AI-Assisted Test Automation and Chatbot Platform for Research Council Staff

Enforcement · Inform

What it collects

Operational data

Anonymized data

Software test specifications, code artefacts, and organizational policy documents used to generate and execute test cases and to ground chatbot responses in institutional context.

GC AI Register — Description field

About behaviour

Anonymized data

Employee queries and interaction logs submitted to the chatbot, used to tailor responses and improve system performance. Linked to GC employee accounts but not to the general public.

GC AI Register — Primary users and Description fields

Run by: Social Sciences and Humanities Research Council of Canada (SSHRC)
Where: No fixed location
Kept: Not stated by the Helpful Places.
Shared with: Accountable organization, Vendor
Your copy: You cannot see the data it holds about you. What you can do

What it is for

Enforcement

Inform

This system uses Microsoft's Azure AI Foundry platform to help Government of Canada employees at the Social Sciences and Humanities Research Council automate software testing and build internal chatbots. The chatbots draw on organizational data to provide policy-compliant, tailored answers to staff questions. The system is currently in development and is intended for internal government use only, not for direct interaction with the public.

What it collects and what happens to it

Data taken in

Operational data

Anonymized data

Software test specifications, code artefacts, and organizational policy documents used to generate and execute test cases and to ground chatbot responses in institutional context.

GC AI Register — Description field

About behaviour

Anonymized data

Employee queries and interaction logs submitted to the chatbot, used to tailor responses and improve system performance. Linked to GC employee accounts but not to the general public.

GC AI Register — Primary users and Description fields

Processing

Language Models

Azure AI Foundry hosts large language models used to generate test cases, validate software outputs, and power the customized chatbots that answer staff queries in natural language.

GC AI Register — Description field

What it does

Deciding (Analytical AI)

Human decides

AI models generate and validate test cases, scoring or classifying software behaviour against expected outcomes. Human developers review results and decide how to act on failures or gaps.

GC AI Register — Description field

Creating (Generative AI)

Human decides

The chatbot component generates novel text responses to staff queries by drawing on organizational data and policy documents. Responses are advisory; employees retain final judgement on action.

GC AI Register — Description field

Outputs

Generated content

Anonymized data

AI-generated test cases and validation scripts produced for software quality assurance, and natural-language chatbot responses delivered to GC employees. Neither output type is directed at members of the public.

GC AI Register — Description field

A recommendation or prediction

Anonymized data

Chatbot responses serve as advisory recommendations for staff seeking policy-compliant information; employees decide what action, if any, to take based on the suggestion.

GC AI Register — Description field

Run by

Social Sciences and Humanities Research Council of Canada (SSHRC)

SSHRC is the federal department deploying Azure AI Foundry for internal quality assurance, test automation, and chatbot development for its Government of Canada employees.

GC AI Register — Department field

Built by

Microsoft

Microsoft supplies the Azure AI Foundry platform, which provides the underlying AI models, infrastructure, and tooling used by SSHRC for test automation and chatbot development.

GC AI Register — Vendor field

Kept for

Not stated by the Helpful Places.

Shared with

Available to the accountable organization

Outputs and interaction logs are accessible to SSHRC as the deploying organization. Access is limited to GC employees; no public-facing data access is described.

GC AI Register — Primary users field

Available to vendor

As a cloud-hosted platform, Microsoft (Azure) may have access to data processed through the service under applicable data-processing agreements. The register does not specify data-residency or vendor access terms.

GC AI Register — Vendor field

Not available to me

The system is intended for GC employees only. Members of the public have no described mechanism to access outputs, logs, or data held by the system.

GC AI Register — Primary users field

Stored

Stored on 3rd Party Cloud

Data is processed and stored on Microsoft Azure cloud infrastructure. Specific data-residency jurisdiction (e.g. Canadian Azure regions) and contractual safeguards are not detailed in the register entry.
Duration: Not specified in the register

GC AI Register — Vendor field (Microsoft Azure)

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 interacting with the chatbot have a right to know that they are receiving AI-generated responses. The system is described as being in development; transparency mechanisms for employees are not yet detailed in the register entry. Employees may contact SSHRC's administration for information about how the system operates.

Risks and safeguards

Societal & cultural harmAI-generated chatbot responses grounded in organizational data may propagate outdated or incorrect policy interpretations, eroding trust in internal information systems. Mitigation noted in the register: responses are designed to be policy-compliant; however, no independent audit or human-review safeguard is described for the chatbot outputs at this stage of development.