Engineering Trustworthy Agentic AI for Critical Systems
3.20T1 sourcearXiv cs.MA
Source record
Published by arXiv cs.MA (T1 source). The original is at https://arxiv.org/abs/2607.18548.
Pipeline notes
The summary and note below are generated by the signal pipeline — they are Beyond Desk’s reading, not quotations from the source.
SummarySurvey paper treating trustworthiness as a first-class engineering property for agentic AI systems. Organizes trust around five dimensions (safety, robustness, transparency, accountability, privacy) mapped to an assurance workflow, then examines application across power systems, autonomous vehicles, HPC, and communication networks, proposing a cross-domain certification framework.
Why it mattersUseful reference for anyone designing or auditing agents in safety-critical settings. Maps concrete trust mechanisms, failure modes, and metrics across four engineering domains under one framework.
Cited by
No citations on record.
