Curated reading and learning materials
A hand-picked selection of AI literacy resources — prioritising quality, independence, and accessibility for non-technical readers.
Structured approaches to understanding and teaching AI literacy, developed by researchers and educational organisations.
A framework developed by AI researchers and educators identifying the five core concepts every student should understand about artificial intelligence.
Why it matters: Provides a structured, research-backed vocabulary for teaching AI concepts from primary school through secondary education.
Curriculum materials developed by MIT to introduce AI concepts to secondary students, with an emphasis on societal implications alongside technical basics.
Why it matters: Free, academically rigorous materials that go beyond technical explanations to examine the social and ethical dimensions of AI.
Resources for educators integrating AI literacy into classroom and curriculum contexts.
A free online course teaching AI concepts without requiring a technical background, developed by Reaktor and the University of Helsinki.
Why it matters: One of the most successful public AI literacy initiatives globally, with clear explanations of how AI works and what it cannot reliably do.
A coalition providing guidance and policy frameworks for schools integrating AI literacy into their curricula.
Why it matters: Addresses the institutional and policy dimension of AI in education, beyond the individual classroom level.
Rigorous, independently produced research on the state of AI, its societal implications, and governance approaches.
An annual report tracking the state of AI development across research, industry, policy, and society — rigorously sourced.
Why it matters: The most comprehensive annual overview of AI progress and its societal implications, maintained by an independent academic institution.
A repository of AI policies, principles, and research from OECD member countries.
Why it matters: Essential for understanding how governments around the world are approaching AI regulation and governance.
The best accessible materials for non-technical readers who want to go deeper — videos, books, and newsletters.
A visual explanation of transformer architecture and how language models work, produced without requiring a mathematics background.
Why it matters: The clearest visual explanation of LLM architecture available to non-specialists.
A newsletter and book examining overhyped AI claims and explaining what AI can and cannot reliably do.
Why it matters: One of the most rigorous public-interest resources for evaluating AI claims accurately and skeptically.