{
 "@context": "https://schema.org",
 "@type": "DefinedTerm",
 "@id": "https://wulfkaal.github.io/entities/knowledge",
 "identifier": "kaal:entity:knowledge",
 "name": "Knowledge",
 "termCode": "knowledge",
 "inDefinedTermSet": {
  "@id": "https://wulfkaal.github.io/entities/index.json"
 },
 "author": {
  "@type": "Person",
  "name": "Wulf A. Kaal",
  "identifier": "https://orcid.org/0009-0008-7840-1847"
 },
 "canonicalForm": "https://wulfkaal.github.io/entities/knowledge.md",
 "sha256": "1677b89b2196539ab704fa08e8fd95c9e6b769563fb3e74e9f8c5d8428498b77",
 "additionalProperty": [
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   "name": "status",
   "value": "derived"
  },
  {
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   "name": "claim_count",
   "value": 2
  },
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   "name": "work_count",
   "value": 2
  },
  {
   "@type": "PropertyValue",
   "name": "year_span",
   "value": [
    "2021",
    "2026"
   ]
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  }
 ],
 "subjectOf": [
  {
   "@type": "Claim",
   "@id": "https://wulfkaal.github.io/claims/3808867-024",
   "identifier": "kaal:claim:3808867-024",
   "text": "A single powerful application such as Google already exercises substantial control over human knowledge and thought, and could control societal outcomes by making disparate recommendations to similarly situated users.",
   "abstract": "For example, a powerful application such as Google has already a lot of control over human knowledge and thought.",
   "citation": "Wulf A. Kaal, How Decentralized Systems Can Upgrade AI (2021). SSRN: https://ssrn.com/abstract=3808867",
   "datePublished": "2021",
   "claim_type": "failure",
   "confidence": "argued",
   "is_failure_mode": true,
   "scope_conditions": [
    "dominant internet based applications accumulating societal functions since the early 2010s"
   ],
   "source_pdf_sha256": "eeccf6d0587bd278a96ce6ac8ec5003e26d161c245f6c94b4144d84f374802eb",
   "status": "current"
  },
  {
   "@type": "Claim",
   "@id": "https://wulfkaal.github.io/claims/7598518-016",
   "identifier": "kaal:claim:7598518-016",
   "text": "Yi et al. (2026) report that an imperfect external verifier drives the model toward the verifier's own knowledge center.",
   "abstract": "Intelligence models increasingly learn from data that earlier Intelligence models produced, and when that loop repeats the rare cases disappear first. This paper preregisters a test of whether a reputation-weighted validator pool, filtering the training data of a recursive replacement loop, keeps those rare cases alive. The outcomes remain sealed until a replication of the original model-collapse result succeeds.",
   "citation": "Wulf A. Kaal, Can Reputation Prevent Model Collapse? A Preregistered Test of Reputation-Weighted Data Filtering (2026). SSRN: https://ssrn.com/abstract=7598518",
   "datePublished": "2026",
   "claim_type": "mechanism",
   "confidence": "reported",
   "is_failure_mode": true,
   "scope_conditions": [
    "The finding is prior work cited by the paper and is not measured in this study.",
    "It is a limit on verifier-based selection generally, including the pool under test."
   ],
   "source_pdf_sha256": "cd22d148b2b55c2e27f087dcaa61cdf44ad7022b400b355c31a9cd7e43a31749",
   "status": "current"
  }
 ],
 "description": "2 claims in the published works of Wulf A. Kaal carry the concept tag 'knowledge'. Derived node: a roster, not an adjudicated definition."
}