AI RESEARCH
Explainable AI to Improve Machine Learning Reliability for Industrial Cyber-Physical Systems
arXiv CS.LG
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ArXi:2601.16074v2 Announce Type: replace Industrial Cyber-Physical Systems (CPS) are sensitive infrastructure from both safety and economics perspectives, making their reliability critically important. Machine Learning (ML), specifically deep learning, is increasingly integrated in industrial CPS, but the inherent complexity of ML models results in non-transparent operation. Rigorous evaluation is needed to prevent models from exhibiting unexpected behaviour on future, unseen data. Explainable AI (XAI) can be used to uncover model reasoning, allowing a extensive analysis of behaviour.