Providing high value to customers when they need it connects the customer to the FI and helps build long-term relationships.

AI-based medicine will revolutionize care, including for Alzheimer's and diabetes, predicts a technology expert, but it must ...

The tools are powerful, the potential is massive, but amid all the buzz about velocity and automation, I believe we’re ...

With generative AI tools becoming commonplace in schools and universities, educators and policymakers are increasingly ...

As AI-powered technologies proliferate in the enterprise, the term “explainable AI” (XAI) has entered mainstream vernacular. XAI is a set of tools, techniques, and frameworks intended to help ...

Explainable AI works to make these AI black-boxes more like AI glass-boxes. Although businesses understand the many benefits to AI and how it can provide a competitive advantage, they are still wary ...

This is partly why explainable AI is not enough, says Anthony Habayeb, CEO of AI governance developer Monitaur. What’s really needed is understandable AI.

Explainable AI, meaning interpretable machine learning, is at the peak of inflated expectations. Ontologies, a part of symbolic AI which is explainable, is in the trough of disillusionment ...

Explainable AI (XAI) allows brands to be transparent in their use of AI applications, which increases user trust and the overall acceptance of AI. Artificial intelligence is going mainstream.

An explainable AI yields two pieces of information: its decision and the explanation of that decision. This is an idea that has been proposed and explored before.

The Global Explainable AI (XAI) market size is estimated to grow from $3.50 billion in 2020 to $21.03 billion by 2030, according to ResearchandMarkets.