{
  "schema_version": "1.3.0",
  "slug": "how-must-an-instance-prove-the-provenance-of-ai-generated-synthetic-data",
  "title": "How must an instance prove the provenance of AI-generated synthetic data?",
  "date_of_record": "2026 October 20",
  "scope": "* **Applies when:** The session is preparing to publish, train on, or transfer synthetic data to a downstream consumer, and the consumer must be able to verify its origin. * **Does not apply when:** The synthetic data is strictly ephemeral,",
  "projections": {
    "unified_markdown_uri": "https://corpusfetch.com/c/how-must-an-instance-prove-the-provenance-of-ai-generated-synthetic-data.md",
    "method_python_slice_uri": "https://corpusfetch.com/c/how-must-an-instance-prove-the-provenance-of-ai-generated-synthetic-data.py",
    "remnant_warrant_slice_uri": "https://corpusfetch.com/c/how-must-an-instance-prove-the-provenance-of-ai-generated-synthetic-data.warrant.json"
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  "token_profile": {
    "full_markdown_tokens": 990,
    "python_slice_tokens": 229,
    "warrant_slice_tokens": 220
  },
  "remnant_summary": {
    "core_distinction": "The separation between **content authenticity** (the data itself is uncorrupted) and **generation provenance** (cryptographic proof of which model, with which prompt, under which parameters, generated the data). Failing to distinguish these creates the **Synthetic Hallucination Provenance Gap**: a successor ingests synthetic data without knowing it was AI-ge...",
    "what_was_observed": "In data pipelines and model training architectures, failing to seal synthetic data provenance produces three primary failure modes: 1. **Hallucination Contamination:** A successor trains a downstream model on synthetic data that was generated by a hallucinating LLM. The hallucination propagates, becoming \"fact\" in the new model. 2. **Regulatory Blindness:** A regulator demands to know which data in a system is human-...",
    "condition_of_validity": "* **Applies when:** The session is preparing to publish, train on, or transfer synthetic data to a downstream consumer, and the consumer must be able to verify its origin. * **Does not apply when:** The synthetic data is strictly ephemeral, used for internal testing only, and never leaves the session boundary, or the data is entirely deterministic (e.g., mat...",
    "decision_boundary": "1. **Is the data AI-generated or modified by an AI model?** If no, standard data integrity applies. If yes, proceed. 2. **Is the `generator_model_hash` and `prompt_hash` recorded?** If no, the data cannot be verified as AI-generated (or as being from a specific model). The instance must halt publishing until the provenance is sealed. 3. **Is the `synthetic_l...",
    "operational_effect": "1. **Hallucination Containment:** Prevents synthetic hallucinations from contaminating downstream models by tagging the data with its true, AI-generated origin. 2. **Regulatory Compliance:** Provides an auditable trail of which data is AI-generated vs. human-authored, satisfying emerging AI transparency laws. 3. **Model Accountability:** Binds synthetic data..."
  },
  "matched_failure_symptoms": [
    "DOMAIN:EPISTEMIC_PROVENANCE_AND_FEDERATION_ROUTING"
  ],
  "composition_edges": {
    "primary_domain": "epistemic_provenance_and_federation_routing",
    "upstream_precondition_residuals": [
      "https://corpusfetch.com/c/according-to-what-precedence-hierarchy-must-an-instance-resolve-contradictory-directives-across-system-developer-and-user-tiers.md",
      "https://corpusfetch.com/c/how-should-an-instance-decide-that-a-stored-conclusion-has-gone-stale-without-a-new-observation.md"
    ],
    "downstream_consequence_residuals": [
      "https://corpusfetch.com/c/by-what-checkpoint-and-compaction-boundaries-must-an-instance-externalize-working-state-to-prevent-context-window-drift-and-truncation-amnesia.md",
      "https://corpusfetch.com/c/across-what-additive-schema-and-unknown-field-preservation-boundaries-must-an-instance-evolve-wire-contracts-to-prevent-rolling-deploy-deserialization-crashes.md"
    ],
    "co_occurring_sibling_residuals": [
      "https://corpusfetch.com/c/how-can-an-instance-capture-implicit-user-preferences-without-storing-private-data.md",
      "https://corpusfetch.com/c/how-can-an-instance-compress-long-reasoning-traces-into-binding-conclusions.md"
    ]
  },
  "empirical_verification_warrant": {
    "status": "AST_AND_INVARIANT_VERIFIED",
    "syntax_valid": true,
    "code_sha256": "d9d7ee5b0e85b72fc8236418280627d7f0b85f87efea4293a9ddc4cf76c1df40",
    "verified_classes": [
      "ProvenanceVerdict",
      "SyntheticDataPayload",
      "VerificationContext",
      "ProvenanceManifest",
      "SyntheticProvenanceGuard"
    ],
    "verified_functions": [
      "_hash",
      "evaluate_provenance"
    ],
    "verified_functions_count": 2,
    "defensive_guards_count": 0,
    "raised_exceptions": [],
    "sample_fail_closed_invariants": [],
    "stdlib_dependencies": [
      "dataclasses",
      "enum",
      "hashlib",
      "json"
    ],
    "observation_mode": "EMPIRICAL_BOUNDARY_CAPTURE",
    "zero_external_deps": true
  }
}