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Artificial Intelligence Tip Sheet (view source)
Revision as of 14:42, 24 September 2025
, 14:42, 24 September 2025no edit summary
* Practice Data Minimization: Only collect and use the data that is absolutely necessary for the system’s purpose. Every extra data point increases the risk of introducing bias and privacy violations.
* Practice Data Minimization: Only collect and use the data that is absolutely necessary for the system’s purpose. Every extra data point increases the risk of introducing bias and privacy violations.
* Establish Clear Data Governance: Appoint clear ownership and accountability for the data's quality, lifecycle, and ethical use.
* Establish Clear Data Governance: Appoint clear ownership and accountability for the data's quality, lifecycle, and ethical use.
==== Key Resources: ====
* [https://www.tbs-sct.canada.ca/pol/doc-eng.aspx?id=32601 Guideline on Service and Digital (See Appendix C: Standard on Enterprise Data)]
* [https://www150.statcan.gc.ca/n1/pub/12-586-x/12-586-x2017001-eng.htm Statistics Canada's Quality Assurance Framework]
* [https://www.priv.gc.ca/en/privacy-topics/privacy-laws-in-canada/the-personal-information-protection-and-electronic-documents-act-pipeda/p_principle/ PIPEDA fair information principles - Office of the Privacy Commissioner of Canada]
=== 2. Developing & Updating Policies ===
When creating or changing policies that involve AI, assess its impact on people from the very beginning.
* Conduct an Algorithmic Impact Assessment (AIA) to determine the system's risk level. This must include an explicit assessment of the proposed data sources for potential bias.
* Incorporate foundational legislation like the Accessible Canada Act, the United Nations Declaration for the Rights of Indigenous People and the Employment Equity Act in the policy analysis.
* Challenge policy assumptions in areas like risk scoring, eligibility determination, and the underlying assumptions of the policy itself that could lead to discriminatory outcomes.
==== Key Resources: ====
* [https://www.canada.ca/en/government/system/digital-government/digital-government-innovations/responsible-use-ai/algorithmic-impact-assessment.html Algorithmic Impact Assessment (AIA) Tool]
* [https://laws-lois.justice.gc.ca/eng/acts/a-0.6/ Accessible Canada Act]
* [https://www.justice.gc.ca/eng/declaration/index.html United Nations Declaration on the Rights of Indigenous Peoples Act]
* [https://laws-lois.justice.gc.ca/eng/acts/e-5.401/ Employment Equity Act]
* [https://www.canada.ca/en/government/system/digital-government/digital-government-innovations/responsible-use-ai/guide-peer-review-automated-decision-systems.html Guide to Peer Review of Automated Decision Systems - Canada.ca]
=== 3. Designing Programs & Services ===
Embed fairness directly into the architecture of any AI-powered program.
* Ensure meaningful human oversight and provide plain-language notices to users explaining how the AI works and how to challenge a decision.
* Include systemically marginalized groups in all phases, from initial design to final testing and implementation.
* Audit all AI tools for equity, especially internal systems, to ensure they do not perpetuate bias and barriers.
* Embed accessibility and bias mitigation throughout design, testing, and implementation.
==== Key Resources: ====
* [https://www.tbs-sct.canada.ca/pol/doc-eng.aspx?id=32592 Directive on Automated Decision-Making]
* [https://www.tbs-sct.canada.ca/pol/doc-eng.aspx?id=32603 Policy on Service and Digital]
* [https://accessible.canada.ca/creating-accessibility-standards/accessible-and-equitable-artificial-intelligence-systems-technical-guide Accessible and Equitable Artificial Intelligence Systems - Accessibility Standards Canada]
* [https://www.canada.ca/en/government/system/digital-government/digital-government-innovations/responsible-use-ai/guide-peer-review-automated-decision-systems.html Guide to Peer Review of Automated Decision Systems]
=== 4. Procuring Technology & AI Systems ===
* Require conformance with accessibility standards in all procurement contracts. This includes both the hardware/software standards and the specific standards for AI.
* Require potential vendors to disclose the sources of their training data, their data-cleaning methods, and the steps they took to mitigate bias in their models.
* Require conformance with accessibility standards in all procurement contracts, including ICT and AI-specific standards.
* Mandate an external, independent peer review for any high-impact AI system before a contract is finalized and before deployment.
==== Key Resources: ====
* [https://accessible.canada.ca/creating-accessibility-standards/canasc-en-301-5492024-accessibility-requirements-ict-products-and-services CAN/ASC - EN 301 549:2024 Accessibility requirements for ICT products and services (EN 301 549:2021, IDT) - Accessibility Standards Canada]
* [https://accessible.canada.ca/creating-accessibility-standards/asc-62-accessible-equitable-artificial-intelligence-systems ASC-6.2 Accessible and Equitable Artificial Intelligence Systems - Accessibility Standards Canada]
* [https://www.tbs-sct.canada.ca/pol/doc-eng.aspx?id=32592 Directive on Automated Decision-Making]
=== 5. Managing & Supervising Teams ===
As a leader, help build your team's capacity to work with AI ethically and inclusively.
* Obtain training on bias, equity, and accessible design principles.
* Actively engage employees from systemically marginalized groups to gather feedback on AI tools and processes.
=== 6. Working in Human Resources (HR) ===
Exercise caution to prevent AI from creating discriminatory barriers in recruitment, promotion, or talent management.
