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AI-Assisted Anomaly Detection in Spectrum Licence Data

Enforcement · Planning & Decision-making

What it collects

Operational data
Anonymized data
  • Spectrum licence site data submitted by wireless service providers (Internet Service Providers), sourced from ISED's Spectrum Management System and other publicly available regulatory datasets. This data describes radio transmission sites and licence parameters, not individuals.
Run by
Innovation, Science and Economic Development Canada (ISED)
Where
No fixed location
Kept
Not stated by the Helpful Places.
Shared with
Accountable organization

What it is for

EnforcementPlanning & Decision-making

This system uses machine learning to automatically find and flag errors or anomalies in spectrum licence site data submitted by wireless service providers to the federal government. It is used internally by Government of Canada employees to improve data quality and support regulatory oversight of the radio spectrum. The system does not process personal information. Its use is publicly disclosed on the Government of Canada's Algorithmic Impact Assessment register.

What it collects and what happens to it

Data taken in

Operational data
Anonymized data
  • Spectrum licence site data submitted by wireless service providers (Internet Service Providers), sourced from ISED's Spectrum Management System and other publicly available regulatory datasets. This data describes radio transmission sites and licence parameters, not individuals.

Processing

Anomaly Detection
  • Machine learning models are trained to detect and label errors or anomalies in spectrum licence site data records submitted by wireless service providers, automating what was previously a slow and inconsistent manual review process.

What it does

Deciding (Analytical AI)
Human decides
  • The system classifies and scores spectrum licence site data records as anomalous or normal. Human analysts (GC employees) review the flagged records and make final compliance or management decisions.

Outputs

A recommendation or prediction
Anonymized data
  • The system produces anomaly labels and flags on spectrum licence site data records, indicating which records are likely erroneous. These outputs are advisory — GC employees review and act on the flagged records.

Run by

Innovation, Science and Economic Development Canada (ISED)
  • The federal department responsible for deploying and operating this machine learning system for spectrum licence data quality and regulatory oversight.

Government of Canada AI Register — 2526-ISED-ISDE-015

Built by

Government of Canada
  • The system was developed internally by the Government of Canada, not by a third-party vendor.

Government of Canada AI Register — 2526-ISED-ISDE-015

Kept for

Not stated by the Helpful Places.

Shared with

Available to the accountable organization
  • Outputs and flagged data are available only to GC employees within ISED for internal compliance and spectrum management 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 Algorithmic TransparencyThe Government of Canada publicly discloses the use of this AI system through the Algorithmic Impact Assessment register, available on the Open Government Portal. Members of the public can access the register entry for information about how the system works and its intended purpose.

Risks and safeguards

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