Government
Eligibility · casework · public accountability

Every eligibility decision a citizen can appeal — and you can reconstruct

When public-sector AI helps decide who gets a benefit, it is high-risk by classification. KLA holds the determination for caseworker review and seals the lineage an ombudsman, inspector, or appeals tribunal will demand — without forcing the agency into a full technology reset.

01The accountability gap

When AI quietly sets a citizen outcome, the agency owns the consequence

Oversight teams do not need another slide about responsible AI. They need a concrete way to stop, review, and replay the decisions that actually affect a person — before the complaint, not after.

The failure mode that draws scrutiny

An eligibility or casework assistant moves from drafting a recommendation to effectively setting a citizen outcome — and the agency cannot reconstruct what evidence produced it, who reviewed it, or how a person would appeal. In the public sector that is not a bug report. It is an accountability and legitimacy problem.

What due process requires

  • Meaningful human oversight on the decision that changes a citizen outcome
  • A reconstructable basis: what evidence and context produced the recommendation
  • A real appeal path: the person can see, understand, and challenge the decision

Three citizen-facing actions KLA holds before they commit

Eligibility determinations

Recommend, but cannot finalise a benefit decision without a caseworker.

Citizen notices

Draft, but cannot send correspondence or a notice without oversight.

Records disclosure

Cannot release or redact records (FOIA/SAR) without a defensible basis.

02From decision to appeal trail

The four steps that turn an AI decision into a record a citizen can challenge

The EU AI Act lists AI that determines access to essential public services among its high-risk categories (Annex III), triggering obligations a responsible-AI statement does not satisfy: meaningful human oversight, record-keeping, and transparency. KLA turns each into a runtime control point.

  1. 01 · Classify

    High-risk by Annex III

    AI used to decide access to essential public services and benefits is high-risk. KLA marks the step so it cannot run the same path as low-stakes drafting.

  2. 02 · Hold

    Caseworker stays in control

    The eligibility recommendation, notice, or prioritisation is held for a named reviewer before it commits to a citizen.

  3. 03 · Seal

    Reviewable lineage

    Source context, reviewer, and final action are sealed into a record oversight bodies and inspectors can replay.

  4. 04 · Appeal

    A citizen can challenge it

    The same sealed record is the basis a person needs to understand the decision and exercise a right to appeal.

sealed · offline-verifiableIllustrative appeal trail, not a customer deployment — it shows how the record is a byproduct of execution, produced before a citizen complains rather than after.

Govern in place, without a rip-and-replace

KLA adds the control path to the public-sector systems you already run: it intercepts the consequential action, routes it to a named caseworker, and seals what an inspection actually asks for — the source evidence, the reviewer log, the disclosure-or-redaction basis, and retention that lets an ombudsman replay the case years later. The obligations of EU AI Act high-risk classification become runtime controls on the decisions that affect citizens, not a policy document filed away.

Government AI Runtime Controls | KLA Digital