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

MIT researchers introduce a technique that improves how AI systems explain their predictions, helping users assess trust in ...

One of the most important aspects of data science is building trust. This is especially true when you're working with machine learning and AI technologies, which are new and unfamiliar to many people.

Artificial intelligence is seeing a massive amount of interest in healthcare, with scores of hospitals and health systems already have deployed the technology – more often than not on the ...

In a global report issued by S&P, 95% of enterprises across various industries said that Artificial Intelligence (AI) adoption is an important part of their digital transformation journey. We’re ...

Enterprise-grade explainability solutions provide fundamental transparency into how machine learning models make decisions, as well as broader assessments of model quality and fairness. Is yours up to ...

While machine learning and deep learning models often produce good classifications and predictions, they are almost never perfect. Models almost always have some percentage of false positive and false ...

Can you tell the difference between a husky and a wolf? Both are large canines with shaggy, dense fur. Both have longer snouts and pointy ears. Both look huggable — but one definitely isn’t. And while ...

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 ...