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The Governance Inversion Hypothesis: Why More AI Regulation May Produce Less Organisational Control

arXiv:2606.26117v2 Announce Type: replace Abstract: This paper introduces the Governance Inversion Hypothesis (GIH) to explain a growing paradox in artificial intelligence (AI) governance: under conditions of increasing regulatory expansion and technological complexity, organisations may become more formally governed while simultaneously experiencing a decline in operational control over AI systems. Existing AI governance frameworks generally assume that stronger regulation improves accountabili

Record details

Published: 4 August 2026
Source: arXiv cs.CY
Category: Research
Topics: Regulation · Transparency
Retrieved: 4 August 2026

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These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

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How to cite this record

ethics.ai (4 August 2026), “The Governance Inversion Hypothesis: Why More AI Regulation May Produce Less Organisational Control,” evidence record 15846, https://ethics.ai/record/15846 (originally published by arXiv cs.CY).

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