Scalable Oversight: Supervising AI Systems That Exceed Human Capabilities

Paul Christiano (ARC), Jan Leike (OpenAI)

Abstract

We discuss the challenge of providing oversight to AI systems that may exceed human capabilities in some domains. We propose scalable oversight as a research agenda for maintaining meaningful human control.

Eigenvector Insight — Zone III / PASF-PADE AnalysisNot part of the original paper

Eigenvector Research — Marco van Hurne

How this paper contributes to solving the Zone III problem (PASF-PADE)

Scalable oversight is the central governance challenge for Zone III. As agents become more capable, human oversight becomes harder. This paper frames the problem correctly: the goal is not to prevent autonomy but to maintain meaningful control as autonomy increases.

Why AI is not sufficient for Zone III without this

Zone III refers to high-complexity, high-risk, long-running agentic workflows — the class of enterprise AI deployments where a single failure can cascade across hundreds of steps. Standard AI models, trained to predict the next token, are not inherently designed for durable, governed, multi-step execution. This paper addresses one or more of the structural gaps that make Zone III deployments unsafe without explicit architectural intervention.

Key Contributions

→Scalable oversight research agenda
→Debate and amplification techniques
→Human control preservation methods

Topics

scalable oversighthuman controlAI safetygovernance

Relevance Scores

Long-Horizon Score82

Enterprise Score90

Completeness80

Paper Info

Year2023

VenuearXiv

Typetheoretical framework

ChapterCh. 3

Authors2

Zone III Analysis

Frameworks

AEGIS OCG