A machine can now reject a loan, flag a patient as high-risk, rank a job applicant, identify a military target, recommend a ...

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 ...

Why transparency and explainability are now the currencies of AI success ...

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 ...

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

Automation should not replace accountability.

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 ...

Explainability is not just a roadblock to AI adoption - it also has implications for public health and safety. This is how the tensions between transparency, accuracy and performance are coming to a ...

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

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 ...