Automation should not replace accountability.

Researchers have developed AdapGNN, a novel model-agnostic framework that addresses the oversmoothing problem in graph neural ...

A practical review of explainable AI examines how transparency and interpretability improve trust in high-stakes ...

Artificial Intelligence is quickly becoming ubiquitous in personal and professional lives in ways we both observe and others we don’t see as readily. Artificial Intelligence is used to influence ...

AI and data are reshaping how work gets done. Many business leaders are experimenting, piloting tools, or automating fragments of their business with AI. That activity creates the feeling of progress.

CEO of Neurala, a deep learning neural network software company, and founding director of the Neuromorphics Lab at Boston University. Automation: A word that simultaneously evokes technological and ...

Value stream management involves people in the organization to examine workflows and other processes to ensure they are deriving the maximum value from their efforts while eliminating waste — of ...

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 ...

As artificial intelligence (AI) tools continue to reshape healthcare delivery and operations, legal and compliance teams should proactively navigate ...

The so-called "black-box" aspect of AI, usually referred to as the explainability problem, or X(AI) for short, arose slowly over the past few years. Still, with the rapid development in AI, it is now ...