Explainable, Interpretable & Trustworthy AI for Intelligent Digital Twin: Case Study on Remaining Useful Life

arXiv:2301.06676v2 Announce Type: replace
Abstract: Artificial intelligence (AI) and Machine learning (ML) are increasingly used in energy and engineering systems, but these models must be fair, unbiased, and explainable. It is critical to have confidence in AI's trustworthiness. ML techniques have been useful in predicting important parameters and in improving model performance. However, for these AI techniques to be useful for making decisions, they need to be audited, accounted for, and easy to understand. Therefore, the use of explainable AI …

abstract artificial artificial intelligence arxiv case case study confidence cs.lg digital digital twin energy engineering fair intelligence intelligent life machine machine learning stat.ap stat.co study systems trustworthy trustworthy ai twin type unbiased