Foundations in AI Literacy
Introduction to AI for Teachers and Students, Ethan Mollick and Lilach Mollick
This is a very informative overview of large language models (LLMs) and their impact on work and learning. Ethan Mollick is an expert and pioneer in AI and education, and should be on your radar if you want to stay up to date with the most recent trends.
The AI Pedagogy Project, created by the metaLAB (at) Harvard within the Berkman Klein Center for Internet & Society, provides a starter pack on AI literacy for educators by providing information on key concepts in AI, its capabilities and guidelines for how to critically integrate them into teaching. The informative, optimistic, yet critical approach to AI pedagogies makes this resource valuable.
A Generative AI Primer, by the National Centre for AI, UK
This is an informative, concise and up-to-date guide on current AI technologies that are widely used in higher education. It briefly explains frontier models (e.g., ChatGPT, Microsoft’s Copilot, Google Gemini, etc.) including their capabilities and limitations, provides guidelines for AI assessments and policies, and summarizes various uses of AI by educators and students.
AI on the Fly, by Gamze Yilmaz
These mini series include 1-minute videos for the faculty on the run (or the impatient student) introducing basic concepts in AI. The series is designed for the absolute beginner in AI and includes examples related to social science and humanities. The narration is done using generative voices form Elevenlabs (hence a couple glitches).
What is generative AI and how does it work? – by Mirella Lapata, Professor of natural language processing in the School of Informatics at the University of Edinburgh
This is an engaging and informative video with clear examples on the technical aspects and capabilities of the neural network language models and transformers for non-experts. Dr. Lapata illustrates some of the uses and applications of AI during the talk.
Large language models, explained with a minimum of math and jargon, by Timothy B. Lee & Sean Trott
This is an excellent article that breaks down the basics of large language models, including how neural networks function, using simple explanations with minimal math and technical jargon. The concepts may still seem complex at first, but try to focus on the analogies used to illustrate them.
Awesome Generative AI, by Steven Van Vaerenbergh & contributors
This is a collectively curated list of available up-to-date AI tools ranging from chatbots and search engines to writing assistants and academic research tools. The best way to familiarize yourself with these tools is to play with them. I would start with the first three chatbots - ChatGPT, Gemini and Copilot. These are built using foundation models, meaning they were trained using the largest LLMs available, hence their better-quality performance compared to other tools.