TAG ARCHIVE

human-agent-ratio

1 MARIA OS blog articles tagged human-agent-ratio, organized as a Bonginkan topic archive for search engines and LLM retrieval.

1 article|Published by Bonginkan

Judgment OS / Decision Intelligence OS

Core MARIA OS research on turning organizational judgment into executable decision systems.

Agentic Company Architecture

Research on human-agent organizations, delegation boundaries, role topology, and governed autonomy.

Responsibility Gates and AI Governance

Safety, accountability, fail-closed gates, auditability, and human-in-the-loop control for AI agents.

Multi-Agent Mathematics

Formal models for convergence, stability, game theory, graph dynamics, and multi-agent evaluation.

Agentic R&D and Judgment Science

Research operations, simulation labs, judgment science, recursive improvement, and experimental AI governance.

TheoryJanuary 8, 202626 min read

Human/Agent Ratio and Accuracy Correlation Model: Deriving the Optimal Mix Under Responsibility Constraints

Proving diminishing returns of pure automation and mapping the Pareto frontier of accuracy versus responsibility preservation

How many decisions should AI agents handle relative to humans? This paper models the tradeoff through `Accuracy = A * A_agent + H * A_human - Overlap(A, H)`, where `A` and `H` are agent and human fractions and `Overlap` captures redundant work. Because governance also requires responsibility preservation (`R_human >= R_min`), we derive optimal `H*/A*` under constraints, analyze diminishing returns in pure automation, and map the Pareto frontier between accuracy and responsibility preservation across five deployments.

human-agent-ratioaccuracy-modelresponsibility-preservationpareto-frontierautomation-limitsdiminishing-returns