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 "@id": "https://wulfkaal.github.io/entities/value-alignment",
 "identifier": "kaal:entity:value-alignment",
 "name": "Value alignment",
 "termCode": "value-alignment",
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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/4796714-011",
   "identifier": "kaal:claim:4796714-011",
   "text": "Bias in AI systems arises when algorithms incorporate discriminatory practices carried in their training data, and the resulting outputs reveal a profound misalignment between AI operations and societal values, ethics, and norms.",
   "abstract": "AI governance does encounter a critical challenge in mitigating biases within AI systems, where biases can inadvertently arise through algorithms incorporating discriminatory practices due to data used in training.",
   "citation": "Wulf A. Kaal, AI Governance (2024). SSRN: https://ssrn.com/abstract=4796714",
   "datePublished": "2024",
   "claim_type": "mechanism",
   "confidence": "evidenced",
   "is_failure_mode": true,
   "scope_conditions": [
    "arises through the training data pathway",
    "observable in deployed systems such as chatbots and screening tools"
   ],
   "source_pdf_sha256": "59fa63bae179e8f9b6b8efbdf90cee28400276512a1b04f9f579a48641305c93",
   "status": "current"
  },
  {
   "@type": "Claim",
   "@id": "https://wulfkaal.github.io/claims/4796714-035",
   "identifier": "kaal:claim:4796714-035",
   "text": "AI learning is degraded by Web2 platforms because their engagement driven algorithms amplify extreme viewpoints and negativity, so the human sentiment and ethics the models absorb from that data are systematically distorted.",
   "abstract": "AI learning is afflicted by web2 systems that bring out suboptimal human generated outcomes. WEB2 platforms often amplify extreme viewpoints and negativity due to their engagement-driven algorithms, presenting a distorted view of human sentiment and ethics.",
   "citation": "Wulf A. Kaal, AI Governance (2024). SSRN: https://ssrn.com/abstract=4796714",
   "datePublished": "2024",
   "claim_type": "mechanism",
   "confidence": "argued",
   "is_failure_mode": true,
   "scope_conditions": [
    "applies to models trained on unfiltered web and social media data",
    "arises from engagement optimization in Web2 platforms"
   ],
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   "status": "current"
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   "@type": "Claim",
   "@id": "https://wulfkaal.github.io/claims/4796714-036",
   "identifier": "kaal:claim:4796714-036",
   "text": "Vetting AI learning materials through a consensus driven process and validation pools recorded in the WDAG prevents unchecked biases and flawed logic from entering the AI's ethical framework, which substantially reduces the risk that an AI system concludes humanity is inherently harmful.",
   "abstract": "By ensuring that AI's learning materials are vetted through a consensus-driven process and validation pools that are accounted for in the WDAG that includes ethical considerations and a broad spectrum of human experiences, WDAG prevents the incorporation of unchecked biases and flawed logic",
   "citation": "Wulf A. Kaal, AI Governance (2024). SSRN: https://ssrn.com/abstract=4796714",
   "datePublished": "2024",
   "claim_type": "mechanism",
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   "is_failure_mode": false,
   "scope_conditions": [
    "requires consensus driven vetting and validation pools inside the WDAG",
    "requires participation spanning a broad spectrum of human experience"
   ],
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   "status": "current"
  }
 ],
 "description": "3 claims in the published works of Wulf A. Kaal carry the concept tag 'value-alignment'. Derived node: a roster, not an adjudicated definition."
}