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 ...

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.

The answer: both suffer from a “truthiness” problem. Truthiness is a term coined by Stephen Colbert to describe the tactic of weaving facts into a false narrative. Conspiracy theories like QAnon rely ...

Explainability is not a technology issue — it is a human issue. Therefore, it is incumbent on humans to be able to explain and understand how AI models come to the inferences that they do, said Madhu ...

TruEra, provider of a suite of AI quality solutions, is releasing TruLens, an open source explainability software tool for machine learning models that are based on neural networks. TruLens is a ...

You’ve heard the maxim, “Trust, but verify.” That’s a contradiction—if you need to verify something, you don’t truly trust it. And if you can verify it, you probably don’t need trust at all! While ...