Last revised: May 2026
Gender-Based Analysis Plus (GBA Plus) Alignment Statement
DataPeak is committed to supporting inclusive, equitable, and non-discriminatory outcomes. Our approach aligns with the Government of Canada’s Gender-Based Analysis Plus (GBA Plus) framework, an analytical process used to assess how diverse groups of people may experience systems, policies, and technologies differently, and to identify and mitigate potential barriers or unequal impacts.
1. What is GBA Plus?
Gender-Based Analysis Plus (GBA Plus) is an analytical approach used to support the development of inclusive and responsive initiatives by:
Understanding who is impacted
Identifying differences in how groups experience outcomes
Anticipating and reducing barriers
It is an intersectional framework, meaning it considers a range of identity factors beyond gender, including age, disability, ethnicity, economic status, geography, language, race, religion, and sexual orientation.
GBA Plus is used to challenge assumptions, reduce bias, and improve outcomes across diverse populations.
2. Relevance to AI Systems
AI systems can unintentionally introduce or reinforce bias if data, models, or workflows do not account for diverse populations.
Applying GBA Plus principles to AI systems helps ensure:
Outputs do not disproportionately impact certain groups
Bias in data and processing is identified and addressed
Systems are designed with awareness of diverse user contexts
Outcomes remain fair and non-discriminatory
DataPeak recognizes that minimizing bias and preventing discriminatory outcomes in AI systems is critical, particularly when AI is used to analyze data or support decision-making.
3. DataPeak Alignment with GBA Plus
DataPeak aligns with GBA Plus by supporting inclusive, bias-aware, and transparent practices across its platform, including in the use of AI.
3.1 Bias-Aware AI Workflows
AI outputs can be reviewed, validated, and refined by users
Workflows allow adjustment of inputs and processing steps
Data transformation capabilities support improved data quality
Outcome: Reduces the likelihood of biased or discriminatory outputs.
3.2 Human Oversight and Control
Human-in-the-loop workflows prevent fully automated decision-making
Users can review, approve, or modify outputs
AI is used as a support tool rather than a final decision-maker
Outcome: Prevents unchecked automation that could lead to unequal impacts.
3.3 Transparency and Traceability
Visibility into workflow steps and data transformations
Structured outputs and reporting
Auditability of AI-driven processes
Outcome: Enables identification and mitigation of potential bias.
3.4 Inclusive Data Handling
Support for structured and unstructured data
Flexible workflows across different use cases
Tools to refine and improve data inputs
Outcome: Reduces the risk of incomplete or unrepresentative data influencing results.
4. Commitment to Non-Discrimination
DataPeak is committed to:
Minimizing bias in AI-generated outputs
Preventing discriminatory or unequal outcomes
Supporting equitable use of data and AI technologies
Enabling customers to identify and address bias in their workflows
This aligns with the intent of GBA Plus to ensure that systems and decisions do not create or reinforce barriers for different groups.
Official Government Reference
Gender-Based Analysis Plus (GBA Plus) – Government of Canada
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