Writing essays, specifically expanding a list of well-reasoned bullet points into communicative written prose will be a worthless operation in the future, and likely already is.
There's no market for kids essays, we never made them write these things with the purpose of being useful output. The market for essays for grown ups is also very small, making kids write things down was not with the purpose of covering the case of them becoming journalists or something. It's just that makes them learn to think and structure their thought process. That's why people take notes and write down things even if its not going to be graded or read by anyone else.
Yes. And one interesting thing about ChatGPT is that, when asked to write an essay about a topic, it defaults to the standard introduction-body-conclusion organization of a school essay assignment [1]. Since its training data must have included texts organized in many other ways, I wonder if it was tweaked to default to the school-essay format.
[1] https://www.gally.net/temp/202212chatgpt/defaultessay.html
Writing an idea down as concisely as possible is important, the rest is just embellishment and is easily handled by AI.
For students, the objective is to write what to an adult would be mediocre essays, because they are on a path to writing adult level essays.
The AI can write mediocre essays, but not adult level essays.
Assuming that a student must write a bunch of mediocre essays in order to progress past the AI to write adult level essays, then they need to be evaluated on writing a bunch of mediocre essays.
If the teacher cannot distinguish between AI output and the student's output, and the result is that we give up on evaluating mediocre student essays, then the students are ultimately inhibited from progression to adult level essays, which, currently, are superior to the AI's output.
We automated a lot of arithmetic and then some higher math decades ago, but that hasn't meant that knowing how to do it is worthless.
Effective communicative prose is an inherently high-value part of coordinating human activity. The number of roles exclusively dedicated to it might shrink but it's part of nearly every activity in a specialized society. What's most likely is that people will use it as a time-saving tool but everyone will be evaluating how good the output is and tweaking it. And that means until we're at a point where people trust AI to actually evaluate the value of AI output, many of these roles (and certainly anyone building AIs that do this) will need to know how to recognize good output -- and the training involved in that probably involves practice in personally doing it.
Or, maybe practicing things we know how to do is a good way to practice?