Case Study: AI in Social Systems – Impact and Implementation

Artificial intelligence is increasingly embedded in public services where decisions implicate rights, benefits, and burdens. This article proposes a practical lifecycle for responsible public‑sector AI spanning procurement, pilot, monitoring, and redress, with ethical checkpoints and governance artifacts at each phase. Using concrete examples and visuals, we distill lessons from applications such as predictive policing, welfare eligibility, and school placement. We define metrics that go beyond accuracy to include equity, participation, service quality, trust, and cost‑benefit, and we outline implementation guidance aligned to Technology in Society criteria. We conclude with recommendations for dignified, accountable digital public services.