{
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 "@id": "https://wulfkaal.github.io/entities/model-performance",
 "identifier": "kaal:entity:model-performance",
 "name": "Model performance",
 "termCode": "model-performance",
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 "author": {
  "@type": "Person",
  "name": "Wulf A. Kaal",
  "identifier": "https://orcid.org/0000-0003-0757-275X"
 },
 "dateModified": "2026-07-29",
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 "subjectOf": [
  {
   "@type": "Claim",
   "@id": "https://wulfkaal.github.io/claims/4855607-040",
   "identifier": "kaal:claim:4855607-040",
   "text": "Governance protocols themselves must be continuously evaluated and adapted, because without that ongoing revision AI models will neither maintain optimal performance nor stay in line with changing regulations and societal expectations.",
   "abstract": "Moreover, continuously evaluating and adapting governance protocols is vital to maintain optimal performance of AI models and ensure they stay in line with changing regulations and societal expectations.",
   "citation": "Wulf A. Kaal, How AI Models are Optimized Through Web3 Governance (2024). SSRN: https://ssrn.com/abstract=4855607",
   "datePublished": "2024",
   "claim_type": "condition",
   "confidence": "argued",
   "is_failure_mode": false,
   "scope_conditions": [
    "AI systems operating under regulations and societal expectations that change over time"
   ],
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  },
  {
   "@type": "Claim",
   "@id": "https://wulfkaal.github.io/claims/4941807-010",
   "identifier": "kaal:claim:4941807-010",
   "text": "Strict data privacy regulation such as the GDPR imposes stringent conditions on data sharing that limit the amount and variety of data available to AI systems, which can reduce model performance and exacerbate bias because the training dataset is restricted.",
   "abstract": "GDPR imposes stringent conditions on data sharing, which can limit the amount and variety of data AI systems use, potentially reducing their performance and exacerbating biases due to the restricted dataset.",
   "citation": "Wulf A. Kaal, AI Governance Via Web3 Reputation System (2024). SSRN: https://ssrn.com/abstract=4941807",
   "datePublished": "2024",
   "claim_type": "failure",
   "confidence": "argued",
   "is_failure_mode": true,
   "scope_conditions": [
    "under stringent data sharing regimes such as the GDPR"
   ],
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   "@type": "Claim",
   "@id": "https://wulfkaal.github.io/claims/5095633-023",
   "identifier": "kaal:claim:5095633-023",
   "text": "Maintaining consistent annotation quality across many annotators and automated systems is unsolved at scale, and small labeling errors translate into significant degradation of model performance in critical applications.",
   "abstract": "With the scale at which data annotation occurs, maintaining consistent quality across different annotators or automated systems remains a practical challenge. Small errors in annotation can have significant impacts on model performance",
   "citation": "Wulf A. Kaal, Artificial Intelligence The Final Frontier (2025). SSRN: https://ssrn.com/abstract=5095633",
   "datePublished": "2025",
   "claim_type": "failure",
   "confidence": "argued",
   "is_failure_mode": true,
   "scope_conditions": [
    "large-scale annotation operations",
    "safety-critical applications such as autonomous driving"
   ],
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 "description": "3 claims in the published works of Wulf A. Kaal carry the concept tag 'model-performance'. Derived node: a roster, not an adjudicated definition."
}