Accountability & Audit
When an agent acts for a citizen, much of what it does happens out of sight. Government runs the other side of the same arrangement, applying automated steps to whole populations at once, with no person watching any single case. What an agent does in a person’s name therefore has to stay visible at two scales: the single interaction, and the automated process that runs across a whole population.
This surfaces new challenges: a citizen has to be able to find out what an agent did for them and get a wrong decision corrected, and an agency has to be able to catch a systemic error in its own automation, not just a single bad case.
When an agent acts in a citizen's name, responsibility for what it did becomes hard to fix: the citizen, the agency, and the agent's provider can each point elsewhere, while the record of what was actually done is thin or absent.
As agents handle more of each interaction, two conditions sharpen. A mistake can surface only after a decision has been acted on, when it is hardest to reverse, and a single fault in an automated process can repeat across an entire population before anyone detects it. For policymakers this leaves an accountability gap precisely where automation makes errors fastest to spread and slowest to see.
Make what an agent did in a citizen's name legible and accountable: reviewable by the citizen before it takes effect, and a trail that fixes responsibility after.
Give a clear path to challenge, reverse, or seek recourse when it goes wrong.
Catch and stop a systemic fault before it reaches population scale.
Keep a path open for people who can't read or check that record themselves, or who must rely on a trusted person to do it for them.