> Why bother learning to retain any information when AI knows everything and can recall it in a split second.
This is a real question though. One I've been asking since the early 00s. Learning means something different than it did in decades previous. Merely remembering easy to look up facts is not the slam dunk it used to be.
Memorizing facts was never the slam dunk in and of itself, but just a path to something greater, and I don't think that's changed. Think about the most obvious example - what we're doing right now: language. You can only fluently speak and communicate with others because you've memorized, to the point of complete subconscious mastery, a completely ridiculous amount of information and knowledge - thousands of words, countless grammatical nuances, cultural and contextual connotations/implications, and much more.
Imagine trying to speak without having this base of knowledge. Even if possible, you'd never be able to use the language in a comparable fashion. And I think this generalizes to basically everything in every domain. If you want to get good at chess, you need to study a ridiculously massive amount of tactics/patterns. If you want to get good at basketball, you need to simple practice dribbling and shooting a ball into a hoop for many thousands of hours, and so on.
The whole point of the memorization is to make it feel like it's not memorized. Like when you see these words, or come up with your own - it requires absolutely zero effort. There's nothing magical there. It's the exact same way that a master chess player can easily play a competent game of chess with 1 minute on their clock or while blindfolded.
If, and as, we start doing away with the rote, I'd expect we're going to see worse and worse outcomes. Arguably, this is already happening as Western education is continually 'rethought' while China rockets ahead of everybody with an education system that looks very much like a more centralized version of the US education system of 70 years ago.
You hit the nail on the head. It sounds silly to say, but it simply is useful to know things. And to know things, you "memorize" them. More specifically, you build neural pathways as the information becomes better known to you, and which can be activated quickly. This is why I maintain a massive Anki deck for anything I find curious and want to remember, inspired by Michael Nielsen (https://augmentingcognition.com/ltm.html) and others.
Even if AI is very powerful, it is very obvious that someone actually knowledgable in a given domain can leverage AI more usefully than someone without that base of knowledge. And to be actually knowledgeable, as opposed to vaguely familiar with terms, takes significant effort over time. Luckily we have tools like spaced repetition that make that effort easier.
The last thing I'd add is that it's useful to know lots of things in various domains. Much like an LLM, our brains draw connections between disparate things which we know well, in the process of diffuse mode thinking.
Was learning easy to look up facts ever slam dunk useful?
It had its place in the 80s when looking up involved at least finding the right book. But that time was already on the way out in the 00s. My impression was more that education likes to ask for facts because they are easy to test for.
What you really want to teach are concepts and broad strokes. Nobody needs to know on which weekday the Soviet Union collapsed, but an understanding of the causes of the collapse is useful. Similarly, you don't need to know the speed of light to more than one digit of precision, but knowing the role of the speed of light as the speed at which information can travel through space is useful
That kind of knowledge also continues being useful in the age of AI. It allows you to see the connections in the world, and know which questions you even have to ask
You need to be able to hold facts in your own working memory while you think about them. If you do this with the same facts, and think through different combinations, they’ll stick in your memory for longer.
I never sat down to memorise trivia about the Roman calendar, but I know Julius Caesar was assassinated on the 15th, the ides of March, because of repeated exposure while thinking things through.
It seems like old assessment techniques could luck in to testing comprehension, because the people who understood things would also remember them. This devolved into the recall being seen as the goal, instead of as proxy measure of something harder to test.
Hey you wrote out my general thoughts on the subject pretty damn well :)
>> Why bother learning to retain any information when AI knows everything and can recall it in a split second.
> This is a real question though.
Is it? Why bother to learn how to add 2 numbers when you can just use a calculator.
> Learning means something different than it did in decades previous.
Not really. This is just the acquisition of a new tool. It can possibly be incorporated into education like how calculators were used in the 00s/90s, but you must know how to do the work without the tool.
Once smart glasses with displays or just talking to Ai in your earbuds becomes humanly ubiquitious then I believe the game changes. As long as it's 100% correct humans become know it alls.
I hooked up my local LLM with zim-tools and a 120GB copy of Wikipedia. With some very strict instruction it's turned into a bar-trivia machine, it can answer factual questions faster than I can look them up and it's all offline.
The fun starts when you ask it more complicated questions like 'i have a device that communicates with microwaves and draws a maximum of 20mA at 12v, is it safe for use near humans?' It will look up microwave safety, ionizing and non-ionizing radiation, workplace exposure limits and eventually come up with 1/4W is already safe and the device likely is not a 100% efficient microwave transmitter.
Don't agree. If you know no facts, you'll be unable to think even the most basic thoughts. The more you know, the deeper your thinking can be as well as the more subtle.
For every fact you learn there is a necessary context and numerous exceptions when it's applied in other contexts. If you expect AI to spit all relevant facts at you every time you're clueless, you will have no idea when AI is wrong or lying. You will have to trust everything AI (or its owner) tells you.
Yes. Fact fluency allows higher level of abstraction. This is very clear in the case of mathematics - try doing algebra without having your addition and multiplication tables memorized, kids who fail algebra are often missing these basic facts, along with other basics like order of operations.
It's not just math either. Try to be an electrician without memorizing the basic principles of electricity and how they interact. You're going to have a bad time.
By induction we can see how this scales upwards, basically infinitely, to higher and higher levels of thinking.
I think this is mostly compounding confidence at play that unlocks your mind to be more fluid when faced with a task to do/problem to solve that actually requires skill (not just following a series of known steps). It’s like public speaking (unless you have really bad stage fright) you generally will give a better presentation if you really know your stuff, or at least will be less nervous allowing yourself to get into that flow state.
> Try to be an electrician...
> By induction...
Well played.
I think the shift is in part from learning behavior indicating an ability to apply (‘I wanted to do something so bad I went to the library/college/etc.!’), to the free availability of knowledge leading to a delinkage of knowledge v.s. the ability to apply knowledge and get a desired outcome.
AI can really help the outcome part (by just doing it for you), so for better or worse I see that delinkage continuing.
People who bother to actually learn while using AI will have an edge on those shovel slop, but there’s clearly a difference from previous eras.