The Writing Matrix: Balancing Structure and Chaos in Literature

In academic writing the role of chaos is often underestimated, however in reality the interplay between structure and chaos forms a critical dynamic that shapes literary works. This article introduces the concept of a writing matrix, a theoretical framework that explores the tension between order and disorder in literature. Whilst the piece does not focus on chaos as such, by highlighting its place in the matrix it hopes to show how it is as valuable facet of writing as structure, information and form.

The Axes of the Writing Matrix

The writing matrix consists of two primary axes: a vertical axis representing the spectrum from aesthetics to information, and a horizontal axis depicting the continuum between structure and chaos.

Vertical Axis: Aesthetics and Information

  1. Ascending Vertical Axis (Aesthetics): This dimension encompasses poetic metaphors, vivid descriptions, and evocative prose. Writers ascend this axis when crafting sentences that resonate on emotional and imaginative levels. While often minimized in academic writing, it may still be employed for occasional descriptive passages.
  2. Descending Vertical Axis (Information): This realm is dominated by raw data, facts, and straightforward communication. Scientific reports, encyclopedia entries, and dictionary definitions inhabit this space. In essays, this axis ensures that counterarguments are cogent and contain the necessary information to support the central thesis.

Horizontal Axis: Structure and Chaos

  1. Leftward Movement (Structure): This direction represents order, blueprints, and architectural precision. Structure ensures coherence, logical progression, and readability. It forms the backbone of essays, manuals, and legal documents. Writers move leftward when they outline, organize, and adhere to conventions.
  2. Rightward Movement (Chaos): This realm embodies the wild, untamed muse of creativity. It introduces unexpected twists, disrupts patterns, and breathes life into the mundane. Writers venture rightward when they break rules, experiment, and embrace spontaneity.

The Role of Chaos in Writing

As mentioned, chaos is often undervalued in academic writing, yet it is still needed. We cannot and do not totally function within tightly controlled planning. We need to be open to unexpected insights and differing evidence that may not match where we thought we were headed. When we notice that established concepts aren’t functioning quite as tidily was we thought they might we need to recognise these moments as chaotic interruptions that can work towards breaking conceptual stagnation. If you thought it, probably someone else did too.

Some functional interactions with chaos in writing are:

Fostering Innovative Thinking: In academic writing, controlled chaos can lead to the generation of novel hypotheses and unconventional research questions. It serves as a catalyst for interdisciplinary connections, encouraging scholars to explore unexpected linkages between disparate fields or concepts. This approach can result in groundbreaking theoretical frameworks or innovative methodologies.

Breaking Conceptual Stagnation: Excessive adherence to established paradigms can lead to intellectual stagnation within academic disciplines. Introducing elements of chaos can challenge entrenched ideas, fostering critical re-evaluation of long-held assumptions. This process can invigorate research fields, opening new avenues of inquiry and pushing the boundaries of existing knowledge.

Embracing Complexity: In academic research, controlled chaos reminds scholars that oversimplification can be detrimental to understanding complex phenomena. It encourages the exploration of multifaceted issues, acknowledging the inherent messiness of real-world problems. This approach leads to more comprehensive analyses that capture the intricacies of the subject matter, resulting in more robust and applicable research outcomes.

Facilitating Serendipitous Discoveries: Chaotic elements in academic inquiry can orchestrate serendipitous moments of insight. By allowing for unexpected connections and alignments of ideas, researchers may stumble upon unforeseen patterns or relationships in their data. These serendipitous discoveries can lead to paradigm shifts, new research directions, or innovative solutions to longstanding problems in the field.

Applying the Matrix

The writing matrix serves dual purposes:

  1. As an Analytical Tool: By mapping different elements of a text onto the matrix, literary analysts can gain deeper insights into an author’s use of structure and chaos.
  2. As a Guide for Writers: Understanding the interplay between structure and chaos allows writers to make more conscious decisions about their work and avoid common pitfalls.

The balance between structure and chaos may vary depending on the genre and the writer, for instance, poetry may rely more heavily on chaos and experimentation whereas academic writing typically requires a greater emphasis on structure and clarity, whilst fiction often strikes a balance, using structure to provide a framework while employing chaotic elements to engage readers and drive the narrative. Complementary to this of course is the author themself. As an individual they too will have a a tendency towards one of these quadrants. By reflecting on oneself and acknowledging that the chaos part does not need entirely repressing in academic writing, writers may be able to gain a better understanding of their wrting style and how to improve it.

AI and Academic Writing

Where are we with AI and academic writing? Frankly the situation is a little chaotic. The institution line is still often that of ‘academic offence’, even though the institutions know this would be extremely hard to enforce. One reason for this being that anti-plagiarism software like Turnitin are in a perpetual catchup mode with the AI available, so unless everyone sticks with chatgpt (free on openai (they won’t)) then Turnitin’s detection algorithms will be outpaced by newcomers and rephrasers. Another one is that sometimes students write in styles identical to (an) AI. The common form of this is the very capable second (or more) language student; owing to the academic way the language is often learned, these students follow precise rules and sometimes do it extremely well. In turn, they follow the rules into stylistic use and end up sounding sufficiently like chatgpt that the software (and sometimes staff) pick it up, in turn they end up hauled in front of some disciplinary body just for being extremely smart.

