Disability data futures: Achievable imaginaries for AI and disability data justice
November 06, 2024 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Denis Newman-Griffis, Bonnielin Swenor, Rupa Valdez, Gillian Mason
arXiv ID
2411.03885
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.AI
Citations
1
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Data are the medium through which individuals' identities and experiences are filtered in contemporary states and systems, and AI is increasingly the layer mediating between people, data, and decisions. The history of data and AI is often one of disability exclusion, oppression, and the reduction of disabled experience; left unchallenged, the current proliferation of AI and data systems thus risks further automating ableism behind the veneer of algorithmic neutrality. However, exclusionary histories do not preclude inclusive futures, and disability-led visions can chart new paths for collective action to achieve futures founded in disability justice. This chapter brings together four academics and disability advocates working at the nexus of disability, data, and AI, to describe achievable imaginaries for artificial intelligence and disability data justice. Reflecting diverse contexts, disciplinary perspectives, and personal experiences, we draw out the shape, actors, and goals of imagined future systems where data and AI support movement towards disability justice.
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