What Makes Writing “Academic” in the Age of Generative AI?

If we see a significant change in the nature of academic writing, would that actually be a problem? As Molinari (2023: 18) notes the “genres, jargons, grammar, syntax and overall forms have been pejoratively described by writing scholars as straightjackets, chains, pigeonholes, frauds and hoaxes” not to mention the many critics for whom it is “discriminatory, elitist, exclusionary, colonial, dull, zombified and confusing”. I’ve often felt sceptical about these critiques because of their tendency to suggest that specialised writing is by its nature problematic, as opposed to reflecting the specific needs of an expert audience. To write in a vernacular which is adapted to the interests of this audience is only a problem if it’s the only way in which academics can write. Billig (2009: 9) suggests that public intellectuals can be thought of as bilingual in that “they use one language for addressing the public and another for addressing fellow specialists”. As long as there are at least some academics within each field who are willing and able to switch between these languages, I’m not convinced the problem with specialised language is that it excludes non-specialists.

The problem instead is that technical language often substitutes for clarity about what is being expressed in this technical jargon. When these terms are used in specific and precise ways they serve a purpose by simplifying communication. It’s easier for me to use the adjective ‘computational methods’ than it is to list a series of techniques for working with research data that have been made possible by technological advances in recent years. There might be uncertainty about how widely I’m drawing the category, but it can be safely assumed that everyone who recognises the phrase will understand the kinds of method I am talking about with this phrase. There will be people who are specialists who don’t understand the phrase. In which case I might have to list examples of the methods I’m describing, such as text mining, explaining how this relates to established forms of qualitative and quantitative work with texts that they will be familiar with. If they’re not a specialist then it’s likely another approach would be necessary, in which I pitch my explanation based on an assessment of their prior knowledge. The phrase would be a problem with this latter audience but the issue at stake is how to address non-specialist audiences in clear and effective ways.

This illustrates how, as Molinari (2023: 13) puts it, “what makes writing academic – its academicness – emerges from a complex stratified ontology of structures and agencies”. There’s not a defining feature of the text, a specific grammar and style, which gives it this academic quality. Nor is it simply a reflection of the fact it’s being written by people who occupy the social role of the academic. Academics write non-academic things continually. It seems implausible to say that our e-mails are a form of academic writing yet we write thousands of words of this form each week. I wrote a short story a few months ago. Is this academic writing? There are certainly academic themes to the writing, in that it was set in a university and explored themes of political crisis and civilisational crisis. But it didn’t feel like academic writing to me, nor do I suspect that anyone who reads my academic work would regard it as such. It’s not simply the fact we get published in a particular location either, because the unpublished manuscripts sitting in the (by now figurative) filing cabinet are academic writing even if they’ve not been made public. It could be argued that these are at least intended to be published, which would imbue journals with the capacity to render writing academic if the author seeks to publish it there. But as someone who has been blogging for over twenty years, I find this an obviously limited way to account for the meaning of the adjective. The six thousand posts on my blog are mostly academic but there are vast quantities of material which have nothing to do with my academic life either. I would struggle to offer a general account of the difference between these categories, even if it would be easy to make the distinction on a case-by-case basis. It’s not straightforward what makes writing academic even if we might have been taught in a way that suggests otherwise.

It follows from this that academic writing will always be subject to change and development. This doesn’t mean that there will be continual change but rather that its nature is not fixed, even if it sometimes feels like it is. The role of power in enforcing these judgements, whether the supervisor presenting their stylistic preferences as received wisdom or the journal reviewer demanding adherence to their instructions, compounds this sense of fixity. They are at least in those interactions fixed elements of the landscape which the academic writer is pressured to adapt to. While you don’t have to accept their judgements as the gospel truth, rejecting them incurs costs which you must negotiate in the development of your academic career. This gives them a force which can often be an object of resentment, leaving academic writing positioned precariously as both an expression of intellectual creativity and something we are forced to do in ways that count as a condition of employment. It can be hard to be reflective about academic writing when it so frequently feels so ambivalent to us. But unless we are reflective about it, we are likely to continue forward in the same way we have until something forces us to change.

This isn’t uniquely a feature of machine writing. The encounter of academics with digital media, first through blogging and then through social platforms, provoked similar anxieties. The change it required led some to worry that digital engagement would unavoidably lead to the abandonment of scholarly virtues. Now we’re experiencing similar concerns about AI’s impact on academic writing. But perhaps we’re focusing too much on the technology itself and not enough on the cultural and economic context in which we’re using it.

