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Helpful Places

Government of Canada – DTPR AI Register

AI-Assisted Interview Feedback for Public Servants

Education & Learning

What it collects that can identify you

Biometric
Identifiable data
  • Video recordings of practice interviews capture the user's face, voice, and body language. These biological signals are the primary input to the system's analysis.
Run by
Canada School of Public Service (CSPS)
Where
No fixed location
Kept
Not stated by the Helpful Places.
Shared with
Not stated by the Helpful Places.

What it is for

Education & Learning

This system analyzes video recordings of practice job interviews and provides automated feedback on communication skills, including speech patterns and tone. It is used by Government of Canada employees who want to improve their interview performance. The system involves personal information — video recordings — and users are informed that AI is in use.

What it collects and what happens to it

Data taken in

Biometric
Identifiable data
  • Video recordings of practice interviews capture the user's face, voice, and body language. These biological signals are the primary input to the system's analysis.

Processing

Computer Vision
  • Interprets video frames from practice interview recordings to analyze facial expressions, gaze, and non-verbal communication cues as part of the performance feedback pipeline.
Speech & Audio
  • Analyzes the spoken content of practice interview recordings to provide feedback on speech patterns, pacing, clarity, and tone as described in the system capabilities.
Affect & Emotion Analysis
  • Infers tone and emotional delivery from speech and video signals to generate feedback on how the interviewee comes across — a core advertised capability of the system.

What it does

Sensing (Perceptive AI)
Human decides
  • The system processes video recordings of practice interviews to extract structured signals about speech patterns, tone, and communication behaviors from audio and visual data.
Deciding (Analytical AI)
Human decides
  • The system scores or classifies aspects of interview performance — such as tone, pacing, and delivery — and produces structured feedback ratings that the user then reviews and acts on.

Outputs

A recommendation or prediction
Identifiable data
  • The system produces personalized feedback on interview performance — including scores or ratings on speech patterns and tone — delivered to the individual GC employee who completed the practice session. The feedback is advisory; it does not constitute a hiring or promotional decision.

Run by

Canada School of Public Service (CSPS)
  • The Canada School of Public Service deploys this AI-assisted feedback tool to help Government of Canada employees build communication and interview skills.

Government of Canada AI Register — AI Register ID 2526-CSPS-EFPC-026

Built by

Knockri
  • Knockri is the vendor that built and supplies the virtual interview feedback AI system, providing video analysis and speech and tone assessment capabilities.

Government of Canada AI Register — AI Register ID 2526-CSPS-EFPC-026

Kept for

Not stated by the Helpful Places.

Shared with

Not stated by the Helpful Places.

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 UseThe register confirms that AI use is disclosed to users before they engage with the system. GC employees are informed that their practice interview video will be analyzed by an AI system.
  • Right to Algorithmic TransparencyUsers have a right to understand how the system evaluates their interview performance, including what signals (video, speech, tone) are analyzed and how feedback scores are generated. The register entry does not detail how this transparency is operationalized; users should contact the Canada School of Public Service for more information.
  • Right to Non-discriminationUsers have the right not to be assessed in a discriminatory manner based on protected characteristics such as accent, cultural background, disability, or other attributes that may influence speech and tone signals. No bias testing or fairness audit disclosures are present in the register entry.

Risks and safeguards

  • Reputational harmAutomated feedback on speech, tone, and body language may produce inaccurate or culturally biased assessments that unfairly characterize an individual's communication style, potentially affecting their self-perception or career confidence. The system is limited to practice interview sessions and does not feed directly into hiring decisions, which provides a partial mitigation. No specific bias audit or accuracy threshold is disclosed in the register entry.
  • Psychological harmAutomated scoring of personal communication style — including inferences about emotional tone — may cause distress, anxiety, or reduced confidence in users who receive negative or confusing feedback. The developmental status of the system suggests mitigations may not yet be fully in place; no specific safeguards (such as human review of feedback or opt-out mechanisms) are described in the register entry.
  • Civil liberties harmVideo-based affect and tone analysis of government employees raises concerns about surveillance of expressive and communicative behavior in a workplace context. Although participation is described as practice-oriented, the use of biometric-adjacent signals (facial expression, voice tone) warrants scrutiny under Canadian privacy law. No privacy impact assessment or consent framework details are disclosed in the register entry.