Give the Caseworker a Map, Not a Score
Decision-support tools should show caseworkers evidence, provenance, gaps, uncertainty and lawful options—not compress a person into a recommendation score.
Human-centred technology—from everyday life to deep engineering.
Decision-support tools should show caseworkers evidence, provenance, gaps, uncertainty and lawful options—not compress a person into a recommendation score.
AI can assist judicial preparation, but a judge must still verify the record and law, resist anchoring, protect confidentiality and own every material reason.
Remote hearings can widen access, but cases involving liberty, family life, confidential advice, coercion or vulnerable participation may still require a physical courtroom.
Automated court transcripts can improve speed and access, but only certification, traceable corrections and human responsibility can turn probabilistic text into an authoritative record.
Legal self-help succeeds only when it transfers consented context and deadlines to the right human professional—not when it merely generates a form or referral link.
Machine translation can widen access to courts, but testimony, consent and authoritative legal texts still need accountable human interpretation and a clear path to correction.
Guided legal forms can make justice easier to enter, but they must recognise uncertainty, urgency and vulnerability—and know when to transfer control to a person.
Private vendors can strengthen public digital services, but rights-critical infrastructure must remain understandable, auditable, operable and genuinely replaceable.
Automation saves little if one wrong decision forces a person through an opaque maze. Build notification, evidence, tracking and human review as one usable appeal journey.
Government data control requires more than a dashboard. It must reveal sources, access and decisions, then carry corrections and appeals through every affected service.