Connecting Global AI Frameworks to Canadian Campuses

Adopting UNESCO’s human-centric approach to AI literacy, the initiative prioritizes human agency, fundamental rights, and ethical discernment alongside software mechanics.

• Human Agency & Control: Teaches students to critically evaluate when, where, and why automated tools should, or should not, be introduced into academic and professional workflows.
• Ethics & Systemic Impact: Cultivates systematic auditing skills to identify algorithmic bias, protect privacy, evaluate data provenance, and respect intellectual property.
• Pedagogical Standards: Provides faculty and academic leadership with clear guidance to evaluate student submission integrity while embedding domain-specific AI literacy into existing courses.

UNESCO. (2024). UNESCO AI competency framework for students. UNESCO Publishing.

Developed jointly by the OECD and the European Commission (in alignment with international benchmarks like PISA 2029 for incoming secondary students), the AILit Framework defines AI literacy as the combination of technical knowledge, durable skills, and future-ready attitudes needed to thrive in an automated world. The initiative structures learning across four core competency domains:

• Engaging with AI: Recognizing when AI systems are active in daily software, evaluating the accuracy and relevance of generated outputs, and understanding foundational computational capabilities and technical limitations.
• Creating with AI: Collaborating with generative models in creative and technical problem-solving — refining outputs through iterative prompt design while addressing data ownership, attribution, and algorithmic bias.
• Managing AI: Strategically delegating structured tasks to AI systems (such as data synthesis or automated simulation) so human learners can focus on high-level creativity, metacognition, empathy, and complex reasoning.
• Shaping AI: Analyzing how data inputs, system architectures, and policy choices impact society, empowering students to advocate for responsible, human-centred technology design.

OECD & European Union. (2026). Empowering learners for the age of AI: An AI literacy framework for primary and secondary education. OECD Publishing. Download PDF

The initiative maps AI skills directly onto the federal government’s nine foundational workplace competencies, accelerating career readiness for post-secondary graduates:

• Critical Thinking: Training students to question model outputs, identify hallucinations, and cross-reference machine-generated data with primary sources.
• Digital Skills: Advancing past basic computer literacy into prompt engineering, contextual data retrieval, and machine learning tool navigation.
• Adaptability: Preparing graduates to continuously audit, learn, and integrate rapidly shifting software tools as industry standards evolve.
• Problem Solving: Applying hybrid human-AI workflows to complex, open-ended business, humanities, and scientific challenges.
• Communication & Collaboration: Formulating structured, precise human-to-machine prompts while facilitating multidisciplinary teamwork in tech-enabled environments.

Kaufmann, L., Lee, W., Nguyen, C., & Palameta, B. (2024). Skills for Success proficiency levels development: Final report. Social Research and Demonstration Corporation.