The course

The tools everyone calls artificial intelligence are machines, and machines can be understood: what goes in, what comes out, what got decided on the way, and by whom. This course builds that machine in front of you, one part per lesson, until you hold the complete map. No mathematics beyond what fits on a napkin, and no vocabulary left undefined. Every lesson earns one part of the machine and writes one line of fine print underneath it, the thing that part cannot do. Anyone can tell you what these tools promise; the fine print is the course. And every lesson comes as two videos on one page, the same class twice. The Abbreviated runs fifteen to twenty-some minutes, every picture of the full lesson at a faster walk. The Explained runs twenty-some to forty, the same pictures with room to breathe, two voices trading the material. Nothing lives in one cut that is missing from the other, so choose by the time you have today, and switch freely; plenty of people watch the short cut first and come back to the long one when a part won't let go of them.

Curriculum

9 Chapters · 22 Lessons

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      Start here: how this course works

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      E01 · Everything Is Numbers

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      E02 · The Pile That Reads You Back

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      E03 · Why Your AI Doesn't Think

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      E04 · Where Does The Next Word Come From

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      E05 · What Did The Model Actually Read

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      E06 · Is The New One Actually Better

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      E07 · Where Confident Wrong Answers Come From

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      E08 · What Did The Model Just Forget

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      E09 · Anchor Your AI To A Document

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      E10 · When AI Thinks Step By Step

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      E11 · The Six Dimensions Of Every Prompt

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      E12 · The Energy And Waste Of Using AI

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      E13 · What's Free For You, What Costs Money

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      E14 · Pay Less, Depend Less

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      E15 · Tool Choice As Values Choice

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      E16 · The Privacy Floor

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      E17 · Cognitive Offloading And Your Own Mind

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      E18 · AI As Something You Check

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      E19 · When The Machine Runs Without You

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      E20 · Model Collapse And What Comes Next

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      The glossary: every term, in the course's own words

You could learn this from the people selling it to you.

Most AI instruction today is written by the industry that sells AI, and the incentive shows. A vendor's course succeeds when you adopt their tool. This course succeeds when you can judge any tool, including deciding that one is wrong for you, which is a lesson no vendor can afford to teach. Here there is no product behind the curtain. What is for sale is the understanding itself, whole, fine print included.

Diego Bonilla, Ph.D.

Full Professor of Communication Studies The work I do has changed its name four times. When I started teaching it, in the late nineties at Syracuse, it was called computer literacy. Then it was information literacy, and I created a university course on privacy that I have now taught for over twenty years. Then it was digital literacy: in 2007 and 2009 I served on the ETS committee at Princeton that set the passing standard for the national assessment, back when the phrase needed explaining, and from 2014 to 2016 I was the California State University system's ICT Literacy Ambassador. Now it is called AI literacy, and within a year of ChatGPT's release I was directing the faculty community on AI literacy at my university. Four names, one job: helping people not be at the mercy of the newest machine. I have also worked on the other side of the counter. In 2000 I began making films that a machine assembles, differently for every viewer; the first of them took first prize at the Moscow International Film Festival, two decades before the industry shipped a generative model. A generative video poem I made with a UNAM poet was selected for the field's definitive anthology and exhibited in Sacramento and Istanbul, and in 2025 my VR work took an award at an AI film festival. And I study these systems as a scholar: my doctorate measured what a machine can infer about a person from the traces they leave, and my recent published work is on AI and elections, and on how these models represent cultures that are not the ones they were trained on. The systems this course explains run under my hands daily, in production; they made the pictures and the voices you will see inside. The vendors began teaching AI literacy two years ago, because before that there was nothing to sell. I am not against them. I am simply not one of them, and that is the difference you are buying. Ph.D., Syracuse University · Full Professor, Sacramento State · ETS iSkills committee, Princeton, 2007 and 2009 · CSU ICT Literacy Ambassador, 2014-2016 · Directed the AI Literacy faculty community, 2023-2026 · First prize, Moscow International Film Festival, for a machine-assembled film · Published scholarship on AI, elections, and cultural representation, in two languages

The receipts

A course about checking claims should survive being checked. Every reference on every lesson page is a live link, verified by hand before it was allowed to stand; the ones that could not be verified say so, with the reason. The course ends in a glossary of 237 terms defined in the course's own words, not the industry's. And every lesson closes with a test you can run this week, in your own field, on your own materials, at no cost. You leave able to use these tools, and able to tell when one is wrong, which is the half nobody sells.

The whole course, both cuts of every lesson.

Twenty lessons that build the machine behind AI part by part, in plain language, with the fine print read aloud.

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