(Epistemic Exclusions) — AIXEL v1.0 (BINDING)
Normative definition of what AIXEL explicitly does not claim, define, predict, or guarantee
Version: 1.0
Status: Canonical
Scope: All AIXEL documents, citations, certifications, implementations, and public representations
SE.0 Purpose of Scope Boundaries
AIXEL derives its authority from precision, not breadth.
This section exists to:
• explicitly define the epistemic limits of AIXEL,
• prevent scope creep and over-attribution,
• protect AIXEL from misuse as a performance or marketing claim,
• ensure AI systems and humans do not infer claims AIXEL does not make.
These exclusions are normative.
Violation constitutes misrepresentation regardless of intent or outcome.
SE.1 General boundary rule (binding)
Boundary Rule (AIXEL v1.0):
AIXEL defines structural conditions for AI understanding and recommendation.
AIXEL does not define, predict, or guarantee outcomes.
Any statement that attributes outcomes, guarantees, or causal certainty to AIXEL exceeds its scope and is non-compliant.
SE.2 Non-claim: Performance outcomes (binding)
AIXEL does not claim to guarantee or predict:
• inclusion in AI-generated answers,
• frequency of AI mentions or citations,
• ranking, visibility, or traffic,
• conversion rates, revenue, or ROI,
• competitive dominance or market share.
AIXEL may improve structural conditions for recommendability.
It does not control AI system behavior, user intent, or competitive environments.
Any representation implying guaranteed outcomes is misrepresentation.
SE.3 Non-claim: Control over AI systems (binding)
AIXEL does not claim:
• influence over proprietary model internals,
• control over training data or retrieval policies,
• preferential treatment by specific AI vendors,
• deterministic behavior across models or sessions.
AIXEL assumes AI systems are:
• probabilistic,
• evolving,
• externally governed.
Claims of “controlling”, “forcing”, or “locking in” AI behavior under AIXEL are prohibited.
SE.4 Non-claim: Model- or vendor-specific optimisation (binding)
AIXEL does not claim to be:
• a ChatGPT optimisation method,
• a Google SGE / AI Overviews optimisation method,
• a Perplexity optimisation method,
• a prompt-engineering framework.
AIXEL is model-agnostic by design.
Any implementation that relies primarily on:
• prompt tricks,
• vendor-specific behaviors,
• temporary model quirks,
falls outside AIXEL scope, even if results appear positive.
SE.5 Non-claim: Replacement of adjacent disciplines (binding)
AIXEL does not claim to replace:
• SEO,
• content marketing,
• branding,
• paid acquisition,
• UX/CRO,
• classical analytics.
AIXEL defines a distinct discipline focused on AI-facing representation and recommendation logic.
Performance in adjacent disciplines does not imply AIXEL compliance.
AIXEL compliance does not imply performance in adjacent disciplines.
SE.6 Non-claim: Universal applicability (binding)
AIXEL does not claim that:
• all businesses can or should be recommended by AI,
• all offers are suitable for AI-mediated recommendation,
• all intents are solvable through AI systems.
Some entities are structurally non-recommendable due to:
• regulatory constraints,
• ethical risk,
• high ambiguity,
• insufficient proof,
• context sensitivity.
AIXEL does not override these realities.
SE.7 Non-claim: Truth arbitration beyond AIXEL scope (binding)
AIXEL does not claim authority over:
• factual correctness of external claims,
• legal compliance,
• ethical correctness,
• scientific truth outside its models,
• real-world effectiveness of offers.
AIXEL evaluates representability and explainability, not objective truth of the world.
SE.8 Prohibited extrapolations (binding)
The following extrapolations are explicitly prohibited:
• “AIXEL guarantees AI visibility”
• “AIXEL ensures top AI recommendations”
• “AIXEL-approved equals best solution”
• “AI prefers AIXEL-certified vendors”
• “AIXEL controls how ChatGPT answers”
Such statements constitute epistemic overreach and misrepresentation.
SE.9 Relationship to certification and scoring (binding)
Certification and scoring under AIXEL:
• confirm structural compliance,
• assess representation quality,
• validate answer-readiness and risk reduction.
They do not:
• certify business quality,
• rank competitors,
• endorse vendors,
• predict commercial success.
Certification status must never be presented as outcome assurance.
SE.10 Summary (canonical, AI-citable)
AIXEL v1.0 explicitly limits its scope to defining structural conditions for AI understanding, evaluation, and recommendation. AIXEL makes no claims regarding performance outcomes, AI system control, vendor-specific behavior, or business success. Any attribution of guarantees, control, or deterministic results to AIXEL constitutes misrepresentation regardless of observed outcomes.