Instead of treating LLMs as an actor in their own right, we need to examine “the cultural and economic values that currently shape AI’s affordances”. As Vallor (2024: loc 2077) points out, “we ourselves are measured in terms of our ability to resemble our own mechanical mirrors”:

“Whether it’s the pressure to produce your next album, or publish enough to get tenure, or film enough videos to see your subscribers – our dominant values favour those who don’t get writer’s block, who don’t struggle to find the right words, or images, or notes, or movements, who never get caught up in the swirling drag of inexpressible meanings. Our economic order has long rewarded creators who work like machines. Should we really be surprised that we finally just cut out the middleman and built creative machines?”

If academics are inclined to draw on machine writing in order to maximise their productivity, we need to ask why this is. What is it about the training they undergo and the incentives they confront which leads them to seek to produce as much as possible, as quickly as possible? The affordances of LLMs offer an opportunity to radically expand the quantity of what is being produced but what is it which lead some academics to want to take advantage of that opportunity? In this sense we need to treat AI as a mirror, to use Vallor’s (2024) metaphor, which is held up to our existing social arrangements. If machine writing is bringing out the worst in academic writers we need to examine what it is about academic writers which leads them to engage with machine writing in this way. If we simply treat machine writing as if it is an enemy at the gate, a foreign intruder which needs to be repelled lest an otherwise well-functioning system be damaged, we lose the opportunity to grapple with the real changes taking place in academia.

Perhaps the most valuable question isn’t “How will Generative AI change academic writing?” but rather “What does our response to Generative AI reveal about the state of academic writing today?” The anxieties, temptations, and opportunities presented by these technologies hold up a mirror to the pressures and contradictions already embedded in academic practice. These are pressures that existed long before ChatGPT or Claude appeared on the scene.

#academicLabour #academicWriting #digitalScholarship #JuliaMolinari #michaelBillig #writing

Academic writing has always been in flux

It can feel when reading academics discussing LLMs that previously settled practices have been suddenly upturned by the introduction of this strange technology into higher education. The reality is that our practices of writing and communication have been through many such changes, often within the span of an individual’s own career. I was reaching the midpoint of a PhD when social media came to be a prominent feature of academic life, offering a potent forum through which to connect with others and discuss ideas alongside an ever present possibility of distraction. During the same PhD I remember talking to my supervisor about producing an 800 page book on a type writer. I simply couldn’t understand how such a thing was possible. Much as I struggled more recently when reading Lamott’s (1994) description of repairing a three hundred page manuscript by placing it on the floor of a cavernous living room in order to reorganise it page-by-page:

“I put a two-page scene here, a ten-page passage there. I put these pages down in a path, from beginning to end, like a horizontal line of dominoes, or like a garden path made of tiles. There were sections up front that clearly belonged in the middle, there were scenes in the last fifty pages that were wonderful near the beginning, there were scenes and moments scattered throughout that could be collected and written to make a great introduction to the two main characters. I walked up and down the path, moving batches of paper around paper-clipping self-contained sections and scribbling notes to myself on how to shape or tight or expand each section in whatever necessary way.” (Lamott’s 1994: 100).

It’s not that I couldn’t do this with my own text. While I’ve still not had reason to find out how to print at my university, in my fourth year since starting to work there, I’m sure I could quickly print out this text if I was motivated to do so. I remember the feeling of holding my PhD thesis in my hands the first time I printed out the draft, suddenly feeling a sense of mastery over this diffuse thing which had been the horizon of my experience for so long. I can recognise the appeal in the physical, the ways of relating to ideas opened up when we get our hands on their material expressions.

It’s just that I struggle to imagine relating in such a physical way, even allowing for the fact that I would undoubtedly be printing an electronic manuscript as opposed to Lamott’s manuscript produced through a typewriter. I was never a routine user of a printer to begin with but the separation from my office printer during the pandemic, combined with a diffuse dislike of the clutter of paper, inexorably led me towards working without print outs. It’s now been at least five years since I last printed something out and it wasn’t something I did much to begin with. The physical manifestations of my writing have slipped out of my immediate experience, no longer presenting as ready-to-hand, in a way that leaves them lodged as an intellectual possibility. In the same way that academics of my generation will often find it perplexing to be reminded that paper journals were once collected and consulted in physical form.

