AI-Enhanced Employment Equity Analysis for Federally Regulated Employers

Employment & Work · Planning & Decision-making

What it collects

Sensitive personal information

Anonymized data

The system processes employment equity data that includes information about persons — specifically workforce representation rates by designated group (e.g., women, Indigenous peoples, persons with disabilities, visible minorities) and pay gap data. The register notes personal information is involved. Data is aggregated at the employer level for analysis, suggesting individuals are not directly identifiable in most outputs.

Government of Canada AI Register — 2526-ESDC-EDSC-001

Operational data

Anonymized data

Employer-reported employment equity data sourced from in-house ESDC systems and Microsoft infrastructure, including representation rates, pay gap figures, and sectoral and location data reported by federally regulated private-sector employers.

Government of Canada AI Register — 2526-ESDC-EDSC-001

Run by: Employment and Social Development Canada (ESDC)
Where: No fixed location
Kept: Not stated by the Helpful Places.
Shared with: Accountable organization

What it is for

Employment & Work

Planning & Decision-making

This system enhances the EquiVision platform used by Employment and Social Development Canada to analyze diversity, equity, and inclusion data from federally regulated private-sector employers. It uses generative AI and natural language processing to automate data collection and provide deeper insight into representation rates and pay gaps. Government employees and decision-makers use the system to identify potential employment barriers and foster employer accountability. Users are informed that AI is used in this system.

What it collects and what happens to it

Data taken in

Sensitive personal information

Anonymized data

The system processes employment equity data that includes information about persons — specifically workforce representation rates by designated group (e.g., women, Indigenous peoples, persons with disabilities, visible minorities) and pay gap data. The register notes personal information is involved. Data is aggregated at the employer level for analysis, suggesting individuals are not directly identifiable in most outputs.

Government of Canada AI Register — 2526-ESDC-EDSC-001

Operational data

Anonymized data

Employer-reported employment equity data sourced from in-house ESDC systems and Microsoft infrastructure, including representation rates, pay gap figures, and sectoral and location data reported by federally regulated private-sector employers.

Government of Canada AI Register — 2526-ESDC-EDSC-001

Processing

Language Models

Large language models and natural language processing techniques are applied to automate data collection and analysis of DEI metrics from employment equity reports submitted by federally regulated employers.

Government of Canada AI Register — 2526-ESDC-EDSC-001

What it does

Creating (Generative AI)

Human decides

The system uses generative AI capabilities to support analysis and reporting on employment equity data. Outputs inform human decision-makers who determine how to act on the insights produced.

Government of Canada AI Register — 2526-ESDC-EDSC-001

Understanding (Semantic AI)

Human decides

Natural language processing is used to extract meaning from employment equity data sources, enabling richer querying and analysis of DEI metrics across employers and sectors. Outputs are advisory and reviewed by GC employees.

Government of Canada AI Register — 2526-ESDC-EDSC-001

Outputs

A recommendation or prediction

Anonymized data

The system produces deeper insights and analyses into DEI metrics — including representation rates and pay gap trends by employer, sector, and location — that support human decision-makers in identifying employment barriers and assessing employer accountability. These are advisory outputs reviewed by GC employees.

Government of Canada AI Register — 2526-ESDC-EDSC-001

Operational data

Anonymized data

The system automates and streamlines the collection and analysis of employment equity reporting data, producing structured DEI metrics and aggregated employer accountability records for use by government decision-makers and for public exploration via the EquiVision website.

Government of Canada AI Register — 2526-ESDC-EDSC-001

Run by

Employment and Social Development Canada (ESDC)

The federal department responsible for deploying and operating the AI-enhanced EquiVision system to support employment equity analysis and employer accountability under federal regulation.

Government of Canada AI Register — 2526-ESDC-EDSC-001

Built by

Microsoft

Microsoft is the technology vendor supplying the AI capabilities (including generative AI and natural language processing tools) and data infrastructure used to enhance the EquiVision platform. The system is developed in part by ESDC and in part by this vendor.

Government of Canada AI Register — 2526-ESDC-EDSC-001

Kept for

Not stated by the Helpful Places.

Shared with

Available to the accountable organization

GC employees at ESDC are the primary users of the system and have access to the AI-generated DEI analysis outputs. The system is designed to empower internal decision-makers and federally regulated employers and business sectors who can explore data on the EquiVision platform.

Government of Canada AI Register — 2526-ESDC-EDSC-001

Stored

Stored on 3rd Party Cloud

Data is processed and stored using Microsoft infrastructure, as indicated by the data sources field listing Microsoft as a primary data source provider alongside ESDC's in-house systems.
Duration: Not specified in the register

Government of Canada AI Register — 2526-ESDC-EDSC-001

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 UseUsers are informed that AI is used in this system, as confirmed in the Government of Canada AI Register. Individuals affected by employment equity data collection and analysis should be able to learn about the AI's role through ESDC's public transparency mechanisms and the EquiVision platform.
Right to Algorithmic TransparencyAs a federally regulated system, affected parties may request information about how the AI system analyzes employment equity data through ESDC's standard access-to-information procedures. The Government of Canada AI Register entry provides baseline transparency about the system's purpose and capabilities.

Risks and safeguards

Societal & cultural harmAI-driven analysis of DEI data could perpetuate or amplify existing biases in employment equity reporting if the underlying data reflects historical discrimination or if the model introduces new biases.Safeguard: The system is in development with ESDC oversight; it is designed specifically to identify employment barriers and foster accountability, with primary users being GC employees who review outputs before any accountability actions are taken.
Reputational harmAutomated analysis and public reporting of employer DEI metrics could result in inaccurate or unfair characterizations of employers if the AI misclassifies or misinterprets employment equity data.Safeguard: The system targets GC employees as primary users who review AI-generated insights; the system is still in development and has not yet reached full production deployment, providing an opportunity to establish accuracy review procedures before public-facing outputs are finalized.