{
 "@context": "https://schema.org",
 "@type": "DefinedTerm",
 "@id": "https://wulfkaal.github.io/entities/discrimination",
 "identifier": "kaal:entity:discrimination",
 "name": "Discrimination",
 "termCode": "discrimination",
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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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   "value": 7
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   "value": [
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 "subjectOf": [
  {
   "@type": "Claim",
   "@id": "https://wulfkaal.github.io/claims/3071378-013",
   "identifier": "kaal:claim:3071378-013",
   "text": "Because of societal perceptions of minorities, minority groups face an uphill battle navigating the political environment of corporate America, which in turn significantly affects their positioning and success there.",
   "abstract": "societal perceptions of minorities,59 minority groups face an uphill battle in navigating the political environment in corporate America, which in turn can significantly affect their positioning and success in corporate America.",
   "citation": "Wulf A. Kaal, Blockchain Technology and Race in Corporate America (2017). SSRN: https://ssrn.com/abstract=3071378",
   "datePublished": "2017",
   "claim_type": "mechanism",
   "confidence": "argued",
   "is_failure_mode": false,
   "scope_conditions": [
    "corporate environments where promotion depends on political navigation"
   ],
   "source_pdf_sha256": "125f01674d13b6bb0310c4be7a20ff538dccbc36ecf352770b3c580028387edd",
   "status": "current"
  },
  {
   "@type": "Claim",
   "@id": "https://wulfkaal.github.io/claims/3071378-033",
   "identifier": "kaal:claim:3071378-033",
   "text": "People who work for a DAO are free from existing corporate hierarchies and their possible discriminatory effects because they are not subject to a supervisor, boss, or CEO.",
   "abstract": "People who work for a DAO are free from existing corporate hierarchies and their possible discriminatory effects. People who work for a DAO would not be subject to a supervisor, boss, or CEO.",
   "citation": "Wulf A. Kaal, Blockchain Technology and Race in Corporate America (2017). SSRN: https://ssrn.com/abstract=3071378",
   "datePublished": "2017",
   "claim_type": "mechanism",
   "confidence": "argued",
   "is_failure_mode": false,
   "scope_conditions": [
    "DAO structures with no directors, managers, or employees"
   ],
   "source_pdf_sha256": "125f01674d13b6bb0310c4be7a20ff538dccbc36ecf352770b3c580028387edd",
   "status": "current"
  },
  {
   "@type": "Claim",
   "@id": "https://wulfkaal.github.io/claims/3709041-021",
   "identifier": "kaal:claim:3709041-021",
   "text": "Majority rule in a microdemocracy can produce discrimination, because a majority that is itself unaffected by a rule it enacts can impose a disproportionate burden on the minority the rule does affect.",
   "abstract": "Similarly, majority rule may mean discrimination of the minority. A majority that is unaffected by a rule they instantiate may have a discriminatory impact on a minority that is disproportionately affected by the change in the rules.",
   "citation": "Kaal, Blockchain Technology for Good (2020). SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3709041",
   "datePublished": "2020",
   "claim_type": "failure",
   "confidence": "argued",
   "is_failure_mode": true,
   "scope_conditions": [
    "applies to majority rule voting in microdemocratic systems"
   ],
   "source_pdf_sha256": "5216a7bca45a48e3bef11ec524936e66af737c0fd66271e9f6866dc20a4482cc",
   "status": "current"
  },
  {
   "@type": "Claim",
   "@id": "https://wulfkaal.github.io/claims/3782198-035",
   "identifier": "kaal:claim:3782198-035",
   "text": "Anonymity can exacerbate second and third order discrimination because it makes such discrimination more difficult to detect, so other governance mechanisms in a decentralized organization must be used to combat it.",
   "abstract": "In fact, anonymity can exacerbate )nd and Grd-order effects, as it makes it more difficult to detect. To combat such effects, different mechanisms in the governance of a decentralized organization must be employed.",
   "citation": "Craig Calcaterra, Wulf A. Kaal, Contemporary Decentralization (2021). SSRN: https://ssrn.com/abstract=3782198",
   "datePublished": "2021",
   "claim_type": "failure",
   "confidence": "argued",
   "is_failure_mode": true,
   "scope_conditions": [
    "applies where members infer protected characteristics from behavior, and to systemic discrimination"
   ],
   "source_pdf_sha256": "e7e1378e3eed06cace6534e7792a7307d607d18bc6beb4ac45896476280728e4",
   "status": "current"
  },
  {
   "@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",
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  {
   "@type": "Claim",
   "@id": "https://wulfkaal.github.io/claims/4855607-003",
   "identifier": "kaal:claim:4855607-003",
   "text": "Deep learning models inadvertently learn and amplify whatever biases exist in their training data, so the composition of the training corpus, not the architecture, is the source of unfair or discriminatory outcomes.",
   "abstract": "Depending on the data used for training, deep learning models can inadvertently learn and amplify biases present in the training data, potentially leading to unfair or discriminatory outcomes.",
   "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": [
    "depends on the data used for training"
   ],
   "source_pdf_sha256": "eb0b3e62374b45a8fa888c6bde9725e606bcb46cf4b5e74a6e851d9f25099113",
   "status": "current"
  },
  {
   "@type": "Claim",
   "@id": "https://wulfkaal.github.io/claims/4941807-015",
   "identifier": "kaal:claim:4941807-015",
   "text": "A critical unsolved challenge for AI governance is bias mitigation, because biases enter inadvertently when algorithms incorporate discriminatory practices carried in the data used for training.",
   "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 Via Web3 Reputation System (2024). SSRN: https://ssrn.com/abstract=4941807",
   "datePublished": "2024",
   "claim_type": "failure",
   "confidence": "evidenced",
   "is_failure_mode": true,
   "scope_conditions": [
    "where training data embeds discriminatory practices"
   ],
   "source_pdf_sha256": "ab66c1e99a88da1fa36b0c6b536df5184231fe6aa427f3dd53287a4e0ac79853",
   "status": "current"
  }
 ],
 "description": "7 claims in the published works of Wulf A. Kaal carry the concept tag 'discrimination'. Derived node: a roster, not an adjudicated definition."
}