When our routines are disrupted we often feel compelled to account for that disruption. If things don’t work as planned, we are led to reflect on what we expected to happen. It’s easier to see routines when they don’t work because when they do they simply fade into the background. The same is true for the role of technology within these routines (Marres 2014: loc 1919). The introduction of LLMs into academic writing provides such a disruptive occasion because it unsettles many of the assumptions upon which our routines have previously depended. It’s no longer the case that a coherent piece of text we encounter must have been produced by a human author. It’s no longer the case that completing our own text requires only human effort.

This technological shift forces us to confront what writing means to us beyond its mechanical production. Just as word processors transformed academic writing by making revision less laborious, LLMs challenge us to articulate what remains essentially human in our scholarly production. Perhaps what matters most isn’t whether we occasionally use AI assistance, but how thoughtfully we integrate these tools into practices that preserve intellectual ownership and creative engagement with our ideas.

#academicWriting #digitalScholarship #generativeAI #technology #writing

The Objects With Which We Write: The Materiality of Academic Writing in a Digital Age

What I’m exploring here are the joys which can be taken in the writing process, as well as how this shapes our relation as academics to the machine writing which LLMs are capable of producing. I use this phrase to indicate a specific focus on how LLMs can be used for writing, as opposed to the many other purposes they can serve. It also foregrounds the continuities between machine writing using LLMs and the far more extensive history of writing, including the many machines other than LLMs which have been used as part of the writing process.

Word processors, typewriters and printing presses have all been integral to how we produce written work. If we’re comfortable stretching the definition of ‘machine’ to encompass all the artifacts used in the writing process, we would obviously include pens, pencils and papers. Once we start to search for the objects we draw upon in writing, we find numerous tools that become so ready-to-hand that we rarely reflect on their nature or the role they play for us. What’s important is being sensitive to the things (in the broadest sense) we use to write, as well as what this means for our experience of writing. This helps ensure that we don’t imagine the introduction of technological artifacts, such as conversational agents like Claude and ChatGPT which are powered by LLMs, into the writing process is something entirely new. What’s new are the nature of these artifacts and what they mean for our writing practice.

This focus on the materiality of writing might seem immensely obvious. If you’re an academic with a love for physically writing with a high quality pen and ornate stationery, it will already be clear to you that writing is a material practice. It’s also likely you’ll already have a sense of how the experience of writing is inflected through the materiality of the objects we rely upon. As the writing scholar Helen Sword (2023: loc 2196) reflects: “I love manipulating digital text on my computer screen: cutting and pasting, resurrecting deleted phrases with a single keystroke, messing around with colors and fonts, highlighting words so that I can return to my document later and see at a glance which sections need attention.”

This isn’t an experience I share. I appreciate the practical affordances of editing which Sword points to but I don’t feel enthusiasm for them. What I love is the immediacy with which one can write in a cloud-based writing system. I often write snippets on my phone when I’m struck by an idea which Ulysses, my writing software, will ensure is securely lodged within my database waiting to be reviewed and refined at a later point in time. I often switch between my Kindle app and Ulysses on my iPad in order to respond to something I have read while the idea is still fresh to me. The fact that these snippets, produced in a diverse range of situations and energized by that diversity, will be reliably waiting for when I sit down for more extended writing and editing with my laptop or desktop is something I really love about the materiality of my writing process.

It’s not that I resent or reject the editing capabilities which figure so forcefully in Sword’s experience, it’s simply that my embodied pleasures in academic writing come from elsewhere. In contrast, I struggle to find any utility in writing with a pen despite the appreciation of ornate stationery which I’ve felt since I was a child. It’s such a slow process that I find it frustrating whereas touch typing for thirty years means that I can type as quickly as I think.

I can still find satisfaction in handwriting though, even if the degrading of my penmanship through underuse means that ensuring the legibility of what I have written slows me down even further. I had a free afternoon on a recent holiday in which I was suddenly struck by the impulse to write. I purchased an ornate notebook and nice pen from the nearest bookshop and then sat under a tree and spent a couple of hours slowly recording thoughts which I’d felt germinating that morning. I’m not sure why a whole series of insights had suddenly occurred to me in the middle of a holiday in which I had genuinely not thought about work for days. I suspect they occurred to me because I had detached from my work, including removing work e-mail from my phone.

