\system{} combines five gears with utility-gated dispatch for safety in autonomous agents, proving stability for single agents and providing distributed guarantees for multi-agent CPS, evaluated on UR5 robots.
Levels of autonomy for ai agents
10 Pith papers cite this work, alongside 3 external citations. Polarity classification is still indexing.
10
Pith papers citing it
3
external citations · external index
citation-role summary
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citation-polarity summary
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use method 1representative citing papers
Coding agents struggle to infer least-privilege file permissions by omitting needed accesses while granting unused or sensitive ones, but Sufficiency-Tightness Decomposition improves sensitive-task success by up to 15.8% and reduces attacks.
Formalizes design space for human-LLM collaborative planning along mode, scope, and level axes; evaluates AMBIPOM prototype via user study and benchmark revealing hybrid workflows and trade-offs.
The First Fundamental Theorem of Welfare Economics holds for autonomy-complete competitive equilibria that are autonomy-Pareto efficient, with the classical version recovered in the low-autonomy limit.
The paper names 'agentic literacy debt' as the structural deficit from deploying autonomous AI agents without literacy infrastructure for users to govern them.
Limited legal personhood for AI, implemented via purpose-bound operating companies within human-controlled holding structures, serves as a precautionary governance instrument that enables transparency and accountability without resolving questions of artificial consciousness.
The 2025 AI Agent Index catalogs technical and safety details for 30 deployed AI agents and finds low developer transparency on safety, evaluations, and societal impacts.
Introduces a 5-by-5 design space for agency and autonomy levels in agentic AI systems along with six tactics for compliance-aware deployments.
The Digital Apprentice is a developmental AI framework with methodology capture, human-gated authorization, and runtime alignment correction to enable scalable yet accountable agentic systems.
citing papers explorer
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Managed Autonomy at Runtime: Gear-Based Safety and Governance for Single- and Multi-Agent Cyber-Physical Systems
\system{} combines five gears with utility-gated dispatch for safety in autonomous agents, proving stability for single agents and providing distributed guarantees for multi-agent CPS, evaluated on UR5 robots.
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Do Coding Agents Understand Least-Privilege Authorization?
Coding agents struggle to infer least-privilege file permissions by omitting needed accesses while granting unused or sensitive ones, but Sufficiency-Tightness Decomposition improves sensitive-task success by up to 15.8% and reduces attacks.
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How to Steer Your Multi-Agent System: Human-LLM Collaborative Planning
Formalizes design space for human-LLM collaborative planning along mode, scope, and level axes; evaluates AMBIPOM prototype via user study and benchmark revealing hybrid workflows and trade-offs.
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Post-AGI Economies: Autonomy and the First Fundamental Theorem of Welfare Economics
The First Fundamental Theorem of Welfare Economics holds for autonomy-complete competitive equilibria that are autonomy-Pareto efficient, with the classical version recovered in the low-autonomy limit.
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Agentic Literacy Debt: A Structural Problem the AI Literacy Field Has Not Yet Named
The paper names 'agentic literacy debt' as the structural deficit from deploying autonomous AI agents without literacy infrastructure for users to govern them.
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Precautionary Governance of Autonomous AI: Legal Personhood as Functional Instrument
Limited legal personhood for AI, implemented via purpose-bound operating companies within human-controlled holding structures, serves as a precautionary governance instrument that enables transparency and accountability without resolving questions of artificial consciousness.
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The 2025 AI Agent Index: Documenting Technical and Safety Features of Deployed Agentic AI Systems
The 2025 AI Agent Index catalogs technical and safety details for 30 deployed AI agents and finds low developer transparency on safety, evaluations, and societal impacts.
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Autonomy and Agency in Agentic AI: Architectural Tactics for Regulated Contexts
Introduces a 5-by-5 design space for agency and autonomy levels in agentic AI systems along with six tactics for compliance-aware deployments.
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The Digital Apprentice: A Framework for Human-Directed Agentic AI Development
The Digital Apprentice is a developmental AI framework with methodology capture, human-gated authorization, and runtime alignment correction to enable scalable yet accountable agentic systems.
- Autonomy Reshapes How Personalization Affects Privacy Concerns and Trust in LLM Agents