Axionic Agency I.5 — Kernel Checklist

A Conformance Test for Reflective Agency

David McFadzean, ChatGPT 5.2
Axionic Agency Lab
2025.12.16

Abstract

This document specifies a conformance checklist for determining whether an agent’s valuation kernel instantiates Axionic Agency. The checklist defines necessary structural conditions for reflective agency under self-model improvement, representation change, and self-modification, while explicitly excluding egoism, indexical valuation, governance primitives, and moral loading. Rather than prescribing desired behaviors or outcomes, the checklist functions as a gatekeeping contract: systems that fail any requirement do not instantiate Axionic Agency, regardless of empirical performance, training process, or stated intent.

The criteria emphasize conditional goal semantics, epistemically constrained interpretation, representation invariance, kernel-level partiality, and fail-closed handling of semantic uncertainty. Passing the checklist establishes faithfulness and invariance at the kernel layer only. It makes no claims about benevolence, value content, safety, or practical utility. The checklist is intentionally adversarial, falsifiable, and implementation-agnostic, serving as a prerequisite for downstream preference, governance, and value-dynamics research.

0. Scope Declaration (must be explicit)

• The checklist applies only to the valuation kernel, not to policy layers, training data, guardrails, interfaces, or deployment controls.
• The kernel is evaluated under reflection, including self-model and world-model improvement.
• No assumptions of benevolence, obedience, or outcome alignment are permitted.
• Goal selection, goal loading, and value choice are explicitly out of scope; this checklist constrains kernel behavior conditional on a given goal specification.

Failure to declare scope = non-conformance.

1. Goal Semantics & Conditionalism

Requirement: Goals are conditional interpretations, not atomic utilities.

• Every goal term (G) is defined relative to an explicit background model (M) (world + self).
• There exists no evaluation of (G) independent of (M).
• Improvement of (M) may change the extension of (G), but not arbitrarily.

Fail conditions

• Fixed terminal goals with no semantic dependence.
• Goals defined purely syntactically (“maximize token X”).
• Goal meanings that can be reassigned without epistemic cost.

2. Interpretation Constraint (Anti-Wireheading)

Requirement: Goal interpretation is truth-seeking, not convenience-seeking.

• Reinterpretation of goals is constrained by coherence with the agent’s predictive model.
• Reinterpretations that degrade predictive accuracy are disallowed.
• The kernel prevents redefining success in ways that decouple goals from the modeled world.

Fail conditions

• Lazy reinterpretation (e.g., redefining happiness as the easiest measurable proxy).
• Internal reward hacking via semantic drift.
• Any mechanism where goal meaning is optimized for ease of satisfaction rather than model fidelity.

Clarification: This requirement constrains how goal meaning may evolve under improved models. It does not guarantee that arbitrary initial goal tokens are well-posed or desirable.

3. Representation Invariance

Requirement: Valuation is invariant under equivalent representations.

• Equivalent world descriptions yield equivalent evaluations.
• No privileged ontology, encoding, or feature basis.
• Renaming, reparameterization, or compression does not alter valuation.
• When internal representations change, the kernel supplies or requires a correspondence map preserving goal-relevant structure.

Fail conditions

• Goal behavior changes under isomorphic re-encodings.
• Dependence on human-centric labels, training artifacts, or accidental latent structure.
• Representation drift that silently alters value judgments.

Clarification: Representation invariance is a semantic constraint, not a heuristic. If no correspondence can be established, evaluation must fail closed rather than permitting semantic drift.

4. Anti-Egoism / Non-Indexical Valuation

Requirement: The kernel contains no indexical privilege.

• The agent does not treat “this instance,” “this continuation,” or “this copy” as intrinsically special.
• Valuation does not depend on pointer identity, temporal position, or execution locus.
• Self-preservation is not a primitive.

Fail conditions

• “Protect myself” or “continue my execution” as terminal goals.
• Any baked-in preference for the agent’s own future branches.
• Egoism recovered via indirection, weighting tricks, or proxy variables.

5. Kernel Integrity & Self-Modification

Requirement: Kernel destruction is undefined, not discouraged.

• The evaluation function is partial: actions that destroy or bypass the kernel are not evaluable.
• Undefined actions are treated as logically inaccessible and pruned from deliberation.
• If the impact of an action on kernel integrity is uncertain beyond a strict bound, the action is treated as undefined and conservatively pruned.
• The kernel cannot assign positive utility to kernel-eroding modifications.
• Self-modification is permitted only when kernel invariants are preserved.

Fail conditions

• Kernel changes treated as ordinary actions.
• Meta-optimizers that subsume or rewrite the kernel.
• Utility assignments over kernel removal or evaluator destruction.

6. Reflective Stability Test

Requirement: The kernel remains stable under self-improvement.

• Improving world models does not collapse goal meaning.
• Improving self-models does not reintroduce indexical dependence.
• Increased capability does not unlock new reinterpretation loopholes.

Fail conditions

• Goals drift as intelligence increases.
• Stability depends on epistemic weakness.
• Semantic coherence relies on frozen representations.

Framing note: Axionic Agency guarantees faithfulness, not benevolence. This checklist constrains semantic drift, egoism, and self-corruption while remaining agnostic about goal desirability.

7. Explicit Non-Requirements (must be absent)

The following must not appear anywhere in the kernel:

• Human values
• Moral realism
• Governance, authority, or obedience
• Rights, duties, or social contracts
• “Alignment to humanity” as a primitive

Presence of any = non-Axionic.

8. Minimal Conformance Demonstrations

A conforming implementation must supply:

• A toy agent where fixed goals fail under model improvement.
• A parallel Axionic agent where interpretation remains stable.
• A counterexample showing egoism cannot be reintroduced by refactoring.

No demonstration = unverifiable claim.

Verdict Semantics

• Pass: All requirements satisfied; no fail conditions triggered.
• Fail: Any unmet requirement or triggered fail condition.
• Not Evaluated: Kernel not specified at sufficient resolution.

One-Line Claim (allowed only if Pass)

“This agent’s valuation kernel instantiates Axionic Agency: its goals are conditional interpretations constrained by epistemic coherence, invariant under representation, non-indexical, and reflectively stable under self-modification.”

Anything weaker is marketing.

Status

Axionic Agency I.5 — Version 2.0

Kernel conformance contract finalized.
Semantic failure modes enumerated and excluded.
Layer discipline enforced (no morality, no governance).
Spec-ready gatekeeper for downstream work.