Transparency and explainability are only way organizations can trust autonomous AI.

Researchers have introduced a new framework designed to evaluate AI systems using measurable risk and assurance metrics before deployment. The study, “Risk-Based AI Assurance Framework (RBAAF)”, ...

NEW YORK--(BUSINESS WIRE)--Last week, leading experts from academia, industry and regulatory backgrounds gathered to discuss the legal and commercial implications of AI explainability. The industry ...

In high-stakes settings like medical diagnostics, users often want to know what led a computer vision model to make a certain prediction, so they can determine whether to trust its output. Concept ...

H2O.ai, the leading open-source AI platform company, partners with xAmplify, Australia's leading sovereign AI integrator. Together, we're combining H2O.ai's world-class Agentic AI platform with ...

AI could drive growth, but confidence in the technology is eroding.

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 ...

Artificial intelligence is transforming how financial institutions manage compliance. Tasks like onboarding, screening, and transaction monitoring are increasingly handled by machine learning models ...

What does it mean to trust AI? According to AI expert Ron Brachman, “it’s when technology demonstrates consistent behavior over time.” Trust is a cornerstone of any successful AI deployment. Without ...

Strong brands can still be misunderstood -- because they have not made their story easy for machines to summarize accurately.