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Helpful Places

Government of Canada – DTPR AI Register

AI-Assisted Meeting Transcription, Summarization, and Translation

Inform · Translation & Language Access

What it collects that can identify you

Biometric
Identifiable data
  • Voice recordings of meeting participants captured in client-provided .mp3 files. Voices are a biometric signal that may identify individual speakers.
Run by
Environment and Climate Change Canada (ECCC)
Where
No fixed location
Kept
Not stated by the Helpful Places.
Shared with
Accountable organization

What it is for

InformTranslation & Language Access

This system takes audio recordings of Government of Canada meetings and uses AI to produce a written transcription that identifies individual speakers, generate a summary of the meeting, and translate the transcription into the other official language. It is currently a proof of concept used by Government of Canada employees. Users are not currently informed that AI is being used to process their meeting recordings.

What it collects and what happens to it

Data taken in

Biometric
Identifiable data
  • Voice recordings of meeting participants captured in client-provided .mp3 files. Voices are a biometric signal that may identify individual speakers.

Processing

Speech & Audio
  • The system converts .mp3 audio files containing meeting recordings into text transcriptions with distinct speaker identification, using speech-to-text processing.
Language Models
  • Large Language Model knowledge is used to generate meeting summaries and produce translated versions of transcriptions.

What it does

Sensing (Perceptive AI)
Human executes
  • The system processes audio (.mp3) files from meeting recordings, converting spoken language into structured text with distinct speaker identification.
Understanding (Semantic AI)
Human executes
  • The system understands and summarizes meeting content, extracting key information from transcribed speech to generate a concise meeting summary.
Creating (Generative AI)
Human executes
  • The system generates new content in the form of meeting summaries and translated transcriptions that did not exist before processing.

Outputs

Generated content
Identifiable data
  • The system produces three outputs: a transcription file with distinct speakers identified, a meeting summary generated from the source audio, and a translated version of the transcription. These outputs may contain identifiable information about meeting participants.

Run by

Environment and Climate Change Canada (ECCC)
  • The federal department that is deploying this proof-of-concept AI system to transcribe, summarize, and translate internal meeting recordings for Government of Canada employees.

GC AI Register — 2526-ECCC-007

Built by

Government of Canada
  • The system was developed by the Government of Canada, indicating internal development rather than procurement from an external vendor.

GC AI Register — 2526-ECCC-007

Kept for

Not stated by the Helpful Places.

Shared with

Available to the accountable organization
  • Transcription outputs, meeting summaries, and translated transcriptions are available to the GC employees who submitted the .mp3 file and to the deploying department (Environment and Climate Change Canada).

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 UseAs of the register date, AI use is not disclosed to users. Meeting participants should be informed before their voices are processed by this AI system. Contact Environment and Climate Change Canada for information about planned disclosure practices.
  • Right to Algorithmic TransparencyGovernment of Canada employees whose meetings are processed by this system have the right to understand how the AI transcription, summarization, and translation capabilities work. Details about the underlying models and data handling can be requested from Environment and Climate Change Canada.

Risks and safeguards

  • Psychological harmParticipants in recorded meetings may not be aware their voices are being processed by AI (the register notes AI use is not disclosed to users). This creates a risk of distress or chilling effects on candid conversation.Safeguard: the system is currently in development (proof of concept stage), limiting exposure. A disclosure mechanism should be implemented before wider deployment.
  • Civil liberties harmRecording and transcribing employee conversations without disclosure could infringe on reasonable expectations of privacy in workplace communications. The register explicitly notes AI use is not disclosed to users.Safeguard: restrict use to consenting participants; implement mandatory disclosure; limit retention of transcription outputs; ensure transcripts are not used for surveillance or performance monitoring.