How to explain Generative AI in the classroom • Hacker News Board

Re: How to explain Generative AI in the classroom

#11

Post by crooked-v » Sat, Jan 31, 2026, 4:05 AM UTC

peyton wrote: post #4

This is great and has lots of practical stuff. Some of the takeaways feel over-reliant on implementation details that don’t capture intent. E.g. something like “the LLM is just trying to predict the next word” sort of has the explanatory power of “your computer works because it’s just using binary”—like yeah, sure, practically speaking yes—but that’s just the most efficient way to lay out their respective architectur…

Complicated-enough LLMs also are aboslutely doing a lot more than "just trying to predict the next word", as Anthropic's papers investigating the internals of trained models show - there's a lot more decision-making going on than that.

Re: How to explain Generative AI in the classroom

#12

Post by mmooss » Sat, Jan 31, 2026, 4:26 AM UTC

narrator wrote: post #7

That lesson plan is a good practical start. I think it misses the very big picture of what we've created and the awesomeness of it. The simplest explanation I can give is we have a machine that you feed it some text from the internet, and you turn the crank. Most machines we've had previously would stop getting better at predicting the next word after a few thousand cranks. You can crank the crank on an LLM 10^20 tim…

> awesomeness

They should learn to think for themselves about the whole picture, not learn about 'awesomeness'.

Re: How to explain Generative AI in the classroom

#13

Post by majormajor » Sat, Jan 31, 2026, 4:58 AM UTC

crooked-v wrote: post #11

peyton wrote: post #4

This is great and has lots of practical stuff. Some of the takeaways feel over-reliant on implementation details that don’t capture intent. E.g. something like “the LLM is just trying to predict the next word” sort of has the explanatory power of “your computer works because it’s just using binary”—like yeah, sure, practically speaking yes—but that’s just the most efficient way to lay out their respective architectur…

Complicated-enough LLMs also are aboslutely doing a lot more than "just trying to predict the next word", as Anthropic's papers investigating the internals of trained models show - there's a lot more decision-making going on than that.

> Complicated-enough LLMs also are aboslutely doing a lot more than "just trying to predict the next word", as Anthropic's papers investigating the internals of trained models show - there's a lot more decision-making going on than that.

Are there newer changes that are actually doing prediction of tokens out of order or such, or are this a case of immense internal model state tracking but still using it to drive the prediction of a next token, one at a time?

(Wrapped in a variety of tooling/prompts/meta-prompts to further shape what sorts of paragraphs are produced compared to ye olden days of the gpt3 chat completion api.)

Re: How to explain Generative AI in the classroom

#14

Post by thfuran » Sat, Jan 31, 2026, 4:59 AM UTC

Uehreka wrote: post #3

I couldn’t find it easily, what age range is this intended for? The images make it seem elementary-school-ish, but I’m not sure if elementary school kids have the foundations for interpreting scatterplots, let alone scatterplots with logarithmic axes. I’ve been out of education for a while though, so maybe I’m misremembering.

Logarithms are high school.

Re: How to explain Generative AI in the classroom

#15

Post by TimorousBestie » Sat, Jan 31, 2026, 5:17 AM UTC

I wonder how utterly broken the next generation will be, having to grow up with all this stuff.

Us millennials didn’t do so great with native access to the internet, zoomers got wrecked growing up with social media. . . It’s rough.

Re: How to explain Generative AI in the classroom

#16

Post by augusteo » Sat, Jan 31, 2026, 5:21 AM UTC

The "learning through making" approach is really good. When I've explained LLMs to non-technical people, the breakthrough moment is usually when they see temperature in action. High temperature = creative but chaotic, low temperature = predictable but boring. You can't just describe that.

What I'd add: the lesson about hallucinations should come early, not just in the RAG module. Kids (and adults) need to internalize "confident-sounding doesn't mean correct" before they get too comfortable. The gap between fluency and accuracy is the thing that trips everyone up.

Re: How to explain Generative AI in the classroom

#17

Post by whattheheckheck » Sat, Jan 31, 2026, 6:06 AM UTC

narrator wrote: post #7

That lesson plan is a good practical start. I think it misses the very big picture of what we've created and the awesomeness of it. The simplest explanation I can give is we have a machine that you feed it some text from the internet, and you turn the crank. Most machines we've had previously would stop getting better at predicting the next word after a few thousand cranks. You can crank the crank on an LLM 10^20 tim…

They stole everything from the internet and disregarded copyright laws lol

Re: How to explain Generative AI in the classroom

#18

Post by void-star » Sat, Jan 31, 2026, 6:15 AM UTC

narrator wrote: post #7

That lesson plan is a good practical start. I think it misses the very big picture of what we've created and the awesomeness of it. The simplest explanation I can give is we have a machine that you feed it some text from the internet, and you turn the crank. Most machines we've had previously would stop getting better at predicting the next word after a few thousand cranks. You can crank the crank on an LLM 10^20 tim…

Groan…

Re: How to explain Generative AI in the classroom

#19

Post by superfluous_g » Sat, Jan 31, 2026, 6:25 AM UTC

sdwr wrote: post #10

I think this is a backwards approach, especially for children. Gen AI is magical, it makes stuff appear out of thin air! And it's limited, everything it makes kinda looks the same And it's forgetful, it doesn't remember what it just did And it's dangerous! It can make things that never happened Starting with theory might be the simplest way to explain, but it leaves out the hook. Why should they care?

Getting folks to care is essential in my experience. In coaching adults "what's in it for me?" is the end of my first section and forms the basis of their first prompt. Also how I cover risk - ie. "How do I not damage my credibility?". If you're asking people to break habits and processes, you've got to make them want to.

That said, the hands on approach here is great and also foundational in my experience.

Re: How to explain Generative AI in the classroom

#20

Post by empressplay » Sat, Jan 31, 2026, 7:34 AM UTC

The vast majority of schools in North America don't allow teachers or students to download and run software on school computers (let alone AI models), so I don't entirely know who the audience is for this. I suppose home users? Maybe it's different in the UK.