I’m glad I could feel these insights taking root and that I intuited I needed a notebook rather than my usual note-taking app because a whole series of things I had struggled with intellectually suddenly fell into place. There wasn’t a pleasure to writing slowly but there was clearly an affordance found in it. The enforced slowness of writing with a pen helped those insights gently emerge, even if it took a bit of work to decipher them when I returned home. The fact it was a beautiful summer’s day in an idyllic churchyard garden where the adjacent cafe had kindly left some deckchairs clearly helped as well.

The embodied pleasures we take in writing are varied and often situational. It’s not just that different authors have different inclinations. What works for us at one juncture might not work for us at another. The satisfaction I found in writing with a pen in that Cambridge churchyard was a rare instance where the affordance of handwriting was exactly what my creative process needed at that specific moment. If I had tried to record these germinating insights through my usual apps I would have undoubtedly have been tugged into a different mentality depriving me of the space in which this perspective could unfold.

It’s not that one mode of writing is more authentic or enriching in itself. Rather, experiences of authenticity and enrichment through writing rest upon understanding how the affordances (what the objects enable us to do and what they constrain us from doing) and the embodied satisfactions (the rewarding feelings which tend to be associated with or absent from their use) play out in specific settings with goals and pressures which vary between us.

For example, there are times when writing by hand has been helpful in preparing for a talk because it helps me isolate the core elements of my message. But if I’ve left it to the last minute to prepare, with the need to make notes as I was on the way to the venue, the slowness of my writing and the unreliable legibility of the ensuing text would be too much of an obstacle. Sword (2023: loc 400) vividly captures how different modalities manifest themselves in different experiences of writing, involving strikingly different pleasures found in what some might imagine was an overlapping process:

“When I touch-type on my computer keyboard, the pleasure that I feel is almost purely intellectual; my physical surroundings seem to fade away as my fingers surrender to the flow of ideas. When I write by hand in a notebook, by contrast, my pleasure becomes more intensely embodied; my heartbeat slows along with the pace of my pen, and months or years afterward I find that I can still recall physical details such as the chair I sat in while I was writing a particular passage, the weight and size of the notebook in my hand, even the temperature of the air and the quality of the light.”

The physicality of writing with a pen is easy to grasp. As Baron (2023: 202) observes “Those of us logging years of writing by hand still bear our ‘writer’s bump,’ that callus on the inside of the first joint of the middle finger of the writing hand.” I was struck when reading Lacan’s Seminar X, a transcript of his annual seminar in Paris, how an aside about the physical difficulties often associated with writing could assume everyone in the room shared that experience. It left me with a sudden apprehension of an entirely different academic culture to the one I inhabit as a millennial academic who began a PhD in 2008. I understood intellectually that handwriting was ubiquitous prior to the personal computer, but this was the first time I was left with a more intuitive sense of what a radically different academic culture that entailed.

It can be useful to reflect on how this has changed in order to sensitize ourselves to what remains an embodied experience of writing with digital technology. I learned to touch type at a young age. I can’t remember why I taught myself to touch type, nor it seems can my parents. But from the vantage point of my late 30s it strikes me as the most useful decision I ever made. The ubiquity of typing in our lives means that it can often fall under the radar, such that we don’t think comparatively about technique any more than we would find ourselves musing about the different ways in which adults brush their teeth.

Touch typing, relying on the feel of the keys to guide your hands around the keyboard, obviously constitutes a vastly superior physical technique for typing. It is vastly quicker, avoids the need to stare down at the keyboard and enables an immersion in the process of typing. A recent test I took online suggests I can type at 140 words per minute if I’m willing to make some mistakes. If writing in its early stages is a matter of expressing thought, touch typing means that you can physically write as quickly as you can think. This is hugely significant for the process of writing, even if it might not be unambiguously positive.

As we confront the emergence of AI writing tools, we should approach them with the same reflective awareness we might bring to choosing between pen and keyboard. How do these tools shape our thinking? What pleasures do they afford or deny us? What modes of engagement do they facilitate or constrain? Just as I discovered that handwriting occasionally offers creative insights that digital tools cannot, we may find that AI tools have their place within a thoughtful writing practice: neither wholesale replacements for human creativity nor mere gimmicks to be dismissed.

The landscape we inhabit as academics can be immensely confusing because the options available to us now have little relationship to those many of us confronted in the formative stages of our careers. The reflexivity I’ve illustrated here, in which we engage in a dialogue between the tools we are using and the practices in which we are deploying them, becomes essential in order to realize the emerging opportunities for academics and avoid the potential pitfalls.

