FOCUS
All too often, disability is seen by policymakers and providers as incompatible with good health. The omission of disabled people from the collective understanding of what it means to be healthy is compounded by the continued lack of high-quality data regarding disability. As algorithmic decision-making tools become more widespread, they risk encoding and amplifying systemic ableism and health disparities, particularly for multiply marginalized individuals. In his research, Ian seeks to explore how algorithmic decision-making impacts disabled people. His goal is to contribute to reimagining health and healthcare that recognizes disability as an identity and experience, rather than simply an outcome, and empowers disabled people as partners and experts in their care.
MORE ABOUT IAN
Ian’s interest in disability emerged from his experiences as an autistic person, which inform his goals and ways of working as a policy and services researcher. He aims to conduct participatory research that translates to real, meaningful change and authentically reflects disabled people’s needs, preferences, and right to self-determination.
DISSERTATION GRANT AWARDEE — FALL 2024
Examining the Impact of Algorithmic Decision-Making Tools on the Disability Community
The use of algorithmic decision-making (ADM) tools poses unique risks for people with disabilities, but few studies of algorithmic bias have focused specifically on disability. This three-paper dissertation uses a mixed methods approach to explore how disabled people conceptualize fairness in situations where algorithmic tools are adopted and analyze two different algorithmic tools and their impact on people with disabilities. Results from this study will contribute to the emerging literature on regulation of ADM tools, particularly within high-stakes contexts that disproportionately impact the disability community.
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