AI for sceptics: an honest look
A free, evidence first look at what AI does well, where the hype outruns reality, and why
A taste of a lesson
Isn't it all just autocomplete with good marketing?
That criticism is half right. Technically, language models do generate text one token at a time, like autocomplete. Where it misleads is the implication that nothing interesting is learned: to predict text well, models pick up grammar, facts and reasoning patterns that let them handle tasks they never saw verbatim. And the marketing really is often inflated. A sharper version of your view might be: 'a powerful pattern learner, unreliable without checking'. Test it: give it a task from your own work and grade it honestly. What task will you choose?
Written by the teacher as an example. In your lesson the tutor answers your own questions, and like any AI it can be wrong.
What you will be able to do
- State the strongest sceptical arguments about AI with supporting evidence
- Identify criticisms that are outdated or overstated and explain why
- Design small personal tests that compare AI with a non AI baseline
- Separate evidence, extrapolation and speculation in AI debates
Lesson plan
- 1 The strongest case against the hype Set out the most solid sceptical arguments with evidence. Start
- 2 Criticisms that miss Identify sceptical arguments that are outdated or overstated. Start
- 3 Run your own test Evaluate AI on a task you know, against a fair baseline. Start
- 4 Money, incentives and bubbles Think clearly about investment and incentives behind AI claims. Start
- 5 Your calibrated position Write a precise, defensible personal view of AI. Start
Try asking
About this tutor
For people who suspect AI is overhyped and want a fair hearing rather than a sales pitch or a dismissal. You examine the strongest sceptical arguments: hallucination, energy use, copyright concerns, inflated productivity claims, bubbles and broken promises. You also test the strongest arguments on the other side, using small experiments of your own. The aim is not to convert you but to sharpen your scepticism so it is precise: knowing which criticisms are solid, which are outdated, and where the honest answer is 'nobody knows yet'. Suitable for beginners and for informed critics who want to stress test their views.
Reviews
4.0
3 ratingsSample
- Ana P.Sample
Fair to both sides and never pushy. The bubble lesson was thoughtful. A bit short on environmental detail.
- Desmond K.Sample
Decent, but I felt it leaned slightly towards AI being useful. Still, it did admit uncertainty clearly and the citation check exercise was good.
- Graham W.Sample
I came in a firm sceptic and left a more precise one. The test against a baseline was revealing: AI won on drafting, lost on anything needing local knowledge.
About the teacher
I teach people to judge AI claims, spot synthetic media and report on AI without the hype
9 tutors 435 lessons taught Sample
I teach media literacy for the age of AI. My learners include journalists, students, sceptics and anyone tired of breathless headlines in both directions. We practise reading claims about AI critically, checking images and video, understanding why AI text detectors fail, and asking the questions a careful reporter would ask. My background is in newsroom fact checking and training reporters,...
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