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Helpful Places

Government of Canada – DTPR AI Register

AI-Assisted Code Completion for Government Developers

Employment & Work

What it collects

Operational data
Anonymized data
  • Internal government code — source files, scripts, and related artefacts from GC developer workspaces — is used as the runtime input from which Copilot generates suggestions. The register states no personal information is involved.
Run by
Canada School of Public Service (CSPS)
Where
No fixed location
Kept
Not stated by the Helpful Places.
Shared with
Accountable organization
Your copy
You cannot see the data it holds about you. What you can do

What it is for

Employment & Work

GitHub Copilot is an AI coding assistant deployed by the Canada School of Public Service to help Government of Canada software developers write code faster and more accurately. It suggests code completions, generates functions, and proposes refactoring in real time inside developer tools like Visual Studio Code. The system works with internal code and is used only by GC employees; users are informed that AI is in use. The system is currently in development and does not process personal information.

What it collects and what happens to it

Data taken in

Operational data
Anonymized data
  • Internal government code — source files, scripts, and related artefacts from GC developer workspaces — is used as the runtime input from which Copilot generates suggestions. The register states no personal information is involved.

Processing

Language Models
  • GitHub Copilot uses OpenAI Codex, a large language model specialized for code, to predict and generate syntactically and semantically appropriate code tokens in context.

What it does

Creating (Generative AI)
Human decides
  • GitHub Copilot generates code completions, full functions, and refactored code suggestions in real time. Developers review and accept or reject each suggestion — the AI proposes, the human decides whether to use the output.
Understanding (Semantic AI)
Human decides
  • The system understands the intent of the developer's current code context — reading the surrounding code, comments, and file structure — to produce contextually relevant suggestions.

Outputs

Generated content
Anonymized data
  • The system outputs generated source code — completions, new functions, and refactored blocks — displayed inline in the developer's IDE for review. No personal information appears in the output.

Run by

Canada School of Public Service (CSPS)
  • The Canada School of Public Service is the federal institution that deployed GitHub Copilot to support GC software developers.

Canada AI Register — 2526-CSPS-EFPC-020

Built by

Microsoft
  • Microsoft supplies GitHub Copilot, which is powered by OpenAI Codex. Microsoft is identified as the vendor responsible for building and licensing the underlying AI system.

Canada AI Register — 2526-CSPS-EFPC-020

Kept for

Not stated by the Helpful Places.

Shared with

Available to the accountable organization
  • Output suggestions and usage are visible to GC employee developers using the tool within their IDE. The Canada School of Public Service, as the deploying institution, has administrative access to the deployment.
Not available to me
  • As a member of the general public, you do not have access to the code suggestions or usage logs produced by this system, as it operates exclusively within internal GC developer environments.

Stored

Not stated by the Helpful Places.

How to read the colours

Can it identify you?

Anonymized data
Data about people with the link to who is broken. Stripped of identifiers, blurred, aggregated, or noised so this system can’t reasonably tie a record back to an individual.
Pseudonymous data
Each person’s data is tied to a token (hash, ID, template) that lets this system recognise the same person across events, but the token itself doesn’t reveal a name. Reidentification is possible with extra information.
Identifiable data
The data either contains a direct identifier (name, address, account name, recognisable face or voice, plate number) or carries a token this system uses to look up legal identity during processing.

Who completes the loop?

Human decides
This mode suggests; a person decides what to do next. The AI is always advisory — a human is in the loop on every decision. Example: a triage tool ranks cases for a clinician who chooses which to see first.
Human executes
This mode decides; a person carries out the result. Example: an optimizer plans the day’s trash-collection routes, and drivers run them.
Autonomous
This mode decides and acts on its own. No person reviews each decision or carries out the resulting action.

Definitions from the DTPR standard. Amber is about your data, violet about who decides. The fuller the shape and the deeper the colour, the more identifying the data or the less a person is involved.

What you can do

Ask about this system

Questions go to the Helpful Places, not the vendor.

Your rights

  • Right to Be Informed of AI UseUsers are informed that AI is in use. The register confirms AI use is disclosed to users (AI use disclosed to users: Y).
  • Right to Algorithmic TransparencyGC employees using this system are entitled to understand in plain language how GitHub Copilot generates suggestions and what data it uses. Contact the Canada School of Public Service for further information.

Risks and safeguards

  • Reputational harmCopilot may suggest code containing errors, security vulnerabilities, or inadvertent reproduction of third-party intellectual property, which could harm the reputation of government software products.Safeguard: Suggestions are advisory only — developers review and must explicitly accept each suggestion. The system is currently in a development status, implying additional review processes before production use.
  • Societal & cultural harmReliance on AI-generated code could reduce developer skill development or create dependency on a proprietary vendor system for public-sector software.Safeguard: The tool is positioned as an assistant that supports rather than replaces developers; human review is required for all suggestions. Deployment is currently in development status, limiting exposure.