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 "@type": "DefinedTerm",
 "@id": "https://wulfkaal.github.io/entities/distribution-shift",
 "identifier": "kaal:entity:distribution-shift",
 "name": "Distribution shift",
 "termCode": "distribution-shift",
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 "author": {
  "@type": "Person",
  "name": "Wulf A. Kaal",
  "identifier": "https://orcid.org/0000-0003-0757-275X"
 },
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   "@type": "Claim",
   "@id": "https://wulfkaal.github.io/claims/4855607-004",
   "identifier": "kaal:claim:4855607-004",
   "text": "Deep learning models adapt to changes in data distribution far less readily than human learning does, which limits their reliability once the operating environment diverges from the training data.",
   "abstract": "Furthermore, deep learning models are not as adaptable to changes in data distribution as human learning, which can adapt more quickly to new situations and contexts.",
   "citation": "Wulf A. Kaal, How AI Models are Optimized Through Web3 Governance (2024). SSRN: https://ssrn.com/abstract=4855607",
   "datePublished": "2024",
   "claim_type": "failure",
   "confidence": "evidenced",
   "is_failure_mode": true,
   "scope_conditions": [
    "settings where the data distribution shifts after training"
   ],
   "source_pdf_sha256": "eb0b3e62374b45a8fa888c6bde9725e606bcb46cf4b5e74a6e851d9f25099113",
   "status": "current"
  },
  {
   "@type": "Claim",
   "@id": "https://wulfkaal.github.io/claims/5095633-010",
   "identifier": "kaal:claim:5095633-010",
   "text": "When a training dataset disproportionately represents one region or demographic group, the resulting model produces skewed and sometimes inappropriate outputs once deployed in unfamiliar settings.",
   "abstract": "For instance, if a dataset disproportionately represents a particular region or demographic group, the model may offer skewed performance, demonstrating suboptimal or inappropriate outputs when deployed in unfamiliar settings.",
   "citation": "Wulf A. Kaal, Artificial Intelligence The Final Frontier (2025). SSRN: https://ssrn.com/abstract=5095633",
   "datePublished": "2025",
   "claim_type": "mechanism",
   "confidence": "argued",
   "is_failure_mode": true,
   "scope_conditions": [
    "deployment context differs from the demographic composition of the training data"
   ],
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 ],
 "description": "2 claims in the published works of Wulf A. Kaal carry the concept tag 'distribution-shift'. Derived node: a roster, not an adjudicated definition."
}