Would you blindly trust AI to make important decisions with personal, financial, safety, or security ramifications? Like most people, the answer is probably no, and instead, you’d want to know how it ...

In late October 2020, venture capital firm Wing conducted a survey, “Chief Data Scientist Survey,” of 320 of the senior-most data scientists at both global corporations and venture-backed startups, in ...

Building and scaling AI with trust and transparency is crucial for any organization. For explainable AI (XAI) to be effective, it must enable transparency, explain the predictions and algorithm and ...

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 ...

We have built financial systems that exceed human comprehension, then dressed them in the language of transparency. The reckoning will not be kind.

The Madras HC is reviewing the use of an AI tool, Superlaw Courts, to identify specific issues in an arbitration case.

The reason for this shift is simple: data gravity. The core holds the most complete, consistent and authoritative dataset available to the institution. Moving AI decisioning closer to this data ...

The financial services industry is undergoing an AI-driven transformation that extends well beyond the generative-AI headlines. Chatbots may capture attention, but a far quieter and more consequential ...