Technology obviously does transform society and the economy, and it obviously does make certain skills more or less valuable in the workplace.
Think about marathon-running. Ancient Greek ‘day-runners’ like Pheidippides, the original marathon runner, were a vital part of the functioning of Greek city states. Their aim was to get a message from A to B as quickly as possible, and in a world with no combustion engine or telegrams or internet, if you needed to send a message you needed a day-runner.
Nowadays that is obviously not the case. If you need to send a message to a friend 26 miles away, you’d probably send a text message. If they needed a particular physical set of documents, you still wouldn’t hire a day-runner – you’d hire a taxi driver instead.
And yet, running marathons is incredibly popular and more people run the London marathon every year than there were ever day-runners. None of them run it to courier a message. The vast majority run it for reasons of personal development. A tiny fraction do run it to gain economic benefit – not from being messengers, but from winning races and providing entertainment which spectators are willing to pay for.
The difference between ancient Greek marathon runners and today’s marathon runners is at the heart of so much confusion about AI and its role in society and education.
- Students are baffled by teachers who want them to deliver a message via a marathon run when you could just send a text message.
- Teachers are baffled by students who want to get a taxi round a marathon course and expect a medal at the end of it.
So partly, this confusion is about what you think the purpose of education is.
- If you think the point of education is for students to develop their human potential, then the teacher is by definition right. In order to develop your human potential you can’t get someone or something else to do it for you!
- If you think the point of education is to get a job, you will probably be more open to using technology in education.
Education for personal development
However good AI gets at writing, there is always going to be a personal development use case for writing which is analogous to running.
That is, even if the direct economic value of being a good writer gets completely obliterated by technology, the general life value of being able to write will remain.
Being able to run a mile or two without getting out of breath is good for your general health and fitness, and that’s why lots of people choose to go out running even though there is no direct economic benefit in it for them. Likewise, I suspect that people will value being able to read and write complex texts even if they can’t make money out of it.
One reason I think this is because writing has so many underappreciated benefits. Often, we assume the main purpose of writing is communication, as though it works like this: I have a series of well-worked out and complete thoughts in my head; I write them down; other people can read them.
That is certainly one way we use writing, and the one that generative AI is perhaps best placed to help with. If you have a series of thoughts in your head, you can speak them into a voice memo and get AI to polish them up into a perfect paragraph or series of paragraphs. A good example is where you have a relatively simple decision to make – perhaps whether to say yes to an invitation or not – you make the decision, and then you struggle to communicate it. Generative AI can be helpful in these cases.
But there is another important function of writing which generative AI is less well placed to help with: writing helps extend working memory and is a tool for thinking. A lot of the time we don’t have complete and well-worked out thoughts in our head. It is only by writing our thoughts down that we discover the gaps and the flaws in them. “If you’re thinking without writing, you only think you’re thinking.”
This process is obviously important if you are doing some kind of deep academic work, but it’s still important in everyday life – if you are writing an email to friends with the logistics for a day out, or a memo to colleagues on the decisions that have to be taken at your next meeting. Generative AI might already be a better writer than you in terms of being able to quickly draft readable and error-free texts. But is it better than you at working out what you actually think?
Cars are faster than humans, but we still teach PE at school. Similarly, even if generative AI totally outstrips humans at writing, I think we will still teach it because it is a valuable tool for life.
One of the reasons I love the work of The Writing Revolution is that they explicitly make this link between thinking and writing, and design lessons and curriculum sequences that teach writing as a tool for thinking right from the start. The resources we’ve developed at No More Marking follow this approach too.
But what about education for the job market?
Of course, personal development is not the only purpose of education. Another important purpose is to get a job, and here it would seem the advocates of generative AI are on stronger ground. If AI is going to be used extensively in the workplace, surely it should be used extensively in the classroom too?
I am not so sure. Even if you are solely concerned with the economic function of education, and even if you don’t care very much about the personal development aspect, there are still strong reasons to avoid the excessive use of generative AI in education.
This post was originally published on the No More Marking Substack here. You can subscribe for free to read future posts in this series.
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