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Helpful Places

Government of Canada – DTPR AI Register

AI-Assisted Triage for Visitor Record Applications

Border & Immigration · Risk Assessment & Triage

What it collects that can identify you

Sensitive personal information
Identifiable data
  • Personal information from visitor record applications submitted by applicants to IRCC, classified at Protected B/C security level. Data includes identifying information submitted as part of the immigration application and is used directly in eligibility determination and triage. Data is controlled by the federal government and collected by IRCC.

AIA — About the Data (Q26-36)

Also collects operational data, which is anonymized data.

Run by
Immigration, Refugees and Citizenship Canada (IRCC)
Where
No fixed location
Kept
Retained Not specified in available documentation
Shared with
Accountable organization
Your copy
You cannot see the data it holds about you. What you can do

What it is for

Border & ImmigrationRisk Assessment & Triage

This system uses advanced data analytics and machine learning to sort and prioritize visitor record applications submitted to Immigration, Refugees and Citizenship Canada (IRCC). For straightforward applications, it can automatically approve the eligibility portion before a human officer reviews admissibility and makes the final decision. The system never refuses an application — all refusals remain the exclusive responsibility of trained IRCC officers. AI involvement is disclosed to applicants.

What it collects and what happens to it

Data taken in

Sensitive personal information
Identifiable data
  • Personal information from visitor record applications submitted by applicants to IRCC, classified at Protected B/C security level. Data includes identifying information submitted as part of the immigration application and is used directly in eligibility determination and triage. Data is controlled by the federal government and collected by IRCC.

AIA — About the Data (Q26-36)

Operational data
Anonymized data
  • Historical IRCC case data used to generate machine learning rules, sourced from multiple systems that the automated decision system interfaces with. IRCC collected all training data internally.

AIA — About the Data (Q32-36)

Processing

Classification & Prediction
  • Uses a combination of rules developed with IRCC officers and rules generated through machine learning on previous IRCC case data to classify applications by eligibility and complexity. Identifies routine applications that qualify for streamlined processing and predicts outcomes to sort cases by complexity for officer assignment.

AIA — Project Description

Anomaly Detection
  • Analyzes large datasets to identify anomalies and cluster patterns as part of the process optimization capability, helping distinguish routine applications from complex ones requiring manual officer review.

Government of Canada AI Register — Capabilities

What it does

Deciding (Analytical AI)
Human executes
  • The system classifies visitor record applications by complexity and, for routine cases, automatically approves the eligibility portion. The positive eligibility determination is then acted upon by officers who perform admissibility screening and make all final approve-or-refuse decisions.

AIA — About the Decision (Q10)

Sensing (Perceptive AI)
Human decides
  • Processes unstructured data including audio and text files from visitor record applications to extract structured information for eligibility and triage assessment.

AIA — About the Data (Q37-38)

Outputs

A decision about you
Identifiable data
  • Automated positive eligibility determinations for routine visitor record applications. The system approves only the eligibility portion of certain applications — it never refuses applications nor recommends refusals. Officers subsequently determine admissibility and make all final approve-or-refuse decisions.

AIA — About the Decision (Q10)

A recommendation or prediction
Identifiable data
  • Case complexity rankings and triage assignments that route applications to appropriate officers for manual review. Case annotations or notes summarizing basic application information are provided to officers to support faster processing. These outputs advise officers but do not bind their decisions.

AIA — Project Description

Run by

Immigration, Refugees and Citizenship Canada (IRCC)
  • The federal department responsible for deploying and operating this advanced analytics triage system for visitor record applications. IRCC officers retain final decision-making authority on all applications.

Government of Canada AI Register — Advanced Analytics Triage of Visitor Record Applications

Built by

Not stated by the Helpful Places.

