Algorithmic Decision-Making

The use of software systems — from rule-based logic to machine learning models — to make or substantially inform decisions that affect individuals, such as eligibility for benefits, credit, housing, or employment. In public services, algorithmic decision-making is often deployed to triage, verify eligibility, or flag fraud, and has repeatedly produced serious harms to disabled and marginalised populations (for example, Australia's Robodebt, Michigan's MiDAS, and the Netherlands' SyRI). Key accessibility concerns include opacity, lack of human recourse, bias against atypical communicators, and the use of automation as a scapegoat for regressive policy choices.