paperMay 2026Unreviewed

Intelligence as Managed Autonomy: Failure, Escalation, and Governance for Agentic AI Systems

Srini Ramaswamy

Abstract

As autonomous and agentic AI systems scale in robotic and human-machine environments, managing hallucination and persistent but unjustified action remains an open challenge. Rather than attributing these failures solely to model or alignment limitations, this paper explores the architectural vulnerability of unbounded autonomy - the presumption that an agent should continue operating regardless of rising uncertainty. It introduces a theory of managed autonomy that defines intelligent behavior th

Cite

@misc{ramaswamy2026intelligence,
  title = {{Intelligence as Managed Autonomy: Failure, Escalation, and Governance for Agentic AI Systems}},
  author = {Srini Ramaswamy},
  year = {2026},
  month = may,
  eprint = {2605.27628},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2605.27628}
}