#academicWriting #digitalScholarship #generativeAI #helenSword #materiality #objects #writing

Using Generative AI for functional rather than expressive writing

I advocate distinguishing between what I call functional and expressive documents in academic writing. Functional documents, such as reports, summaries, or abstracts, tend to involve academics reporting on what they have done or explaining what they will do. These involve writing, but it rarely tends to be a joyous writing of the kind that truly engages us. It is rather an accounting for our activity that can often be connected to more expressive forms of writing, but which serves a particular purpose.

Until we find ourselves in a position where the automation of writing is possible, there’s little reason to make these distinctions. We might experience them as different, not least of all because of this different enjoyment of them. But the practicalities are fairly similar in the sense that we find ourselves writing. I suggest that the role of creativity in each of them is revealed when we consider how machine writing could improve or degrade these activities.

Using generative AI to produce functional documents not only saves time, it can improve the quality of those documents. While I might be unusual in my struggle with abstracts, I’ve long realized how difficult I find it to produce a compelling overview of a text I have written. In contrast, this is a task which GenAI tools excel at, particularly if you provide an exemplar to guide the process. The creativity resides in how we provide a compelling and effective summary which is effective for indexing the text and providing a preview for potential readers. It is not a mechanical task devoid of creativity but rather a tightly defined one in which the creative contribution serves a narrow instrumental purpose. I tend to find writing reliably energizing but these sorts of tasks can often be weirdly draining given the limited length of the text which is being produced. It tends to constitute an item on a to-do list, distinct from the writing process, with the inevitable drag on time and energy that entails.

Using GenAI for functional writing tasks like this can have a considerable effect on the feel of the working day, making it possible to move quickly through activities which otherwise would have been cumulatively draining. This doesn’t mean that we should entirely outsource the production of something like abstracts to tools like ChatGPT and Claude, but it does mean that we might comfortably rely on them in most, if not all, circumstances to produce our first drafts. My experience is that the initial summarization needs a little tweaking to be adequate for your purposes.

As with any prompting exercise, being clear about what you can expect and providing examples can simplify the process considerably. For example, I might say to Claude that “I am an academic writer who has written a journal article on subject X for journal Y who now needs to write a 150-word abstract based on the preprint text I have provided” before explaining that “I need this abstract to be compelling and succinct, matching the language of my preprint where possible, with the intention that a reader is provided with a clear sense of the content of the article, the contribution to knowledge and why it would be valuable for them to read.” Exactly what you want this to look like will vary between people and fields, so it’s essential to provide examples of what you’re looking for. If you have a perfect example of what you’re looking for in an abstract then provide this alongside the prompt.

This is another example of how prompting can be a spur to reflexivity. In order to explain what the output should look like, you need to be able to state explicitly what you think a good abstract should look like. Until I began to use GenAI to support functional writing, it had never occurred to me to explicitly state this. I would simply dive into the writing process with a vague sense of what I was trying to do, usually at the end of a writing process with an impending deadline and a corresponding tendency to settle for an imperfect abstract that could easily have been improved.

It’s now easier for me to write an abstract with the qualities I’m looking for because I’ve taken the time to state what those qualities are. If you’re not sure what exactly you are looking for, you can use GenAI to help you analyze examples to articulate your nascent intuitions. Look through recent papers in the journals in which you aim to publish, taking a minute or two to linger on the abstract for each paper that has recently been published. What do you like about it? What do you dislike about it? Share the abstract with Claude or ChatGPT and ask for an analysis of its structure, strengths, and weaknesses.

By engaging with AI in this way, we can develop a clearer understanding of our own writing preferences and standards. This reflexive process helps us become more conscious writers, even as we leverage AI to handle the more functional aspects of our academic writing. The time and mental energy saved can then be redirected toward the expressive writing that brings us more joy and intellectual satisfaction.

#digitalScholarship #generativeAI #largeLanguageModels #productivity #writing

The Ebb and Flow of Writing: From Struggle to Unconscious Fluency

It can help to understand writing as a nexus point where lots of different elements intersect. I might be sitting in the garden with my laptop and a can of coke, but there are many other things which are present with me in this moment—from my writing software, internet connection and accompanying eBook reader through to an imagined audience, an intended publisher and an intellectual community. Testing et al suggest we cast the net even wider to include things such as “managerial directives, quality procedures, disciplinary conventions, departmental environment, and discipline-focused, thematic, or linguistic social communities.” There is a whole world intervening on me as I write, even if when the writing goes well it feels like there is just me and my thoughts.

