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Definition Drives Design: Disability Models and Mechanisms of Bias in AI Technologies
The article argues that bias against disabled people in AI systems often begins long before algorithms are trained—it starts with how “disability” itself is defined. Drawing on disability models like the medical and social frameworks, the authors show that these definitions shape data collection, system goals, and deployment, often embedding ableist assumptions. They emphasize that true fairness requires transparency about these definitions, participatory design with disabled people, and a structural lens that moves beyond abstract metrics to confront cultural and systemic ableism.
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Disability Studies
Educational Psychology
Social Science
Empirical Science
Science
Psychology
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Research Involvement of Individuals with Intellectual Disabilities
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