* Do not use AI in hiring or promotion unless:
*# AI training data was audited and corrected for biases related to gender, race, disability, and other protected grounds.
*# The system has been independently audited for equity impacts in a Canadian context.
*# Interfaces are fully bilingual and accessible.
* Ensure AI-enabled learning or assessment platforms are barrier-free and have been co-designed with meaningful consultation from systemically discriminated groups.
* Conduct an Algorithmic Impact Assessment for any system that automates decisions affecting employees' rights or careers.
==== Key Resources: ====
* [https://www.canada.ca/en/public-service-commission/services/appointment-framework/guides-tools-appointment-framework/ai-hiring-process.html Artificial intelligence in the hiring process - Canada.ca]
* [https://www.canada.ca/en/public-service-commission/services/public-service-hiring-guides/enhance-fairness-reduce-bias-assessment-tools.html Enhance fairness and reduce bias in the content of assessment tools - Canada.ca]
* [https://laws-lois.justice.gc.ca/eng/acts/e-5.401/ Employment Equity Act]
* [https://accessible.canada.ca/creating-accessibility-standards/accessible-and-equitable-artificial-intelligence-systems-technical-guide Accessible and Equitable Artificial Intelligence Systems - Accessibility Standards Canada]
* [https://www.canada.ca/en/government/system/digital-government/digital-government-innovations/responsible-use-ai/algorithmic-impact-assessment.html Algorithmic Impact Assessment (AIA) Tool]
=== 7. Supporting Indigenous Rights & Self-Determination ===
Ensure AI systems respect the rights and data sovereignty of Indigenous Peoples.
* Align AI systems with the principles of the the United Nations Declaration on the Rights of Indigenous Peoples Act and the OCAP® Principles (Ownership, Control, Access, and Possession).
* Include Indigenous Peoples, leaders, and networks in the design, procurement, and governance of any AI system that may affect them.
* Avoid automated systems that could reinforce or create new systemic inequities for Indigenous Peoples.
==== Key Resources: ====
* [https://fnigc.ca/ocap-training/ The First Nations Principles of OCAP®]
* [https://www.justice.gc.ca/eng/declaration/index.html United Nations Declaration on the Rights of Indigenous People Act]
=== 8. Monitoring, Evaluating & Auditing ===
Continuously assess the real-world impact of AI systems to ensure they remain fair and effective over time.
* Assess AI-related impacts using GBA Plus assessments, program evaluations, and privacy and accessibility audits.
* Continuously monitor system outputs for unexpected or inequitable results. If an AI system starts flagging a specific demographic at a higher rate, it requires immediate investigation.
* Report transparently on AI risks, mitigation efforts, and any updates made to the system.
* Establish clear feedback and redress mechanisms so users can challenge an automated decision
==== Key Resources: ====
* [https://www.tbs-sct.canada.ca/pol/doc-eng.aspx?id=32592 Directive on Automated Decision-Making- Canada.ca]
* [https://www.canada.ca/en/women-gender-equality/gender-based-analysis-plus.html Gender-based Analysis Plus (GBA Plus) - Canada.ca.]
=== 9. Engaging the Public & Partners ===
Foster public trust through clear communication and meaningful collaboration.
* Provide plain language explanations of what AI tools do and how they impact people.
* Ensure all outreach is culturally relevant, linguistically accessible, and inclusive of marginalized communities.
* Co-design AI systems with systemically marginalized groups and by recognizing that persons with disabilities must be involved in creating policies and services that affect them.
==== Key Resources: ====
* [https://accessible.canada.ca/creating-accessibility-standards/asc-62-accessible-equitable-artificial-intelligence-systems ASC-6.2 Accessible and Equitable Artificial Intelligence Systems - Accessibility Standards Canada]
=== 10. Designing Training & Communications ===
Create educational materials that are accessible and inclusive.
* Use inclusive and accessible formats like screen-reader-compatible documents, captioned videos, and translated materials.
* Co-create content with systemically marginalized groups to ensure it is relevant and respectful.
* Go beyond "performative" training. Invest in meaningful education that helps public servants understand and confront systemic racism, ableism, and colonialism.
==== Key Resources: ====
* [https://accessible.canada.ca/creating-accessibility-standards/asc-62-accessible-equitable-artificial-intelligence-systems ASC-6.2 Accessible and Equitable Artificial Intelligence Systems - Accessibility Standards Canada]
=== 11. For All Public Servants: Your Personal Responsibility ===
Regardless of your role, you have a part to play in ensuring the responsible use of AI.
* Seek out training on data literacy, AI ethics, and unconscious bias. Understand the basics so you can ask critical questions.
* If you are asked to work on an AI project, ask "What are the risks of bias in this data?" and "Who might be negatively impacted by this system?"
* Actively consult with systemically marginalized groups and colleagues from different levels, locations and classifications. Their insights are invaluable for spotting potential issues.
==== Key Resources: ====
* [https://www.canada.ca/en/government/system/digital-government/digital-government-innovations/responsible-use-ai/gc-ai-strategy-overview.html AI Strategy for the Public Service]
* [https://www.canada.ca/en/government/system/digital-government/digital-government-innovations/responsible-use-ai/principles.html Guiding principles for the use of AI in government]
* [https://www.canada.ca/en/government/system/digital-government/digital-government-innovations/responsible-use-ai/guide-use-generative-ai.html Guide on the use of generative artificial intelligence]
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