AI-Assisted Survey Comment Classification for Statistical Analysis
Research & Development · Planning & Decision-making
What it collects
- Free-text respondent comments submitted via the Annual Survey of Manufacturing and Logging Industries (ASML) and the CAPEX survey. The register states no personal information is involved.
- Run by
- Statistics Canada (StatCan)
- 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
This tool automatically sorts respondent comments from the Annual Survey of Manufacturing and Logging Industries into groups to help Statistics Canada analysts prioritize their review. It uses a large language model to triage comments without prior training examples. The system is retired and affected only Government of Canada employees, not the public. AI use was disclosed to users.
What it collects and what happens to it
Data taken in
- Free-text respondent comments submitted via the Annual Survey of Manufacturing and Logging Industries (ASML) and the CAPEX survey. The register states no personal information is involved.
Processing
- LLM zero-shot learning: a large language model is prompted to classify comments into triage groups without task-specific fine-tuning or labelled training examples.
- Assigns each respondent comment to a triage group (label) representing the type of action or attention it warrants from analysts.
What it does
- Classifies and groups respondent comments into categories for analyst review. The system produces triage groupings; human analysts then decide which comments to action and how.
- Uses LLM zero-shot learning to understand the meaning of free-text respondent comments and assign them to relevant triage groups without task-specific training examples.
Outputs
- Triage group assignments for each respondent comment — advisory groupings that direct analyst attention but do not constitute binding decisions about individuals.
Run by
- Statistics Canada developed and deployed this comment classification tool for use by its own analysts reviewing manufacturing and logging industry survey responses.
Built by
- The Government of Canada is listed as the developer of this system, indicating internal government development rather than a third-party vendor.
Kept for
Not stated by the Helpful Places.
Shared with
- The system was used exclusively by Government of Canada employees (Statistics Canada analysts). Survey respondents and the general public had no access to the classification outputs.
- Classification outputs were available to Statistics Canada analysts for the purpose of reviewing and actioning survey comments.
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.
- AI registerGovernment of Canada Algorithmic Impact Assessment Registry — ASML Comments Classification (2526-StatCan-014)Statistics Canada, Government of Canada AI Register entry 2526-StatCan-014.
- AI registerGovernment of Canada AI Register — 2526-StatCan-014
- AI registerGovernment of Canada AI Register — 2526-StatCan-014
- Register entryPublished by the Helpful Places. Reference a7b0e552. This disclosure was drafted with AI assistance.Schema: ai@2026-05-06-beta
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 the system (Government of Canada employees). The register confirms AI use was disclosed to users. As respondents' comments — not the respondents themselves — were the primary users' data, and primary users were GC employees, disclosure was directed at those internal users.
- Right to Algorithmic TransparencyStatistics Canada has published this system's details in the Government of Canada AI Register, providing transparency about the LLM-based approach and its purpose to triage survey comments.
Risks and safeguards
No risks or safeguards have been published for this system yet.