The terms of inclusion/exclusion of disability in big data are ultimately connected to the kinds of discourses that inform disability in society. Since the rise of big data as a phenomenon, disability’s absence in it, especially in the data formations that underpin artificial intelligence and machine learning, is notable. However, nowhere are data sets and disability more connected than in disability censuses—underscored by the efforts of the Washington Group on Disability Statistics to create internationally comparable disability statistics. The divergence is clear: Why is international cooperation to incorporate disability in data collection gaining speed, yet disability bias and discrimination still pervade traditional and new kinds of data? In this article, we bring critical disability studies in conversation with critical data studies to consider how disability is valued in big data. We argue the importance of adopting a disability data justice approach to crip the normative structures that underpin disability data and to ensure that disabled people control and govern the data collected about them.
Zhuang et al. (Tue,) studied this question.