Back to search

Article

The Supervision Paradox: AI Capability Growth Necessitates Usage Contraction in High-Loss Domains

2026-03-19

Abstract excerpt

Current AI governance rests on an implicit assumption: that human-in-the-loop oversight can scale safely alongside generative AI systems. We argue that this assumption is structurally untenable. Three constraints hold simultaneously: legal liability remains with humans, human cognitive throughput has a biological ceiling, and economic pressures drive AI output velocity beyond that ceiling. When output velocity exc...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
73952098-86b3-5dff-91f6-27d6e5443cc2
DOI
10.20944/preprints202603.1507.v1
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
The Supervision Paradox: AI Capability Growth Necessitates Usage Contraction in High-Loss DomainsDOI 10.20944/preprints202603.1507.v1
The Supervision Paradox: AI Capability Growth Necessitates Usage Contraction in High-Loss DomainsSemantic proximity
Flow-by-Flow: Content-Judgment Bypass for Governing AI Output in High-Loss DomainsSemantic proximity
Flow-by-Flow: Content-Judgment Bypass for Governing AI Output in High-Loss DomainsSemantic proximity
From Behavioural Offloading to Governance Responsibility: Social Behaviour, AI Governance, and Educational Reconstruction in the Age of Ubiquitous AISemantic proximity
A Framework for Ethical AI-Generated Content GovernanceSemantic proximity
Artificial eXperience Intelligence (AXI): An Engineering Discipline for the Human Experience of AI SystemsSemantic proximity
Harm-Conditioned Computational Friction as a Diagnostic of Alignment Robustness: A Critical Review and Evaluation FrameworkSemantic proximity
Decision Support or High-Risk? Classifying AI Workforce-Intelligence Systems Under the EU AI ActSemantic proximity
Who Embraces the Machine? How Familiarity, Mastery and Context Shape Attitudes towards AI InvolvementSemantic proximity
Who Signs the Opinion? Agentic AI, Accountability, and the Delegation Boundary in Actuarial WorkSemantic proximity
Coverage and Complementarity of Three Agentic AI Risk Taxonomies Across 131 Real World IncidentsSemantic proximity
Elevate Before You Eliminate: Firms Should Redesign High-Risk Roles Before Any AI-Attributed LayoffsSemantic proximity
Select a neighboring publication to make it the new centre.