Disability data futures: Achievable imaginaries for AI and disability data justice

• URL: http://arxiv.org/abs/2411.03885v1
• Date: Wed, 06 Nov 2024 13:04:29 GMT
• Title: Disability data futures: Achievable imaginaries for AI and disability data justice
• Authors: Denis Newman-Griffis, Bonnielin Swenor, Rupa Valdez, Gillian Mason,
• Abstract summary: Data are the medium through which individuals' identities are filtered in contemporary states and systems. The history of data and AI is often one of disability exclusion, oppression, and the reduction of disabled experience. This chapter brings together four academics and disability advocates to describe achievable imaginaries for artificial intelligence and disability data justice.
• Score: 2.0549239024359762
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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