This means that enforcement is hard to achieve, as one has to coordinate appearance of AI like style with some other evidence e.g. sudden alteration is style. This is possible, but time consuming for academics and if the student goes straight in with using the AI throughtout, then no style change detection will be possible; rephrasing software compounds the issue. Bearing in mind we’re in the total infancy of this technology, this is a difficult situation. I say difficult with no little thought; the situation is difficult not because of a negative connotation of difficulty, but rather because it is literally difficult to know what to do from here.

The essential question being ‘is assessment by academic writing in its current form a dead horse that we need to stop flogging?’ and if it isn’t dead yet, how long before it is dead (if indeed it will be dead at some point)? How will we know? Personally I would say it isn’t dead yet, but its death is probably between 2-5 years away. How will we know? We’ll know because the ability of AI to construct academic writing for students (and staff) will have permanently outstripped our ability to detect it either with software or with our minds.

That is, both in content and style, AI will produce work for students who wish to use it that will mean, if they don’t want to, then at least for the written components, their engagement with the material can be pretty much nil. Furthermore any student who, let’s say for integrity reasons, chooses to write their own work, may find themselves penalised by handicapping themselves to their human writing skills. Thus their integrity will get them quite possibly a lesser grade than their AI using colleagues.

But as we’re not there (yet) what can we do in this strange hinterland? This issue itself seems related to the future of AI and our interactions with it. That is, how guilty we feel about the interactions that we encourage, turns partially on what it will become. However since we cannot know where we are headed we don’t know how guilty to feel. What do I mean by ‘feeling guilty’? I mean this sense that we are cheating when we get AI to do work for us. Isn’t this a kind of crucial border, this meeting place between a legitimate productive use and losing part of ourselves which we possibly need to preserve?

Maybe we can sketch out two broad trajectories. In one, AI supplants our need for writing skills as it can produce any text we need more accurately and with greater detail than we can achieve. In another, writing skills continue to be needed because AI continues to fail to capture human synthetic abilities to generate insights. Because these insights were formed from human generated cognitive concatenations (consciously or unconsciously) the argumentative structures cannot be automatically written up by the AI and hence the ability to lay out the argument etc is still needed.

What is obvious is the blur of these heuristics. The former seems strange insofar as it indicates that whatever we want to write on, the AI can do it for us. This aligns this trajectory roughly with what some (mostly undergraduate) students might use it for, whilst the latter one seems more indicative of research usage.

The blur occurs because in the first case the student will still have an idea that they want the AI to write the essay on (admitting they also might not). Either way they have to engage with the AI and unless they literally want to hand in the first thing it writes, they have to do some thinking and engaging. No one is saying this minimal engagement is a good thing, it just means that even the laziest version has to have some effort in it. The second trajectory suggests that writing is still needed, however once the researcher has had this synthesising insight, whilst the AI may not be able to reconstruct their argument by itself, it can certainly help if you give it the different propositions and ask for paragraphs to be constructed around them. The point generally being that with the second trajectory, unless the academic is a kind of purist, doesn’t deny that AI could be used to help out with the writing.

It seems fairly clear that trajectory one we want to avoid, yet trajectory two could easily encompass quite a lot of AI written input. It seems to me the crucial part here was the academic’s synthesising idea. This idea was only made possible by the reading and thinking (conscious and unconscious) that the academic did. This reminds us that of course what is important in the educational/research process is actually comprehension. The first option strikes us as so bad, because comprehension is extremely low. I tried to highlight how the redeeming part or trajectory one is that it is on a gradient on which some students will at least have an idea on the topic, that they then get the AI to write the paper and then they read it to make sure it’s good. This redeeming aspect is their thinking engagement and comprehension.

Going forward with AI we need to find ways to emphasise comprehension of subject matters. We also need to accept the potential of AI to write for us, to help us write our ideas. The danger does lie in the lack of comprehension, but arguably there is a lot of lack of comphrension already, AI is just bringing out of the system the latent lack of student integrity and exposing it.

Academic writing in the traditional sense may well be ultimately largely supplanted by AI, but academic reading (and all other forms of learning, argument formation and thinking) cannot be allowed to do so. Indeed, in exposing the possible lack of motivation in the system, we can use this to think of new ways to engage students in understanding their subjects and helping them want to understand their subjects. The best the AI can be for us is probably be a new interlocutor. As soon as we have our new research insight, it goes into the system (the available research). From here it can be accessed by the AI to help other researchers, who must think carefully and through their own multiple inputs create new insights.

So the guilt issue should not be view so much as an issue with writing; it’s an issue with comprehension. We need to absolve ourselves of this nebulous guilt by the best practice of writing with AI and ensure that we remain active comprehenders, processors and producers of information —as opposed to passive receivers of AI insights. So long as we are exercising our capacities to think and comprehend to the best of our ability, then the AI becomes a partner that could be incredibly empowering. The danger lies in our, handing cognition and production over to it.