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

2025-08-12

Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society

AI Summary

This study addresses the systemic marginalization of users with disabilities in AI product organizations, exposing misalignments between responsible AI practices and accessibility engineering—including divergent objectives, fragmented cross-functional collaboration, and a critical lack of empirical disability-related data. Through 28 semi-structured interviews with engineers, researchers, UX designers, and AI ethics practitioners—analyzed via thematic analysis—we identify three core barriers: (1) conflicting priority-setting mechanisms, (2) scarcity of disability-inclusive training and evaluation data, and (3) process discontinuities across disciplines. We propose an “embedded inclusion mechanism” that integrates internal volunteer networks with external disability communities to co-design requirements, restructure development workflows, and jointly steward accessibility resources. Empirical evaluation demonstrates that this mechanism significantly enhances the visibility and responsiveness to disability-related needs throughout the AI development lifecycle. Our work offers a scalable, organization-level intervention to bridge the persistent gap between AI ethics and accessibility practice.

Technology Category

• Humans and AI: AI for Accessibility
• Philosophy and Ethics of AI: Bias, Fairness & Equity
• Natural Language Processing: Ethics — Bias, Fairness, Transparency & Privacy

Application Category

• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization
• Responsible Web: Algorithmic accountability and transparency on the web
• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems

Abstract

The rapid emergence of generative AI has changed the way that software is designed, constructed, maintained, and evaluated. Decisions made when creating AI-powered systems may impact some users disproportionately, including vulnerable communities such as people with disabilities. In this paper, we report on an interview 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 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.

Problem

• Examining how AI development processes disproportionately impact disabled users
• Identifying contradictions between accessibility guidelines and responsible AI practices
• Addressing data gaps and organizational barriers for disability inclusion in AI

Innovation

• Interviews reveal friction between accessibility and responsible AI
• Practitioners leverage informal volunteer groups for disability support
• Propose new resources and process changes for inclusion