AI-Assisted Triage of Radiation Alarms at the Border
Border & Immigration · Safety & Security
What it collects
- Radiation readings collected by CBSA radiation portal monitors as cargo containers pass through. Data is gathered by CBSA Science and Engineering (S&E) and contains no personal information.
- Run by
- Canada Border Services Agency (CBSA)
- 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 system uses a machine learning algorithm to assess alarms triggered by radiation portal monitors at Canadian border crossings. When a cargo container passes through a portal monitor and triggers an alarm, the algorithm helps border officers decide whether the alarm indicates a genuine threat or a benign source of radiation. No personal information is processed. Border officers are informed that AI is used in this process.
What it collects and what happens to it
Data taken in
- Radiation readings collected by CBSA radiation portal monitors as cargo containers pass through. Data is gathered by CBSA Science and Engineering (S&E) and contains no personal information.
Processing
- A machine learning algorithm trained on historical CBSA radiation portal monitor data classifies incoming alarms as requiring further inspection or as likely benign, supporting officer triage decisions.
What it does
- The machine learning algorithm classifies radiation portal monitor alarms — assessing whether an alarm represents an abnormal or benign radiation event. The result is a triage recommendation; border officers make the final determination and take action.
Outputs
- The algorithm produces a triage assessment of each radiation portal monitor alarm — indicating whether the alarm is likely to represent an abnormal radiation event. This output advises government employees who then make the final enforcement decision.
Run by
- The Canada Border Services Agency deploys and operates this machine learning algorithm to triage radiation portal monitor alarms at Canadian border crossings. The system was developed in-house by CBSA.
Built by
- The algorithm was developed in-house by the Government of Canada, with no external vendor involved in its creation.
Kept for
Not stated by the Helpful Places.
Shared with
- Triage outputs and alarm data are available to CBSA employees and Government of Canada personnel with appropriate authorization. Primary users are identified as GC employees.
- The triage output data is an internal operational tool used by border officers and is not accessible to members of the public or to cargo owners. No personal information is collected or produced.
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 Register — Triaging RADNET alarms (2526-CBSA-ASFC-008)Canada Border Services Agency, Government of Canada AI Register, entry 2526-CBSA-ASFC-008.
- AI registerGovernment of Canada AI Register — 2526-CBSA-ASFC-008
- AI registerGovernment of Canada AI Register — 2526-CBSA-ASFC-008
- Register entryPublished by the Helpful Places. Reference ffe5ae4e. 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 Algorithmic TransparencyThe Government of Canada discloses the use of AI in this process. Government employees who use the system are informed that AI is used. Members of the public seeking further information may contact the Canada Border Services Agency through official channels.
- Right to a Human ReviewAll alarm triage assessments are reviewed by Government of Canada border officers (GC employees) who make the final enforcement decision. The AI system provides a recommendation only; no automated action is taken without human review.
Risks and safeguards
- Civil liberties harmAutomated triage of border alarms could contribute to secondary inspection decisions that affect individuals' freedom of movement. The register confirms no personal information is involved, reducing direct civil-liberties risk at the algorithmic stage.Safeguard: Human officers (GC employees) make all final decisions; AI use is disclosed to users; the system targets cargo, not individuals.