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Comment by colinrand | Hacker News Reader

I always get very skeptical with putting more technology in the classrooms (at least here in the US). The primary problem is funding and too many kids for a single teacher. Educational innovation comes in with a bang and out with a whimper when the study turns out to be flawed, often quite severely.

I'm sure LLMs can augment learning in some settings, esp in higher ed, but putting more computer time for kids learning basics (I mean K-8 mostly) I hope is handled more carefully than things like Quizlet...

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One of my high school teachers had a quote she was fond of repeating:

"Education requires three things: a teacher, a student, and a stump. Unwilling to change the first, unable to change the second, educators spend all their money on the third."

> I'm sure LLMs can augment learning in some settings, esp in higher ed

LLMs are great explainers of known theory. They can adapt to the level of the user and illustrate with concrete examples. They have infinite patience, there is no pressure.

> LLMs are great explainers of known theory.

When they don't lie. When they don't make up citations that don't exist.

I think GPT-4 is moderately useful for software development, and I use it daily, but I have to check even very minor things, and having ~25 years of programming experience means I can do that intuitively. A kid doesn't have that.

> When they don't lie. When they don't make up citations that don't exist.

I think this will be close to 0 of a problem when explaining to a HS biology student something like, what a mitochondria does or what mitosis is. It only fails (increasingly rarely) when you push the boundaries of human knowledge.

That assumes that the asker doesn't then ask follow-up questions that do probe beyond the could've-been-a-Wikipedia-page starting point. And I don't know about you, but how `structlog` should be configured had better not be "the boundaries of human knowledge". As I experienced yesterday evening, GPT-4 doesn't even do that right without human assistance.

LLMs are useful tools. They are dramatically less useful if you can't detect bullshit. By definition, a student is poorly equipped to do so, and moreso if allowed to atrophy in the area of research capacity because they can just ask an LLM. (A pocket calculator is a good analogy--life carries much less friction when you can efficiently do arithmetic and basic algebra in your head, because the affordances of dragging out a calculator to know how to minimize the change you get back are bad.)

GPT4 with no tuning produces less bullshit than 99% of teachers.

I don't think it can. I have some experience in teaching and one of the worst issues I initially had was that you can't believe how messed the knowledge can be in heads of the kids. They literally mess everything – topics, words, culture, personal experience. Everything. To teach kids effectively you have to have a lot of background knowledge – from their family background to the info from teacher in previous class and you have to adapt constantly.

People who are talking about automation of education are grown up people who think that all people think structurally and just lack the specific knowledge. Kids actually don't do it.

Honestly, I think the primary problem in the US is parents completely offloading the responsibility of educating their kids onto the teacher. You need to have the appropriate push and environment at home for a successful education. You would never see that in South or East Asia.

This is a very economically driven situation in the US. Upper middles load their kids up non stop with educational stuff outside of the schools, but the lower middle on down can't afford this (it's really expensive) and school often functions primarily as child care.

I think you’re discounting relatively cheap fixes like mindset and pushing your kids to succeed at home. There’s plenty you can do besides throwing money at a problem. A lot of first generation Indian and Chinese immigrants exclusively rely on those methods, and this is usually after a day of working long hours at intensive jobs.

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