Towards trustworthy agentic AI: a comprehensive survey of safety, robustness, privacy, and system security

In three linesComprehensive survey on trustworthy agentic AI systems (LLMs augmented with planning, tool use, memory). Examines safety, robustness, privacy, and system security. Proposes unified metrics, benchmarks, and stage-targeted mitigation strategies across agent workflows. Identifies open challenges: self-evolving agents, runtime verification, privacy-preserving personalization.

Summary generated by Claude — human-verified