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AI-Assisted Numerical Data Extraction for Results Reporting

Planning & Decision-making

What it collects

Operational data
Anonymized data
  • Project titles and descriptions from Housing, Infrastructure and Communities Canada programs. These are administrative records describing funded projects, not records about individuals. No personal information is included.
Run by
Housing, Infrastructure and Communities Canada (HICC)
Where
No fixed location
Kept
Not stated by the Helpful Places.
Shared with
Accountable organization

What it is for

Planning & Decision-making

This system uses a fine-tuned large language model (LLM) to automatically extract numerical data from text describing government-funded housing and infrastructure projects. It is used internally by Government of Canada employees to improve the accuracy and efficiency of results reporting. The system does not process personal information, and users are informed that AI is being used.

What it collects and what happens to it

Data taken in

Operational data
Anonymized data
  • Project titles and descriptions from Housing, Infrastructure and Communities Canada programs. These are administrative records describing funded projects, not records about individuals. No personal information is included.

Processing

Language Models
  • A fine-tuned large language model (LLM) is used to read project text and extract numerical values relevant to results reporting. The model is adapted (fine-tuned) specifically for the department's data extraction task.

What it does

Sensing (Perceptive AI)
Human decides
  • The fine-tuned LLM reads project title and description text and extracts structured numerical data from it. GC employees review and use the extracted results, retaining decision authority over the final reporting.
Deciding (Analytical AI)
Human decides
  • The system classifies and structures numerical values found in unstructured text, producing labeled data outputs that employees use for results reporting rather than acting on autonomously.

Outputs

Operational data
Anonymized data
  • Structured numerical data extracted from project descriptions, used to populate results reports. Outputs are administrative in nature and do not contain personal information about individuals.

Run by

Housing, Infrastructure and Communities Canada (HICC)
  • The federal department responsible for deploying and operating this AI system to improve internal results reporting for housing and infrastructure projects.

Government of Canada AI Register — Results Stories LLM Project

Built by

Government of Canada
  • The system was developed internally by the Government of Canada, with no external vendor identified in the register entry.

Government of Canada AI Register — Results Stories LLM Project

Kept for

Not stated by the Helpful Places.

Shared with

Available to the accountable organization
  • The extracted numerical data outputs are available to GC employees within Housing, Infrastructure and Communities Canada for internal results reporting purposes.

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 UseGC employees who use this system are informed that AI is being used in the results reporting process. The register confirms AI use is disclosed to users.
  • Right to Algorithmic TransparencyThe system is listed on the Government of Canada's public AI register, providing transparency about its purpose, capabilities, and the absence of personal information processing. Users can consult the register entry for further information.

Risks and safeguards

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