The NYU Center for Disability Studies is documenting the experiences of disabled and chronically ill people during the current COVID-19 pandemic. Disabled people, especially people of color and those living in nursing homes or other congregate housing, have been at greatest risk of infection and death from COVID-19. In building a publicly-accessible archive, we collaborate with community members to preserve memories, stories, artworks, and other materials in a range of accessible formats. We are also preserving conversations on social media, records of digital public meetings, and photographs of street art and actions that are otherwise ephemeral. Our goal is to chronicle not only vulnerabilities, but creative initiatives for survival under these new conditions that are structured by old inequalities.
We take disability to be a diverse category that encompasses neurodivergence, aging, illness, mental disability, injury, and addiction, and welcome participants who may not identify with the term “disabled.” We are interested in a similarly wide range of experiences related to the pandemic, not limited to those who have contracted the virus: experiences of quarantine, remote work and unemployment, caregiving, stigma, activism, and medical rationing. To our knowledge, this is the only archive of the COVID-19 pandemic of 2020 that focuses explicitly on experiences of disability.
AI systems are being rapidly integrated into core social domains, informing decisions about who gets resources and opportunity, and who doesn’t. These systems, often marketed as smarter, better, and more objective, have been shown repeatedly to produce biased and erroneous outputs. And while much AI bias research and reporting has focused on race and gender, there has been much less attention paid to AI bias and disability. On March 28, 2019, the AI Now Institute at NYU, the NYU Center for Disability Studies, and Microsoft convened disability scholars, AI developers, and computer science and human-computer interaction researchers to discuss the intersection of disability, bias, and AI, and to identify areas where more research and intervention are needed.