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Leading AI at Work: Governance, Rollout and Practice / Unit 3   LAI 066 review, 2 to 3 minutes

A Drafting Assistant for Notices

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The idea

A worked example, constructed for this course, takes one AI feature through the book's checklist: an assistant that drafts benefit notices.

In practice

A benefits agency wants an assistant that drafts the notice sent after each eligibility decision. The team leader, Ruth, starts with the purpose: the feature is for speed and consistency in plain-language notices. She writes what it is not for: deciding eligibility, or changing the wording of legal phrases. The feature reads the Eligibility Determination and an approved notice template, and it writes a draft Notice. Both the Determination and the Notice are Gold. The Determination's Pack is current; the Notice's Pack is a year old and lacks the newer appeal deadline, so updating it becomes part of the feature. In the Determination's matrix, AI already appears once, as a risk-scoring model; the drafting assistant is added as a second row, with its tests and its review step. The prompts give the tool the Determination's fields and the template, and forbid it to add or reword legal text. Ruth records the decision: the feature suggests, and a caseworker approves every notice before it is sent. For oversight, a senior caseworker checks every draft in the first month and records each correction, the team watches for drafts that soften a denial's reason, and the rollback is a switch that returns caseworkers to the template alone. Running the safety checklist, every answer is yes except one: there are no tests yet for the AI's behavior. Ruth writes three test scenarios from the notice card before launch.

Where people slip

The checklist found two gaps, the stale Notice Pack and the missing tests, and both were fixed before launch rather than discovered after it. Neither gap was about the AI model itself. Both were about the things the feature touched, which is where the book says AI risk actually lives.

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