AI-Assisted Space Robotics Training for Operators

Education & Learning

What it collects that can identify you

About behaviour

Pseudonymous data

Learner interactions within the training environment — responses to exercises, simulation performance, choices made during the training — are processed to personalize and adapt the curriculum. These are linked to individual GC employee accounts.

Government of Canada AI Register — PAT (Personal Assistant Trainer)

Also collects operational data, which is anonymized data.

Run by: Canadian Space Agency (CSA)
Where: No fixed location
Kept: Not stated by the Helpful Places.
Shared with: Accountable organization

What it is for

Education & Learning

PAT is an AI-powered training tool developed for Canadian Space Agency personnel to learn how to operate the Mobile Servicing System (Canadarm2) and eventually the Canadarm3 on the Gateway Station. It delivers both theoretical knowledge and hands-on simulated practice in an adaptive learning environment. The system is currently in development and is intended for use only by Government of Canada employees working in space robotics. It does not make operational decisions about space missions — it supports training.

What it collects and what happens to it

Data taken in

About behaviour

Pseudonymous data

Learner interactions within the training environment — responses to exercises, simulation performance, choices made during the training — are processed to personalize and adapt the curriculum. These are linked to individual GC employee accounts.

Government of Canada AI Register — PAT (Personal Assistant Trainer)

Operational data

Anonymized data

Technical documentation, operational manuals, and procedural content about the MSS (Canadarm2) and its robotics work station (RWS) operational environment, used to build the knowledge base and training content within PAT.

Government of Canada AI Register — PAT (Personal Assistant Trainer)

Processing

Not stated by the Helpful Places.

What it does

Deciding (Analytical AI)

Human decides

PAT adapts the training experience based on learner performance, predicting and classifying learning states to personalize the curriculum. A human trainer or the learner retains control over learning progression decisions.

Government of Canada AI Register — PAT (Personal Assistant Trainer)

Creating (Generative AI)

Human decides

PAT creates a state-of-the-art learning experience, which likely includes generating training scenarios, instructional content, or simulated robotics situations for learners. Human instructors and learners determine how and whether to use the generated content.

Government of Canada AI Register — PAT (Personal Assistant Trainer)

Outputs

A recommendation or prediction

Pseudonymous data

PAT produces adaptive learning recommendations — personalized curriculum paths, next learning activities, and performance feedback — for individual CSA trainees based on their progress and performance in the training environment.

Government of Canada AI Register — PAT (Personal Assistant Trainer)

Generated content

Anonymized data

The system generates training scenarios, instructional content, and simulated operational environments representing the MSS/Canadarm2 robotics work station for learners to interact with during training sessions.

Government of Canada AI Register — PAT (Personal Assistant Trainer)

Run by

Canadian Space Agency (CSA)

The Canadian Space Agency (CSA) is the Government of Canada department responsible for the deployment and operation of PAT, which supports internal space robotics training for CSA employees.

Government of Canada AI Register — PAT (Personal Assistant Trainer)

Built by

OVA

OVA is the external vendor contracted to build and supply the PAT AI system for the Canadian Space Agency.

Government of Canada AI Register — PAT (Personal Assistant Trainer)

Kept for

Not stated by the Helpful Places.

Shared with

Available to the accountable organization

Training performance and interaction data generated by GC employees using PAT is available to the Canadian Space Agency, which uses it to manage and improve training outcomes for space robotics operators.

Government of Canada AI Register — PAT (Personal Assistant Trainer)

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 Algorithmic TransparencyGC employees using PAT may request information about how the AI adapts their training experience. As a Government of Canada system, disclosures about the system are available through the AI register at open.canada.ca. Contact the Canadian Space Agency for further information.

Risks and safeguards

Reputational harmInaccurate or incomplete training content could mislead operators about actual MSS/Canadarm2 procedures, potentially creating false confidence in trainees before they operate real systems.Safeguard: The system is in development with human subject matter experts involved; training is advisory and does not replace formal operational certification processes managed by CSA instructors.