Overview
What the framework is trying to do
The Open University framework defines Critical AI Literacy as a context-specific social practice rather than a possession or checklist. It extends conventional AI literacy by asking how AI shapes knowledge, identities, relationships, participation, and epistemic justice.
An equality, diversity, inclusion, and accessibility lens runs through the framework. Students and educators are expected not only to understand and use AI, but also to verify outputs, identify bias, examine power and ownership, consider labor and environmental costs, and make informed decisions about whether and how AI belongs in learning.
Framework structure
Core dimensions or competencies
AI concepts and applications
Understanding AI and GenAI, terminology, robustness, reliability, applications, potentials, and limitations.
Learning and teaching with AI
Authentic assessment, inclusive learning, iterative use, critical evaluation, and cross-source verification.
AI creativity
Creative production paired with bias detection, comparison, critique, and revision.
AI ethics
Accessibility, privacy, security, copyright, bias, consent, misinformation, and responsible action.
AI in society
Environmental impact, exploited labor, ownership, digital divides, global power, workforce effects, and representation.
AI careers
Disciplinary and workplace applications while retaining human skills, ethical judgment, and EDIA principles.
Critical depth
Why this framework is rated Very High
Rated Very High because structural concerns are part of the framework's core design. It explicitly addresses epistemic injustice, power, colonial perspectives, labor exploitation, environmental impact, accessibility, digital divides, and the possibility of redressing unequal power relationships. Verification and human agency are also embedded throughout.
Central
Bias, power, labor, equity, accessibility, environmental impact, epistemic authority, verification, transparency, human agency
Present
Privacy
Limited
Surveillance
Not evident
See the Critical Dimensions Index for dimensions not assigned a stronger classification.
Evidence base
What supports the framework?
Institutional framework informed by critical digital literacy, AI literacy research, EDIA principles, and institutional teaching strategy
Practical use
Especially useful for
Curriculum development, faculty development, assignment design, authentic assessment, EDIA-focused teaching, institutional strategy, and critical AI literacy research.
Evaluation
Strengths and limitations
Strengths
- Integrates critical theory with concrete teaching practices.
- EDIA is built across the framework rather than treated as an optional ethics topic.
- Connects source verification with structural questions about knowledge and power.
- Distinguishes introductory from advanced Critical AI Literacy, including social-justice-oriented action.
Limitations
- It is an institutional version 0.1 framework rather than a validated assessment model.
- Some terminology, strategic references, and examples are specific to the Open University and UK higher education.
- Surveillance is less explicit than other dimensions such as labor, accessibility, and environmental impact.
Portability
How well does it travel?
Moderate–High. The framework's core concepts transfer readily, especially to higher education, but OU-specific strategy, UK terminology, and institutional examples require adaptation.
Source
Citation
Hauck, M., et al. (2025). A framework for the learning and teaching of Critical AI Literacy skills (Version 0.1). The Open University.