Public services that work for people and their agents.

Telling where a submission came from, and whether it states a view the user holds or one an agent generated. A fluent submission no longer proves a user wrote it, yet the agency still has to act on it.

Letting a user give an AI agent scoped, revocable authority an agency can check is genuine and current. Government's identity systems can prove who a person is, but not what they let an agent do for them.

Keeping what an AI agent did in a user's name visible and answerable, for one case and across a whole population. Mistakes tend to surface only after the damage is done, and one faulty process can repeat on everyone at once.

Helping a user judge how far to rely on a government AI agent, and giving the agency a basis to support that judgment. A user can wrongly refuse an agent that would help, or lean on one a serious case needs a human for.

Forms, queues, and deadlines rationed services for years by demanding effort no one designed in. AI agents strip that effort away, forcing a deliberate choice about which friction only excluded people and which metered need.

Reading the weight of opinion behind public submissions once agents file fluent, distinct-looking entries at scale. Volume and the look of variety can both be manufactured, so neither shows how widely a view is held.

Keeping every user able to reach a government outcome, from a consultation to a benefit, license, or appeal, as private agents come between them and government. Left alone, outcomes start to track who has the better agent.

Knowing a reliable civic tool from a confident-sounding wrong one, for users and the automated tools government runs itself. Building an authoritative-looking tool is nearly free; verifying it and standing behind it is not.

What changes when the AI model behind a service runs, or can be legally compelled, outside a user's own legal protection. It decides whose data law applies and who can reach the data, often without either side able to tell.