A Student's Guide to Writing with ChatGPT

The correct answer, and you'd see it if folks paid attention to the constant linkedin "AI researcher/ML Engineer job postings are up 10% week over week" banners, is to aggressively reorient education in society to education about how to use AI systems.

This rustles a TON of feathers to even broach as a topic, but it's the only correct one. The AI engineer will eat everything, including your educational system, in 5-10 years. You can either swim against the current and be ate by the sharks or swim with it and survive longer. I'll make sure my kids are learning about AI related concepts from the very beginning.

This was also the correct way to handle it circa the calculator era. We should have made most people get very good at using calculators, and doing "computational math" since that's the vast majority of real world math that most people have to do. Imagine a world where Statistics was primarily taught with Excel/R instead of with paper. It'd be better, I promise you!

But instead, we have to live in a world of luddites and authoritarians, who invent wonderful miracle tools and then tell you not to use them because you must struggle. The tyrant in their mind must be inflicted upon those under them!

It is far better to spend one class period, teaching the rote long multiplication technique, and then focus on word problems and applications of using it (via calculator), than to literally steal the time of children and make them hate math by forcing them to do times tables, again and again. Luddites are time thieves.

Times tables aren’t the problem. Memorizing is actually fun and empowering if done right.

But I agree that the “learning is pain” is just not my experience.

> We should have made most people get very good at using calculators, and doing "computational math" since that's the vast majority of real world math that most people have to do.

I strongly disagree. I've seen the impact of students who used calculators to the point they limited their ability to do math. When presented with math in other fields, ones where there isn't a simple equation to plug into a calculator, they fail to process the math because they don't have the number sense. Things like looking over a few experiments in chemistry and looking for patterns become a struggle because noticing the implication that 2L of hydrogen and 1L of oxygen create 2L of water vapor being the same as 2 parts hydrogen plus 1 part oxygen creates 2 part water, which then means that 2 molecules of hydrogen plush 1 molecule of oxygen create 2 molecules of water, all of this implying that 1 molecule of oxygen has to be made of some even number of oxygen atoms so that it can be split in half to make up the 2 water molecules which must have the same amount of oxygen atoms in both. (This is part of a larger series of problems relating to how chemist work out the empirical formula in the past, eventually leading to the molecular formula, and then leading to discovering molecular weight and a whole host of other properties we now know about atoms.)

Without these skills, they are able to build the techniques needed to solve newer harder problems, much less do independent work in the related fields after college.

>Imagine a world where Statistics was primarily taught with Excel/R instead of with paper. It'd be better, I promise you!

I had to take two very different stats classes back in college. One was the raw math, the other was how to plug things into a tool and get an answer. The one involving the tool was far less useful. People learned how to use the tool for simple test cases, but there was no foundation for the larger problems or critiquing certain statistical methodologies. Things like the underlying assumptions of the model weren't touched, meaning students would have had a much harder time when dealing with a population who greatly differed from the assumption.

Rote repetition may not be the most efficient way to learn something, but that doesn't mean avoiding learning it and letting a machine do it for you is better.

I remember seeing a paper (https://pmc.ncbi.nlm.nih.gov/articles/PMC4274624/) that talked about how physical writing helps kids learn to read later. Typing on a keyboard did not have the same effect.

I expect the same will happen with math and numbers. To be fair you said primarily so you did not imply to do completely away with the paper. I am not certain though that we can do completely away with at least some pain. All the skills I acquired usually came with both frustration and joy.

I am all for trying new methods to see if we can do something better. I have no proof either way though that going 90% excel would help more people learn math. People will run both experiments and we will see how it turns out in 20 years.

> The correct answer, and you'd see it if folks paid attention to the constant linkedin "AI researcher/ML Engineer job postings are up 10% week over week" banners

This does not really lend great credence to the rest of your argument. Yes, Linkedin is hyping the latest job trend. But study after study shows that the bulk of engineers are not doing ML/AI work, even after a year of Linkedin putting up those banners -- and if there were even 2 ML/AI jobs at the start of such a period, then 10% week-over-week growth would imply that the entire population of the earth was in the field.

Clearly that is not the case. So either those banners are total lies, or your interpretation of exponential growth (if something grows exponentially for a bit, it must keep growing exponentially forever) is practically disjointed from reality. And at that point, it's worth asking: what other assumptions about exponential growth might be wrong in this world-view?

Perhaps by "AI engineer" you (like many publications nowadays) just mean to indicate "someone who works with computers"? In that case I could understand your point.