RESPONSIBLE AI

Where AI assistants can help the public sector without creating a black box.

AI assistants are useful when they are limited, documented, connected to approved sources, and designed to support human decisions.

Proof

Useful artifacts

Examples of deliverables that can support a scoping, prototype, or pilot mandate.

Flow

Process map

Resident intake Internal validation Follow-up / decision
List

Procurement controls

Fixed scope Acceptance criteria Documentation
Proof

Public review

Bilingual WCAG Minimized data

Good use cases

Internal document search, case summarization, response preparation, request triage, classification support, and explanation of approved rules.

Use cases to govern

Sensitive decisions, eligibility, penalties, legal advice, or responses that could affect residents need clear human oversight.

Required guardrails

Approved sources, response boundaries, useful logging, escalation to a human, and testing against exception scenarios.

Starting deliverables

Use policy, limited prototype, risk register, test scenarios, source content, and acceptance criteria.

QUESTIONS

Frequently asked questions

Can an AI assistant be used in a municipal service?

Yes, especially to orient, summarize, or prepare work. Sensitive decisions should remain human and traceable.

Does AI need to connect to internal data?

Not always. Many prototypes can start with approved, non-sensitive content before broader integrations.

How do you reduce wrong answers?

Limit scope, cite sources, provide escalation, and test ambiguous scenarios.

Ready to scope a first mandate?

A short conversation is often enough to identify the right format: scoping note, prototype, pilot, or implementation mandate.