The Chancellor Trap: Administrative Mediation and the Hollowing of Sovereignty in the Algorithmic Age

TL;DR

This paper argues that AI-mediated governance can obscure failures and weaken sovereignty by reducing public visibility of issues, highlighting the need for institutional designs that reintroduce transparency.

Contribution

It formalizes the concept of chancellorization as a principal-agent problem in digital governance and provides empirical evidence linking digitalization to reduced public visibility of AI failures.

Findings

Higher state capacity correlates with lower public visibility of AI failures.

Digitalization increases internal failure management but decreases external accountability.

Governance effectiveness may paradoxically hinder transparency.

Abstract

The contemporary governance discourse on Artificial Intelligence often emphasizes catastrophic loss-of-control scenarios. This article suggests that such framing may obscure a more immediate failure mode: chancellorization, or the gradual hollowing out of sovereignty through administrative mediation. In high-throughput, digitally legible organizations, AI-mediated decision support can reduce the probability that failures become publicly legible and politically contestable, even when underlying operational risk does not decline. Drawing on the institutional history of Imperial China, the article formalizes this dynamic as a principal-agent problem characterized by a verification gap, in which formal authority (auctoritas) remains downstream while effective governing capacity (potestas) migrates to intermediary layers that control information routing, drafting defaults, and evaluative signals. Empirical support is provided through a multi-method design combining historical process tracing with a cross-national panel plausibility probe (2016-2024). Using incident-based measures of publicly recorded AI failures and administrative digitization indicators, the analysis finds that higher state capacity and digitalization are systematically associated with lower public visibility of AI failures, holding AI ecosystem expansion constant. The results are consistent with a paradox of competence: governance systems may become more effective at absorbing and resolving failures internally while simultaneously raising the threshold at which those failures become politically visible. Preserving meaningful human sovereignty therefore depends on institutional designs that deliberately reintroduce auditable friction.