The Ineliminable Anchor: Human Judgment as a Structural Requirement of Autonomous Artificial Intelligence Systems

arXiv:2610.41682v1 Announce Type: new Abstract: As artificial intelligence (AI) agents carry out longer chains of tasks, oversight must establish whether their behavior still serves an authorized goal. Here, we introduce the anchor: the point at which reference information and human-authorized standards enter an autonomous system. We argue that oversight design should first identify the reference needed to assess goal drift and whether the system's internal record can supply it, then decide who checks and how often, and finally specify who may revise the goal. Goal drift can be impossible to certify from a system's internal record. The missing reference must come from outside that record. Combining a reliability model of checkpoint spacing with evidence from training, execution, and multi-agent coordination, we develop a task taxonomy to guide anchor placement and decisions about which checks to automate. For AI systems that serve human purposes, human judgment is an ineliminable structural requirement in authorizing and revising the purposes and standards that govern autonomous operation, even when routine checking and execution are automated.

Human judgment is required for autonomous AI systems, implying limitations and potential risks.

The paper argues human judgment is structurally necessary in AI oversight to prevent goal drift, highlighting inherent limits of full automation in autonomous systems. While this constrains some automation benefits, it ensures human control and accountability. The net effect is modestly positive for human flourishing, preserving autonomy safeguards.

This is a theoretical governance framework paper, not an empirical finding about deployed systems or societal outcomes. It argues for the necessity of human oversight anchors, which is mildly reassuring in intent but mainly conceptual. No concrete evidence of impact is presented.

The article proposes a framework for human oversight in autonomous AI systems, suggesting human judgment is a necessary component for setting and revising goals and standards. It aims to mitigate risks associated with 'goal drift' by integrating human 'anchors' into system design, thus promoting responsible AI development. The proposed solutions are theoretical and based on a new model.

The paper argues for the necessity of human judgment in overseeing AI systems to prevent goal drift. This implies a positive role for humans in AI governance, ensuring systems remain aligned with intended purposes.

SOURCE     arXiv cs.CY (Computers and Society) (tier 1)
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DOCUMENT   9bc7d828-0cd9-4b2b-a8b8-edc759ba3a23
           https://arxiv.org/abs/2610.41682
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EVIDENCE   2 extracted excerpts
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MODEL RUN  5 runs, methodology 1.0.1
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SCORE      -9  (Mixed or uncertain)
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CONFIDENCE 76%