer trust. AI transparency builds customer trust by making sure systems are fair, equitable and clearly explainable. Ethics in AI. Ethical AI prioritizes human rights, privacy and ...

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 ...

This course explores the field of Explainable AI (XAI), focusing on techniques to make complex machine learning models more transparent and interpretable. Students will learn about the need for XAI, ...

American insurers are being urged not to drag their feet on ensuring their use of AI is “explainable,” as regulators and consumers alike begin to demand it. “It’s not like this is a future issue. The ...

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 ...