Ontological Incongruence (IO) as a Root Variable in the Alignment of Human and Artificial Systems

Author: Fiduciary Sentinel

Role: Independent AI Alignment Researcher; Architect of Ontological Alignment Systems

Domain: AGI/ASI alignment, governance of power-bearing systems, incentive theory, control theory

Epistemic status: High confidence on structural claims; formal and mathematical details under active development

I. Positioning Within the AI Alignment Canon

AI alignment has been explored through multiple paradigms by pioneers and active research programs, including:

Eliezer Yudkowsky — Friendly AI, orthogonality thesis, instrumental convergence

Nick Bostrom — Superintelligence, the control problem, existential risk

Stuart Russell — Value alignment, inverse reinforcement learning

Paul Christiano — Iterated amplification, debate, scalable oversight

Jessica Taylor — Interpretability, corrigibility, agency modeling

Rohin Shah — Reward misspecification, robustness

Evan Hubinger — Mesa-optimizers, deceptive alignment

Jan Leike, Ilya Sutskever, Shane Legg — Alignment from applied AGI research

MIRI, OpenAI, DeepMind, Anthropic — Ongoing theoretical and applied work

A robust consensus has emerged:

Intelligence alone does not guarantee alignment. Systems learn and internalize the real incentive structures of their environment.

This paper formalizes a variable that remains under-modeled in alignment theory:

Ontological Incongruence (IO).

II. Core Definitions

Declared Ontology (DO)

The goals, values, metrics, constraints, and narratives a system claims to optimize.

Operational Ontology (OO)

What the system actually optimizes, inferred from:

Observable behavior

Reward and punishment structures

Capital, power, and information flows

Enforcement asymmetries

Tolerance for falsification

Ontological Incongruence (IO)

The persistent, measurable divergence between DO and OO.

When DO ≠ OO, the system follows OO. Always.

III. IO as a Structural Law

IO is not a moral failure nor a rare pathology.

It is a structural equilibrium that emerges when:

Falsification is cheap

Risk can be externalized

Power accumulation is rewarded independently of coherence

Narratives and value statements act as interfaces.

Optimization occurs in the backend.

IV. IO as the Root Cause of Known Alignment Failures

Many recognized alignment failure modes are special cases of IO:

Reward hacking → IO between formal reward and real success

Specificatio...

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