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AI-Assisted Client Complaints and Satisfaction Management

Safety & Security

What it collects that can identify you

Sensitive personal information
Identifiable data
  • Complaints and claims submitted by members of the public about airport security screening experiences, which may include personal identifying information such as names and contact details.
About behaviour
Identifiable data
  • Narrative text describing client interactions with CATSA screening processes, including accounts of screening officer conduct and procedural experiences, as expressed in complaints and claims.
Run by
Canadian Air Transport Security Authority (CATSA)
Where
No fixed location
Kept
Not stated by the Helpful Places.
Shared with
Accountable organization

What it is for

Safety & Security

The Canadian Air Transport Security Authority (CATSA) is developing an AI tool to automate the handling of client complaints and claims. It uses natural language processing, sentiment analysis, and chatbot technology to triage, route, and respond to submissions from airport security screening clients. The system is still in development and currently serves internal government employees rather than the general public directly. Individuals who submit complaints to CATSA may have their text analyzed by automated systems that infer emotional tone.

What it collects and what happens to it

Data taken in

Sensitive personal information
Identifiable data
  • Complaints and claims submitted by members of the public about airport security screening experiences, which may include personal identifying information such as names and contact details.
About behaviour
Identifiable data
  • Narrative text describing client interactions with CATSA screening processes, including accounts of screening officer conduct and procedural experiences, as expressed in complaints and claims.

Processing

Affect & Emotion Analysis
  • Sentiment analysis is applied to client complaint text to infer emotional tone, supporting triage prioritization and automated routing of submissions.
Language Models
  • Natural language processing models interpret client complaint text, support multilingual response generation, and power the chatbot and virtual assistant capabilities.
Classification & Prediction
  • Automated triage classifies incoming complaints and claims by type, urgency, or topic to route them appropriately within CATSA's case management workflows.

What it does

Deciding (Analytical AI)
Human decides
  • The system performs automated triage and sentiment classification of incoming complaints and claims, scoring and routing them to support human case handlers who make final decisions.
Understanding (Semantic AI)
Human decides
  • Natural language processing is used to interpret the meaning and sentiment of client submissions, enabling search, classification, and alignment with business intelligence reporting.
Creating (Generative AI)
Human decides
  • Chatbot and virtual assistant capabilities generate personalized, multilingual responses to client complaints and inquiries, with human review of complex or high-stakes cases.

Outputs

A recommendation or prediction
Anonymized data
  • Triage classifications, sentiment scores, and routing recommendations produced by the system to support GC employees handling complaints and claims. Business intelligence reports summarizing complaint patterns are also produced at an aggregate level.
Generated content
Identifiable data
  • Personalized, multilingual responses to client complaints and inquiries generated by the chatbot and virtual assistant capabilities, directed to the individual who submitted the complaint.

Run by

Canadian Air Transport Security Authority (CATSA)
  • CATSA is the federal agency responsible for airport security screening in Canada. It is developing and deploying this AI tool to automate its internal complaints and client satisfaction processes.

Government of Canada AI Register — CATSA entry

Built by

Third-Party Vendor
  • The system is developed by an external vendor. The vendor's identity is not disclosed in the public register entry.

Government of Canada AI Register — CATSA entry

Kept for

Not stated by the Helpful Places.

Shared with

Available to the accountable organization
  • Complaint and claims data, along with AI-generated triage classifications and responses, are available to CATSA's internal GC employees who manage client satisfaction processes.

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 UseIndividuals submitting complaints or claims to CATSA should be informed that their submissions may be processed by automated AI systems, including sentiment analysis and chatbot technologies. CATSA has not publicly disclosed specific notice mechanisms in the register entry; members of the public should contact CATSA directly for information about how their complaints are handled.
  • Right to a Human ReviewGC employees are listed as the primary users of this system, implying human oversight of automated outputs. Individuals whose complaints are handled by this system should be able to request that a human CATSA employee review their case. Contact CATSA directly to request human review of a complaint or claim decision.

Risks and safeguards

  • Psychological harmAutomated sentiment analysis of complaint text may misclassify the emotional state of individuals who have experienced stressful or distressing security incidents, potentially leading to inadequate or dismissive automated responses.Safeguard: Human review of complex or escalated cases should be maintained; the system is described as supporting rather than replacing GC employee judgment. The register notes the system is still in development, allowing safeguards to be designed in before deployment.
  • Reputational harmMisclassification of complaints by automated triage could result in legitimate grievances being deprioritized or misdirected, damaging trust in CATSA's accountability processes.Safeguard: Business intelligence reporting alignment mentioned in the register may provide oversight signals; human employees remain the primary users and decision-makers for case resolution.