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 ...

"An AI system can be technically safe yet deeply untrustworthy. This distinction matters because satisfying benchmarks is ...

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 ...

Does your model work? Can it explain itself? Heather Gorr talks about explainability and machine learning. You can send press releases for new products for possible coverage on the website. I am also ...

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 ...

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 ...

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

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 ...