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Government of Canada – DTPR AI Register

AI-Assisted News Topic Detection for Fisheries Policy

Planning & Decision-making · Inform

What it collects that can identify you

Sensitive personal information
Identifiable data
  • The register confirms personal information is involved, though the nature is not fully specified. Given use by both employees and the public, some user or author identity data may be processed in connection with news content or system interaction.

Also collects operational data, which is anonymized data.

Run by
Fisheries and Oceans Canada (DFO)
Where
No fixed location
Kept
Not stated by the Helpful Places.
Shared with
Accountable organization

What it is for

Planning & Decision-makingInform

This system uses large language models and topic clustering to automatically scan news sources and identify emerging topics relevant to Fisheries and Oceans Canada's mandate. It surfaces connections between external news developments and DFO's existing knowledge and resources, helping staff prioritize and plan responses. The system is currently in development and users are informed when AI is involved in the process.

What it collects and what happens to it

Data taken in

Operational data
Anonymized data
  • Published documents from the Canadian Science Advisory Secretariat (CSAS), used as the primary data source to analyze news topics and connect them to DFO's existing scientific and policy knowledge.
Sensitive personal information
Identifiable data
  • The register confirms personal information is involved, though the nature is not fully specified. Given use by both employees and the public, some user or author identity data may be processed in connection with news content or system interaction.

Processing

Language Models
  • Large language models (LLMs) are used to assess the semantic relevance of news topics to DFO's mandate and to surface connections with internal knowledge resources.
Clustering & Segmentation
  • Topic clustering is applied to group emerging news items into coherent themes, enabling systematic identification of trends without relying on pre-defined categories.

What it does

Deciding (Analytical AI)
Human decides
  • The system scores and ranks news topics by relevance to DFO's mandate. Staff decide which topics warrant follow-up action or resource allocation — the AI advises rather than determines.
Understanding (Semantic AI)
Human decides
  • Uses large language models to understand and retrieve connections between external news topics and DFO's internal knowledge base, surfacing relevant existing resources and documents.

Outputs

A recommendation or prediction
Anonymized data
  • The system produces ranked or prioritized news topic clusters indicating their relevance to DFO, along with links to existing internal resources — advisory outputs that staff use to inform planning decisions.
Operational data
Anonymized data
  • Structured summaries of emerging news themes and their connection to DFO's existing knowledge base and mandate areas, delivered as operational intelligence to support departmental strategy.

Run by

Fisheries and Oceans Canada (DFO)
  • The federal department that deploys this news topic detection tool to monitor emerging issues relevant to its fisheries and oceans mandate.

Government of Canada AI Register — 2526-DFO-MPO-002

Built by

Not stated by the Helpful Places.

Kept for

Not stated by the Helpful Places.

Shared with

Available to the accountable organization
  • Outputs — ranked news topics and connections to internal knowledge — are available to Fisheries and Oceans Canada employees. The register also lists the public as a primary user, though the nature of public-facing access is unspecified.

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 are informed when AI is involved in the process, as disclosed in the AI register entry. The specific mechanism of notice (e.g. on-screen disclosure, documentation) is not detailed in the available source.
  • Right to Algorithmic TransparencyThe system is registered in the Government of Canada's public AI register, providing high-level transparency about its purpose, data sources, and the use of large language models and topic clustering. Detailed model documentation is not publicly linked.

Risks and safeguards

  • Societal & cultural harmLLM-based topic relevance assessments may reflect training data biases, potentially skewing which news topics are surfaced as relevant to DFO's mandate.Safeguard: The system is advisory (human decides), limiting direct harm. The register notes the system is still in development, implying ongoing evaluation. No specific bias audit or mitigation mechanism is documented in the source.