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 ...

To many AI practitioners and consumers, explainability is a precondition of AI use. A model that, without showing its work, tells a doctor what medicine to prescribe may be mistrusted. No experienced ...

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 ...

Trust is key to gaining acceptance of AI technologies from customers, employees, and other stakeholders. As AI becomes increasingly pervasive, the ability to decode and communicate how AI-based ...

Neel Somani, whose academic background spans mathematics, computer science, and business at the University of California, Berkeley, is focused on a growing disconnect at the center of today’s AI ...

This research initiative highlights the importance of ethical and explainable artificial intelligence in workforce ...

Machine learning models are incredibly powerful tools. They extract deeply hidden patterns in large data sets that our limited human brains can’t parse. These complex algorithms, then, need to be ...