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 ...

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 ...

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 ...

AI now touches high-stakes decisions, credit, hiring, and healthcare, yet many systems remain black boxes. Governance is lagging adoption: Recent enterprise research finds 93 percent of organizations ...

While accuracy and speed are critical, the study notes that interpretability is now a key requirement for deploying AI in ...

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 ...