  Work integrating conversations around AI and Disability is vital and valued,
particularly when done through a lens of fairness. Yet at the same time,
analyzing the ethical implications of AI for disabled people solely through the
lens of a singular idea of "fairness" risks reinforcing existing power
dynamics, either through reinforcing the position of existing medical
gatekeepers, or promoting tools and techniques that benefit
otherwise-privileged disabled people while harming those who are rendered
outliers in multiple ways. In this paper we present two case studies from
within computer vision - a subdiscipline of AI focused on training algorithms
that can "see" - of technologies putatively intended to help disabled people
but, through failures to consider structural injustices in their design, are
likely to result in harms not addressed by a "fairness" framing of ethics.
Drawing on disability studies and critical data science, we call on researchers
into AI ethics and disability to move beyond simplistic notions of fairness,
and towards notions of justice.
