United Against Algorithms: A primer on disability-led struggles against algorithmic injustice

Governments are progressively integrating data-driven algorithmic systems into critical domains related to the health and welfare of people with disability. These applications encompass tasks such as detecting benefit fraud, assembling disability support plans, and determining eligibility for disability benefits and services. Algorithmic decision-making (ADM) poses urgent concerns regarding the rights and entitlements of people with disability from all walks of life. As ADM systems become increasingly embedded in government decision-making processes, there is a heightened risk of harm, such as unjust denial of benefits or inadequate support, accentuated by the expanding reach of state surveillance. Governments are progressively integrating data-driven algorithmic systems into critical domains related to the health and welfare of people with disability. These applications encompass tasks such as detecting benefit fraud, assembling disability support plans, and determining eligibility for disability benefits and services. Algorithmic decision-making (ADM) poses urgent concerns regarding the rights and entitlements of people with disability from all walks of life. As ADM systems become increasingly embedded in government decision-making processes, there is a heightened risk of harm, such as unjust denial of benefits or inadequate support, accentuated by the expanding reach of state surveillance. Co-published with the Data Justice Lab, Cardiff University.