Toward Fairness in AI for People with Disabilities: A Research Roadmap

TL;DR

This paper highlights the importance of fairness in AI systems for people with disabilities, identifying potential risks and proposing a research roadmap to develop more inclusive and equitable AI solutions.

Contribution

It provides a comprehensive overview of fairness concerns for AI affecting PWD and outlines a research agenda to address these issues.

Findings

AI can both assist and discriminate against PWD if not carefully designed

Current AI systems lack sufficient focus on disability-specific fairness considerations

A roadmap for future research is proposed to improve AI inclusivity for PWD

Abstract

AI technologies have the potential to dramatically impact the lives of people with disabilities (PWD). Indeed, improving the lives of PWD is a motivator for many state-of-the-art AI systems, such as automated speech recognition tools that can caption videos for people who are deaf and hard of hearing, or language prediction algorithms that can augment communication for people with speech or cognitive disabilities. However, widely deployed AI systems may not work properly for PWD, or worse, may actively discriminate against them. These considerations regarding fairness in AI for PWD have thus far received little attention. In this position paper, we identify potential areas of concern regarding how several AI technology categories may impact particular disability constituencies if care is not taken in their design, development, and testing. We intend for this risk assessment of how various classes of AI might interact with various classes of disability to provide a roadmap for future research that is needed to gather data, test these hypotheses, and build more inclusive algorithms.