Practical Templates for Transparency: Notices and Registries for Municipal AI Systems

Why a well-made registry and notices are essential

Municipalities that use AI in citizen-facing services (benefit assessments, local regulations, customer service, document classification) must meet transparency and data protection obligations. The GDPR requires clear information and, where relevant, notification about automated decisions; the EU AI Act introduces additional transparency requirements for high-risk systems and user information. In addition, ENS RD 311/2022 conditions the security of records and their custody in public environments.

A standardized registry and clear notices make compliance, auditing and public trust much easier. Below are practical templates and steps to implement them without technical complexity.

What to include: minimum fields for a public registry of AI systems

Publishing a public registry (transparency portal or dedicated page) with an entry per system reduces regulatory risk and improves traceability. Recommended minimum fields:

• System identifier: internal name + version.
• Risk classification (under the EU AI Act): high risk / not high risk / information tool.
• Functional purpose: what the system does and its administrative objective.
• Legal basis for processing (applicable GDPR article or administrative rule).
• Input data: types of data used (e.g., municipal register, tax declarations, images) — without specific personal values.
• Data source: origin (municipal databases, open data, third parties).
• Expected outputs and decisions the system may automate.
• Human oversight mechanisms: responsible role and control point.
• Bias mitigation measures and tests performed.
• Review frequency and technical/organizational responsible with contact.
• Links to technical documentation (summaries) and to the notice to the data subject.

A one-line-per-field format makes publication and indexing easier.

Brief example (registry)

• System: "GrantEvaluator v2.1"
• Risk: High risk (decisions with legal effects)
• Purpose: Classify applications for pre-selection of cultural grants
• Data: ID number, address, amount requested, grant history
• Oversight: Grants Officer – mandatory human review before final decision
• Contact: [email protected]
• Review: quarterly

Notices to citizens: clear and required language

When an administrative decision is based wholly or partly on AI, the notice to the data subject should be brief, understandable and provide appeal routes. Practical template for notifications:

• Concise title: “Notice: use of automated system in this decision”
• Body (recommend a single paragraph):
  • What the system does (1–2 clear sentences).
  • Legal basis (reference to the call or rule).
  • Consequence for the person (e.g., "this tool has assigned an initial priority").
  • Right to request human intervention and to file an appeal.
  • Where to find more information (link to the registry) and contact for the person responsible.

Avoid technical jargon; assume the reader is not familiar with AI. Add a link to a page with an expanded explanation and FAQs.

Example notice

"In this decision an automated system was used to prioritize applications. The legal basis is set out in call X. If you would like a person to review the decision or to file an appeal, contact [office] or consult [link]."

Internal logs: what to record for audit and traceability

In addition to the public registry, a structured internal log is essential to enable technical and legal audits. Indispensable fields:

• Request identifier (hash or case number).
• Timestamp (UTC) of request and response.
• Model and artifacts version (weights/config).
• Referenced input data identifiers (IDs, not personal data in plain text).
• Result/score/label returned.
• Brief explanation / justification (e.g., summarized feature importance).
• Identifier of the human operator who validated or modified the decision.
• Reference to validation tests and to the public registry version.

Retention: define a minimum retention period for audits (e.g., 5 years for decisions with administrative effects) and anonymization policies where appropriate. Store logs with ENS controls (encryption, access control).

Practical implementation steps (minimum viable)

1. Quick map: inventory AI systems in use and classify risk (one day per area).
2. Registry template: adopt the fields above and publish a first version (two weeks).
3. Citizen notices: integrate standard text into electronic and paper notification processes.
4. Basic logging: instrument defined logs and ensure retention and ENS controls.
5. Legal review and communication: validate with legal counsel and publish a short guide for staff.
6. Maintenance: review after model changes or every 6–12 months.

Common risks and how to avoid them

• Notices that are too technical -> use user-friendly language.
• Recording sensitive data in logs -> reference by ID and encrypt.
• Not updating the registry after a model change -> include version in each entry.
• Lack of human oversight for high-impact decisions -> implement mandatory validation.

Conclusion and recommended actions

Takeaway: Publishing a simple public registry, notifying citizens with clear notices and keeping technical logs with versioning and human oversight are measures that comply with the GDPR and make it easier to meet the EU AI Act and ENS. Immediate actions:

• Today: do a quick inventory of AI systems.
• In 30 days: publish minimum registries and update notice templates.
• In 90 days: have logs instrumented and a legal review process in place.

If your municipality needs a package of templates and an operational checklist, tools like OptimGov include modules that speed up publishing registries and instrumenting logging in line with the ENS and European regulation. Always validate final texts with your legal advisor.