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AI-Assisted Training Course Creation for Government Employees

Education & Learning · Research & Development

What it collects

Operational data
Anonymized data
  • Source documents used as the knowledge base in the RAG tool — existing training materials, reference documents, and organizational content provided to augment the generative AI model's outputs.
Run by
Environment and Climate Change Canada (ECCC)
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

Education & LearningResearch & Development

This tool was a proof-of-concept built by Environment and Climate Change Canada to explore whether generative AI could help staff create training course materials more efficiently. It used a retrieval-augmented generation (RAG) approach, grounding AI-generated content in existing source documents. The system was used internally by Government of Canada employees and has since been retired. Users were informed that AI was in use.

What it collects and what happens to it

Data taken in

Operational data
Anonymized data
  • Source documents used as the knowledge base in the RAG tool — existing training materials, reference documents, and organizational content provided to augment the generative AI model's outputs.

Processing

Language Models
  • A large language model provides the generative AI capability, combined with a Retrieval Augmented Generation (RAG) pipeline that injects relevant source document passages into the model's context before generating training content.
Search & Retrieval
  • A retrieval component searches the corpus of source documents to find relevant passages and feeds them into the language model as augmented context (RAG architecture).

What it does

Creating (Generative AI)
Human decides
  • The system uses generative AI to produce training course content — text and structured course materials — from a combination of model knowledge and retrieved source documents. GC employees (human authors) initiate and review the generated content.
Understanding (Semantic AI)
Human decides
  • The system employs Retrieval Augmented Generation (RAG) to locate and retrieve relevant passages from source documents, grounding the AI-generated course content in existing training materials.

Outputs

Generated content
Anonymized data
  • The system produces newly generated training course materials — structured course text, learning objectives, and other educational content authored by the AI based on source documents and model knowledge.

Run by

Environment and Climate Change Canada (ECCC)
  • ECCC's Digital Services Branch built and operated this proof-of-concept generative AI tool to explore training material creation for Government of Canada employees.

Government of Canada AI Register — 2526-ECCC-003

Built by

Not stated by the Helpful Places.

Kept for

Not stated by the Helpful Places.

Shared with

Available to the accountable organization
  • Outputs (generated course materials) were available to ECCC Digital Services Branch staff and GC employees who used the tool internally. No personal information was collected or processed.
Not available to me
  • This was an internal Government of Canada tool; the system has been retired and its outputs are not accessible to members of the general public.

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 UseAI use was disclosed to users of this system. Government of Canada employees using the tool were informed that generative AI was being used to produce the course content.

Risks and safeguards

No risks or safeguards have been published for this system yet.