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Helpful Places

Government of Canada – DTPR AI Register

AI-Assisted Product Code Recommender for Manufacturing Surveys

Inform

What it collects

About behaviour
Anonymized data
  • Historical write-in responses from survey respondents describing their products, together with the NAPCS codes previously assigned to those descriptions by analysts. No personal information is included; data concerns product activities of manufacturing and logging enterprises.
Operational data
Anonymized data
  • NAPCS (North American Product Classification System) and NAICS (North American Industry Classification System) code descriptions used as reference data to train and run the recommender model.
Run by
Statistics Canada (StatCan)
Where
No fixed location
Kept
Not stated by the Helpful Places.
Shared with
Accountable organization

What it is for

Inform

This tool helps Statistics Canada analysts assign North American Product Classification System (NAPCS) codes to written product descriptions submitted by manufacturers and logging companies. It recommends codes automatically, but a human analyst reviews and confirms each suggestion before it is applied. The system does not process personal information. Its use is disclosed to the government employees who operate it.

What it collects and what happens to it

Data taken in

About behaviour
Anonymized data
  • Historical write-in responses from survey respondents describing their products, together with the NAPCS codes previously assigned to those descriptions by analysts. No personal information is included; data concerns product activities of manufacturing and logging enterprises.
Operational data
Anonymized data
  • NAPCS (North American Product Classification System) and NAICS (North American Industry Classification System) code descriptions used as reference data to train and run the recommender model.

Processing

Classification & Prediction
  • A text classification model that maps free-text product descriptions to the most appropriate NAPCS product code, trained on historical analyst-coded write-ins from the ASML survey.

What it does

Deciding (Analytical AI)
Human decides
  • The system classifies written product descriptions into NAPCS codes. A human analyst (government employee) reviews each recommendation and decides whether to accept or override it before any code is applied — the register explicitly describes this as a human-in-the-loop design.

Outputs

A recommendation or prediction
Anonymized data
  • A recommended NAPCS product code for each submitted write-in description. The recommendation is advisory only; a Statistics Canada analyst must review and confirm each code before it is recorded in the survey dataset.

Run by

Statistics Canada (StatCan)
  • Statistics Canada is the federal department that developed and operates this AI tool to support the Annual Survey of Manufacturing and Logging Industries. It is accountable for the system's design, deployment, and use by government analysts.

Government of Canada AI Register — 2526-StatCan-015

Built by

Not stated by the Helpful Places.

Kept for

Not stated by the Helpful Places.

Shared with

Available to the accountable organization
  • Outputs (recommended NAPCS codes) are available to Statistics Canada analysts (GC employees) who use them to complete survey coding tasks. No access is provided to external parties or the 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 Algorithmic TransparencyAI use is disclosed to the government employees who interact with this system. Statistics Canada has registered this tool in the Government of Canada AI Register, which is publicly accessible and describes its capabilities and data sources.
  • Right to a Human ReviewEvery code recommendation made by the system is reviewed and confirmed by a human analyst before it is applied. The register explicitly describes the system as 'human in the loop', ensuring no automated decision is acted upon without human verification.

Risks and safeguards

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