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Helpful Places

Government of Canada – DTPR AI Register

AI Assistant for Energy Research Document Analysis

Research & Development

What it collects that can identify you

Sensitive personal information
Identifiable data
  • User-uploaded documents and media described as 'private' data, which may contain personally identifiable information depending on the documents submitted by GC employees.

Also collects operational data, which is anonymized data.

Run by
Natural Resources Canada (NRCan)
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

Research & Development

This AI assistant helps Natural Resources Canada employees at CanmetENERGY Devon interpret documents and media they upload, generating customized responses and opinions based on the provided content. It uses a large language model (LLM) built on open-source components from Ollama and AnythingLLM. The system is currently in production and is used exclusively by Government of Canada employees. Users are not currently informed that they are interacting with an AI system.

What it collects and what happens to it

Data taken in

Sensitive personal information
Identifiable data
  • User-uploaded documents and media described as 'private' data, which may contain personally identifiable information depending on the documents submitted by GC employees.
Operational data
Anonymized data
  • User-uploaded documents and media relating to energy research activities, including reports, datasets, and other operational materials provided by GC employees for analysis.

Processing

Language Models
  • Built on open-source large language models run locally via Ollama, with document-context management provided by AnythingLLM. The system interprets user-uploaded documents and media and formulates customized responses.

What it does

Understanding (Semantic AI)
Human decides
  • The system understands and retrieves meaning from documents and media uploaded by the user, grounding its responses in the provided content context.
Creating (Generative AI)
Human decides
  • The system generates customized textual responses and opinions based on documents and media supplied by the user, producing new content that did not previously exist.

Outputs

Generated content
Anonymized data
  • Customized textual responses and opinions generated by the LLM based on the documents and media provided by the user. Outputs are returned to the individual GC employee who submitted the request.

Run by

Natural Resources Canada (NRCan)
  • Federal department deploying and operating the AI assistant for use by Government of Canada employees at the CanmetENERGY Devon research centre.

Government of Canada AI Register: CanmetENERGY Devon AI Assistant

Built by

Ollama / AnythingLLM
  • The system is built on open-source software components: Ollama (for running local LLMs) and AnythingLLM (for document-context management). The underlying models are described as open source and developed externally.

Government of Canada AI Register: CanmetENERGY Devon AI Assistant

Kept for

Not stated by the Helpful Places.

Shared with

Available to the accountable organization
  • Outputs and interaction data are accessible to Natural Resources Canada. Data sources are described as private, limiting external access.
Not available to me
  • Members of the public do not have access to this system or its outputs. The system is restricted to GC employees and is not publicly facing.

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 currently have no mechanism to be informed that they are interacting with an AI system — the register explicitly states that AI use is not disclosed to users. Government of Canada employees who use this system should be notified of AI involvement. Contact Natural Resources Canada for further information about this system.
  • Right to Algorithmic TransparencyGC employees have a right to understand how this AI system works in general — including the logic involved, the role of the LLM, and how it formulates responses from uploaded documents. Details about the specific open-source models used are not publicly disclosed in the register. Contact Natural Resources Canada for further information.

Risks and safeguards

  • Civil liberties harmUsers are not informed that they are interacting with an AI system (AI use disclosed to users: N), which may undermine informed consent and the right to know about automated processing. The register does not document any mitigation measures for this disclosure gap. Deploying organizations should consider implementing a clear AI-use disclosure notice to users before they interact with the system.