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"Accessibility people, you go work on that thing of yours over there": Addressing Disability Inclusion in AI Product Organizations

Sanika Moharana, Cynthia L. Bennett, Erin Buehler, Michael Madaio, Vinita Tibdewal, Shaun K. Kane

TL;DR

Generative AI introduces both opportunities and risks for people with disabilities, requiring systematic attention within AI product organizations. The authors conduct a 25-person, semi-structured interview study across roles to uncover how disability inclusion is addressed, revealing fragmentation across accessibility, safety, and product review processes, plus data and recruitment gaps. They identify practical barriers—resource constraints, organizational churn, lack of disability data, and unclear ownership of accessibility—along with strategies like informal gap filling, red-teaming, and leadership buy-in, and offer resources and process changes to embed disability inclusion in AI workflows. The work highlights the need for integrated education across UX, accessibility, and RAI, and for scalable, leadership-supported approaches to ensure disabled stakeholders are consistently represented in AI development and deployment.

Abstract

The rapid emergence of generative AI has changed the way that technology is designed, constructed, maintained, and evaluated. Decisions made when creating AI-powered systems may impact some users disproportionately, such as people with disabilities. In this paper, we report on an interview study with 25 AI practitioners across multiple roles (engineering, research, UX, and responsible AI) about how their work processes and artifacts may impact end users with disabilities. We found that practitioners experienced friction when triaging problems at the intersection of responsible AI and accessibility practices, navigated contradictions between accessibility and responsible AI guidelines, identified gaps in data about users with disabilities, and gathered support for addressing the needs of disabled stakeholders by leveraging informal volunteer and community groups within their company. Based on these findings, we offer suggestions for new resources and process changes to better support people with disabilities as end users of AI.

"Accessibility people, you go work on that thing of yours over there": Addressing Disability Inclusion in AI Product Organizations

TL;DR

Generative AI introduces both opportunities and risks for people with disabilities, requiring systematic attention within AI product organizations. The authors conduct a 25-person, semi-structured interview study across roles to uncover how disability inclusion is addressed, revealing fragmentation across accessibility, safety, and product review processes, plus data and recruitment gaps. They identify practical barriers—resource constraints, organizational churn, lack of disability data, and unclear ownership of accessibility—along with strategies like informal gap filling, red-teaming, and leadership buy-in, and offer resources and process changes to embed disability inclusion in AI workflows. The work highlights the need for integrated education across UX, accessibility, and RAI, and for scalable, leadership-supported approaches to ensure disabled stakeholders are consistently represented in AI development and deployment.

Abstract

The rapid emergence of generative AI has changed the way that technology is designed, constructed, maintained, and evaluated. Decisions made when creating AI-powered systems may impact some users disproportionately, such as people with disabilities. In this paper, we report on an interview study with 25 AI practitioners across multiple roles (engineering, research, UX, and responsible AI) about how their work processes and artifacts may impact end users with disabilities. We found that practitioners experienced friction when triaging problems at the intersection of responsible AI and accessibility practices, navigated contradictions between accessibility and responsible AI guidelines, identified gaps in data about users with disabilities, and gathered support for addressing the needs of disabled stakeholders by leveraging informal volunteer and community groups within their company. Based on these findings, we offer suggestions for new resources and process changes to better support people with disabilities as end users of AI.

Paper Structure

This paper contains 33 sections, 1 table.