The Universal AI Literacy Framework was developed by Leo S. Lo and introduced in the 2025 preprint AI Literacy for All: A Universal Framework. It supports learning design across different educational and professional settings.
What should AI literacy education cover?
The Universal AI Literacy Framework describes a broad foundation for engaging with AI. Each component has four progressive levels, with descriptors and rubrics that can inform learning and discussion.
- Technical Knowledge
- Understand how AI systems work and recognize their capabilities and limitations.
- Ethical Awareness
- Examine the values, responsibilities, and ethical questions involved in AI use.
- Critical Thinking
- Question outputs, examine evidence, and judge the appropriateness of AI use.
- Practical Use
- Apply AI in context, assess the results, and adapt your approach.
- Societal Impact
- Consider how AI affects institutions, communities, and public life.
Use the framework to ask better learning questions.
- What does this group already understand or do?
- Which capabilities matter in its actual work?
- What activity would help people practice those capabilities?
- What evidence would show progress?
The level names and descriptors differ by component. The original document provides the full framework, learning progression, and rubrics.
Publication status & reuse
The 2025 document is a preprint. It is licensed CC BY-NC 4.0. Consult the original for attribution and reuse terms; it should not be presented as a validated assessment instrument.
Illustrative learning design
An example for a first-year course.
Ask students to examine an AI-generated explanation of a topic in their course. Connect the activity to all five components:
- Technical Knowledge: Explain how a generated answer can sound convincing while containing errors.
- Ethical Awareness: Discuss privacy, disclosure, and whose perspectives may be missing.
- Critical Thinking: Trace a central claim to evidence and judge whether the source supports it.
- Practical Use: Revise the request and document what changed in the response.
- Societal Impact: Consider how relying on generated explanations changes whose knowledge students encounter.
Use a short reflection to discuss students’ reasoning. Adapt the expectations to the course and learners.
This is an illustrative activity, not a validated assessment or a report of measured learning effects.
How institutions have drawn on the framework.
Leo S. Lo’s Universal AI Literacy Framework has informed AI literacy frameworks and guidance at Penn State, Queen’s University, and Clemson University. Each institution has developed its own approach.
- Penn State: AI Literacy
Connects its flexible institutional framework to Lo’s work and other sources.
- Queen’s University: AI Literacy at Queen’s
Identifies Lo’s framework alongside work from the Digital Education Council and UNESCO in explaining its university approach.
- Clemson University: AI Literacy Framework, version 1 (PDF)
Explicitly credits adaptation from Lo’s framework, EDUCAUSE, and AAC&U rubrics.
These sources document influence and adaptation. They do not establish uniform implementation across every course or unit, or validate the framework as an assessment instrument.
Original preprint and citation
Lo, L. S. (2025). AI literacy for all: A universal framework [Preprint]. University of New Mexico Digital Repository. https://digitalrepository.unm.edu/ulls_fsp/213/.
Read the original source