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  "name": "Wulf A. Kaal",
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   "@type": "Claim",
   "@id": "https://wulfkaal.github.io/claims/4796714-007",
   "identifier": "kaal:claim:4796714-007",
   "text": "The black box character of deep learning models is a governance failure and not merely a technical inconvenience: opacity obstructs debugging, obscures bias detection and mitigation, and prevents comprehension of how inputs become outputs.",
   "abstract": "This opacity can obstruct the debugging process, obscure bias detection and mitigation, and hinder comprehension of AI decision-making.",
   "citation": "Wulf A. Kaal, AI Governance (2024). SSRN: https://ssrn.com/abstract=4796714",
   "datePublished": "2024",
   "claim_type": "failure",
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   "is_failure_mode": true,
   "scope_conditions": [
    "most pronounced in deep learning models",
    "matters where decisions must be explained or audited"
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   "@type": "Claim",
   "@id": "https://wulfkaal.github.io/claims/4941807-008",
   "identifier": "kaal:claim:4941807-008",
   "text": "The opacity of deep learning models obstructs debugging, obscures the detection and mitigation of bias, and prevents comprehension of how AI decisions are reached.",
   "abstract": "This opacity can obstruct the debugging process, obscure bias detection and mitigation, and hinder comprehension of AI decision-making.",
   "citation": "Wulf A. Kaal, AI Governance Via Web3 Reputation System (2024). SSRN: https://ssrn.com/abstract=4941807",
   "datePublished": "2024",
   "claim_type": "failure",
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   "text": "Concrete cases show the cost of AI opacity: Nvidia self driving cars that learn from human behavior might confuse the moon for a traffic light, and the DeepPatient project predicted disease onset accurately from medical records while offering no explanation for its predictions.",
   "abstract": "For example, Nvidia's self-driving cars learn from human behavior but might confuse the moon for a traffic light, and the DeepPatient project accurately predicted disease onset from medical records without providing explanations for its predictions",
   "citation": "Wulf A. Kaal, AI Governance Via Web3 Reputation System (2024). SSRN: https://ssrn.com/abstract=4941807",
   "datePublished": "2024",
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   "@id": "https://wulfkaal.github.io/claims/4941807-016",
   "identifier": "kaal:claim:4941807-016",
   "text": "Legal and ethical challenges intensify when AI is deployed in critical decision making roles that significantly affect human lives and the reasoning behind the AI decision is opaque.",
   "abstract": "Legal and ethical challenges are heightened when AI is deployed in critical decision-making roles that significantly impact human lives, particularly when the reasoning behind AI's decisions is opaque.",
   "citation": "Wulf A. Kaal, AI Governance Via Web3 Reputation System (2024). SSRN: https://ssrn.com/abstract=4941807",
   "datePublished": "2024",
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    "in determinative decisions such as parole eligibility, employment, and medical strategy",
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   "@id": "https://wulfkaal.github.io/claims/5541658-003",
   "identifier": "kaal:claim:5541658-003",
   "text": "The distinctive strength of case-based reasoning systems, exemplified by HYPO, is that they model legal argumentation in a detailed and realistic manner rather than merely producing an outcome.",
   "abstract": "A clear strength of the HYPO program was to model legal argumentation in a detailed and realistic manner. This reflects the strength of case-based reasoning systems.",
   "citation": "Wulf A. Kaal, Morgan A. Gray, The Evolving Role of Artificial Intelligence in Law (2025). SSRN: https://ssrn.com/abstract=5541658",
   "datePublished": "2025",
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   "confidence": "argued",
   "is_failure_mode": false,
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    "case-based reasoning systems that compare a problem case with precedent cases"
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   "@id": "https://wulfkaal.github.io/claims/5541658-011",
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   "text": "Accuracy alone is insufficient for legal AI: a model must also be explainable before its outputs can be trusted in judicial settings.",
   "abstract": "Accuracy alone is insufficient without explainability.",
   "citation": "Wulf A. Kaal, Morgan A. Gray, The Evolving Role of Artificial Intelligence in Law (2025). SSRN: https://ssrn.com/abstract=5541658",
   "datePublished": "2025",
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 "description": "6 claims in the published works of Wulf A. Kaal carry the concept tag 'explainability'. Derived node: a roster, not an adjudicated definition."
}