With the recent developments in artificial intelligence and generative AI, several educational assumptions have had to face scrutiny. These new technologies can produce poems, stories, and documents in a thousandth of the time necessary for an individual to produce the same length text. Questions have arisen that were never necessary to ask in the past. Why are we doing the things we do and why should we demand our students follow suit? As a writer and a lecturer, and somebody who cares about the demands I set on others, these developments have forced me to justify in my own mind why I do the things I do, especially in demanding students write essays, academic papers, and other related activities.

So why write? With good prompting, a machine could generate a workable standard paper. Using a series of prompts and refinements, it’s possible to generate a 3000-word paper in a few minutes. With the proper scaffolding of prompts and revisions, it is very possible to produce a measured paper with some success. Thus, with this technology, a student has the possibility to use a machine to create a text generated by probability and statistics. The student does not in fact write the text but with some inputs, receives one that likely is a reasonable mathmatically accurate response to their prompt. So with these fantastic developments, why write? People are busier than ever. Isn’t it unfair to demand they engage in and utilize an outdated educational approach? Wrong! This isn’t about the argument; students have always written essays and papers. This isn’t about tradition or prestige or any other institutional argument. Rather, it’s about reinforcing the value of writing in learning.

Writing is the concentrated expression of thought. To write about a particular idea, one needs to think a particular idea. In the case of academic writing, a writer sets the stage to consider a particular problem and articulate it. In the case of literature reviews, summarizing a text allows for demonstrating their understanding of the material they read. With methodologies, a writer can clarify the process they are using to solve or analyze a particular problem. With discussion sections, it’s about analyzing the results and concluding lessons learned from the research. It’s also about considering future applications for the research or weaknesses in the methodology.

But writing is also about refining ideas and arguments. An idea and an argument may seem good until someone expresses it. After its initial presentation, it can still be refined through grammar and choice vocabulary. Revision is a never-ending process. There is almost always a better way of expression. There are always opportunities to boil down the message to a bare essence of the idea and develop it further. In doing so, the message is easier to read and clearer.

Writing is a process of discovery. It can be the case that a writer gains insight into a separate problem by expressing another. The time involved in understanding something well enough to express it allows for insight into related topics. In education, this quality is important for students and learning. It demands concentration and time. It means experimenting with a problem until the answer is clear. Learning can be inefficient, but here in this case, efficiency is irrelevant. People are not machines. We should never strive to imitate them, or act like them.

Through concluding this argument, I feel like a horse standing before an automobile justifying my own reasons to live. Still, I remain firm in my belief these recent developments in machine learning are not so valuable as to demand a complete replacement of all our traditional educational methods.