  Datasets sourced from people with disabilities and older adults play an
important role in innovation, benchmarking, and mitigating bias for both
assistive and inclusive AI-infused applications. However, they are scarce. We
conduct a systematic review of 137 accessibility datasets manually located
across different disciplines over the last 35 years. Our analysis highlights
how researchers navigate tensions between benefits and risks in data collection
and sharing. We uncover patterns in data collection purpose, terminology,
sample size, data types, and data sharing practices across communities of
focus. We conclude by critically reflecting on challenges and opportunities
related to locating and sharing accessibility datasets calling for technical,
legal, and institutional privacy frameworks that are more attuned to concerns
from these communities.