Kept for

Retained Not specified in available documentation
  • The system maintains a comprehensive audit trail recording all decisions, recommendations, decision points, model versions, authorized decision-makers, and change control processes. Specific retention durations are not stated in the AIA; the system interfaces with IRCC's existing Personal Information Banks which govern retention.
  • Duration: Not specified in available documentation

AIA — Mitigation Measures — Procedural Fairness (Q17-32)

Shared with

Available to the accountable organization
  • Outputs and audit trails are available to IRCC decision-makers and authorized personnel. Access permissions are granted, monitored, and revoked through a documented process. Officers use the system's outputs to process applications but are deliberately not informed of the system's internal rules or analysis to prevent automation bias.

AIA — Mitigation Measures — Procedural Fairness (Q27, Q19)

Not available to me
  • Applicants cannot access the system's internal rules, triage logic, or the specific analysis performed on their application. However, AI use is disclosed to applicants and, where a decision involves denial of a benefit or service, a meaningful explanation must be provided including the role of the system in the decision-making process.

Government of Canada AI Register — AI Use Disclosed · AIA — Section 2 Requirements — Explanation

Stored

Stored locally
  • Data is controlled by the federal government and stored within IRCC systems in Canada. The system operates within a closed environment (not connected to the Internet). Input data is classified at Protected B/C security level.
  • Duration: Not specified; governed by IRCC Personal Information Banks

AIA — About the Data (Q30-31, Q36)

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 UseIRCC discloses AI use to applicants through plain language notices posted through all service delivery channels (Internet, in person, mail, or telephone). Applicants are informed that an automated decision system is used in processing their visitor record application.
  • Right to an Explanation of a DecisionApplicants whose applications result in denial of a benefit or service are entitled to a meaningful explanation that includes: the role of the system in the decision-making process; the training and client data, their source, and method of collection; the criteria used to evaluate client data; the output produced by the system and how to interpret it; and a justification of the decision including the principal factors. Recourse options must also be communicated. A general description must be publicly available via the AIA and departmental website.
  • Right to ContestA recourse process is established for applicants who wish to challenge a decision. Officers can override system determinations, and if an officer encounters information during admissibility assessment that may affect a positive eligibility determination, they may revisit that determination. Visitor record applicants whose applications are refused can re-apply, as IRCC approves many clients with prior refusals.
  • Right to Algorithmic TransparencyA general description of the system's role, the data it uses, and the criteria it applies is publicly available through the Algorithmic Impact Assessment published on the Open Government Portal. The system's logic is described as interpretable and not a trade secret. Rules are linked to legislative and regulatory requirements and reviewed by officers, legal, policy, and data science experts.
  • Right to a Human ReviewAll applications receive a human officer review — IRCC officers make the final decision to approve or refuse on all applications. For applications where the system approves eligibility, an officer still performs the admissibility determination and makes the final decision. For all other applications, officers perform both eligibility and admissibility assessments manually. Officers can override the system's determinations at any time.
  • Right to Non-discriminationAll system rules are assessed for potential bias or discrimination before deployment and at regular intervals. A Gender-Based Analysis Plus has been conducted addressing impacts on gender and other identity factors. Rules are based only on data elements with a clear link to legislative and regulatory requirements. Documented processes are in place to test datasets against biases and unexpected outcomes.

Risks and safeguards

  • Civil liberties harmThe triage and automated eligibility determination function could influence officer decision-making (automation bias) or inadvertently introduce discriminatory outcomes in an immigration context under intense public scrutiny.Safeguard: Officers are deliberately separated from system logic — they are not informed of the rules used or the system's analysis. An ongoing quality assurance process monitors officer decisions against system determinations. All rules are reviewed by officers, legal, policy, and data science experts before deployment and at regular intervals. A Gender-Based Analysis Plus has been conducted. The system never refuses applications. All rules are assessed for potential bias or discrimination.
  • Reputational harmErroneous eligibility classifications could stigmatize applicants or result in unfair processing outcomes in a high-scrutiny immigration context.Safeguard: The system is restricted to approving eligibility only — it never refuses applications nor recommends refusal. Rules are linked only to data elements with a clear link to legislative and regulatory requirements. A comprehensive audit trail records all system recommendations and decision points, with version control for all model changes. Officers can override system determinations and revisit eligibility if new information arises during admissibility screening.