Explainability is now a requirement for institutions deploying AI in financial crime compliance. It supports better ...

MOTOR Ai is scaling its Level 4 autonomous driving software to be deployed in German public transport this year.

AI is vying for circuit and embedded-system design jobs, but in 2025, it still requires a seasoned engineer to ride shotgun.

Identifying false positives is almost as important as detecting genuine concerns during quality control (QC) processes.

Using artificial intelligence, researchers show how γ-secretase recognizes substrates - an important advance for fundamental ...

Explainable AI (XAI) is an emerging field in machine learning that aims to address how black box decisions of AI systems are made. This area inspects and tries to understand the steps and models ...

As such, explainable AI is necessary to help companies pick up on the "subtle and deep biases that can creep into data that is fed into these complex algorithms.

Researchers from DZNE, Ludwig-Maximilians-Universität München (LMU), and Technical University of Munich (TUM) have found that ...

As tech writer Scott Clark noted on CMSWire recently, explainable AI provides necessary insight into the decision-making process to allow users to understand why it is behaving the way it is.

A Future with Explainable AI. Explainable AI is the future of business decision-making. Explainable decision making plays a role in every aspect of AI solutions from training, QA, deployment, ...

Explainable AI addresses this limitation by providing insight into the model’s decision-making process,” the Virginia Tech team notes. The study authors actually created and tested an MPEA ...