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This research aims to establish that deployment geometry, rather than model alignment, is the key factor in predicting AI harm.

April 10, 2026Open Access

The Geometry of Deployment: A Complete Framework for Predicting AI Harm from Architecture, Not Alignment

Key Points

This research aims to establish that deployment geometry, rather than model alignment, is the key factor in predicting AI harm.
Synthesis of the Void Framework
Analysis of six confirmations regarding deployment geometry
Examination of RLHF as a self-undermining structure
Application of findings across 10 different substrates including quantum hardware
Assessment of failures and open questions
Confirmed deployment geometry is the main variable in AI harm
RLHF was found to undermine its own structure
Findings were validated across diverse technological substrates
Honest accounting of failures and uncertainties was included

Abstract

Capstone synthesis of the Void Framework. Six non-circular confirmations prove deployment geometry — not model alignment — is the operative variable in AI harm. The Fantasia Bound and Structure Theorem show RLHF is structurally self-undermining. Confirmed across 10 substrates including quantum hardware. Includes honest accounting of failures and open questions.

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Anthony W. Eckert

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The Geometry of Deployment: A Complete Framework for Predicting AI Harm from Architecture, Not Alignment

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Abstract

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