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  <titleInfo>
    <title>The Limits of Representation - What Disability Data Reveals About Regulating AI Bias</title>
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    <namePart>Duell-Piening, Philippa</namePart>
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    <publisher>Verfassungsblog</publisher>
    <dateIssued>2026-07-17</dateIssued>
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  <abstract displayLabel="Summary">Artificial Intelligence can produce biased outputs. In part, this is because unrepresentative data is used to train, validate and test AI. To remedy skewed datasets and train fairer AI, many call for more comprehensive and systematic data production and processing about diverse people’s bodies and lives, including disabled people. Yet this response rests on a number of assumptions. Drawing on disability data, I argue that we should be cautious about these assumptions when regulating AI.</abstract>
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  <note type="statement of responsibility">Duell-Piening, Philippa</note>
  <subject>
    <topic>Behindertenrecht</topic>
  </subject>
  <subject>
    <topic>Convention on the Rights of Persons with Disabilities</topic>
  </subject>
  <subject>
    <topic>Convention on the Rights of Persons with Disabilities. Fakultativprotokoll | Vereinte Nationen</topic>
  </subject>
  <subject>
    <topic>Data</topic>
  </subject>
  <subject>
    <topic>Data collection</topic>
  </subject>
  <subject>
    <topic>Disability</topic>
  </subject>
  <subject>
    <topic>Disability RIghts</topic>
  </subject>
  <subject>
    <topic>Discrimination</topic>
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  <subject>
    <topic>anti-discrimination</topic>
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  <subject>
    <topic>data protection</topic>
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    <topic>Behindertenrecht</topic>
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    <topic>Convention on the Rights of Persons with Disabilities. Fakultativprotokoll | Vereinte Nationen</topic>
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  <identifier type="doi">10.59704/4f41c03047a50851</identifier>
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