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

Fuente: arXiv
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Autores principales: Newman-Griffis, Denis, Swenor, Bonnielin, Valdez, Rupa, Mason, Gillian
Formato: Preprint
Publicado: 2024
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author Newman-Griffis, Denis
Swenor, Bonnielin
Valdez, Rupa
Mason, Gillian
author_facet Newman-Griffis, Denis
Swenor, Bonnielin
Valdez, Rupa
Mason, Gillian
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2411_03885
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Disability data futures: Achievable imaginaries for AI and disability data justice
Newman-Griffis, Denis
Swenor, Bonnielin
Valdez, Rupa
Mason, Gillian
Human-Computer Interaction
Artificial Intelligence
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.
title Disability data futures: Achievable imaginaries for AI and disability data justice
topic Human-Computer Interaction
Artificial Intelligence
url https://arxiv.org/abs/2411.03885