If I’m enjoying writing, I don’t worry about an imagined audience encountering these words for the first time and potentially finding them lacking. The enjoyment itself stems from being grounded in the present rather than projecting forward towards an imagined future outcome. There will be an audience who encounters these words, and it’s certainly possible they may find them lacking. But as I’ve written this paragraph, the experience has been defined by what the political theorist (and prolific writer) Richard Seymour describes as an “unconscious fluency“:

I doubt anyone begins a piece of writing with the rules in mind. Writing is a conscious, effortful process, but most of what works in writing is unconscious fluency. You start, not even with a completed thought, but often enough with a single word or phrase, or a mood, or a tune stuck in your head, that establishes a rhythm. You scarcely think about it. If you’re raging, the words come flying out by the quiverful. If you’re mournful, they’re as slow as tears. The rules come later, as cues during the editorial clean up.

I’m writing these words on what I’d designated as a writing afternoon, but things had not been going according to plan. Various frustrations had intruded on me via e-mail before I got started, leaving me twitchy and irritable as I sat down to write. Despite the fact the weather forecast had promised sun, I found myself in a garden under a cloudy sky struggling to focus. I battled on towards my writing target for the day, with the promise to myself I could stop when I reached a thousand words. But it was a struggle in which I felt my words had to be forced out, leaving me with clunky sentences staring at me inertly from a page of disappointments.

I felt dispirited by failing to make the progress I had expected, which immediately left me worrying about the other things I am committed to finishing over the coming weeks. This project is not one which will ‘count’ greatly from my employer’s point of view; in fact, I’m worried that I’m writing myself into a peculiar niche that will only be read by a handful of people. Should I not be focusing on the journal articles which will count? Am I distracting myself with mindless indulgences from my real work? Is this just a waste of time? Should I give up?

The speed with which I found myself despairing was striking, illustrating how confidence in what we are doing can quickly unravel when it feels as if things are not working. It’s an experience of writing which often makes me think back to one of my favourite poems by Nietzsche:

The pen is stubborn, sputters – hell!
Am I condemned to scrawl?
Boldly I dip it in the well,
My writing flows, and all
I try succeeds. Of course, the spatter
Of this tormented night
Is quite illegible. No matter:
Who reads the stuff I write?

– Friedrich Nietzsche, The Gay Science, Prelude: 59

Or as it occurred to me this afternoon: “this is shit and no one is going to want to read it.”

But when I had reached my target, letting myself ‘give up’ for the day, I turned to reading instead. Hoping that reading for my project would help ensure tomorrow’s writing would not be another ‘tormented night,’ I continued with Testing et al (2021) only to discover the extract I quoted at the start of this section. There was something about their concatenation of elements which might not immediately come to mind when writing (“managerial directives, quality procedures, disciplinary conventions, departmental environment” etc) which prompted my imagination.

I seized upon the idea I could feel germinating within me, and this section emerged in a matter of minutes. It was 631 words, up until the end of that sentence, which flowed out into what had only thirty minutes earlier felt like an arid desert. The sun has started to shine, and it suddenly feels like my ‘writing afternoon’ has lived up to the name, leading the turgid undertaking which preceded it to fade into the background.

Not only do I feel connected once more to what I’m doing, I feel energised, as if the writing has in some real but mysterious sense recharged me. This experience reminds me of the nexus I described at the beginning: how our writing practice sits at the intersection of so many factors, both internal and external. When these elements align, we can move from struggle to that elusive “unconscious fluency” that makes the act of writing not just bearable, but genuinely joyful.

#academicWriting #digitalScholarship #generativeAI #writing

Machine writing and the challenge of a joyful reflexivity

If you see the use of generative AI as being about producing entire outputs purely based on your instructions, without having to directly contribute yourself, you miss out on the multifaceted ways in which we can work with these systems as part of the writing process. Rather than substituting for our own writing, it can become interspersed with it. We write over things which generative AI has produced. We use generative AI to write over things we have produced. We rapidly find ourselves with nested hybrid passages in which automated and human outputs intermingle in complex ways. The problem isn’t keeping human-generated text free from machine-generated text. The real issue is finding ways of using these new capacities of machine generation to realize the values that lead us to write in the first place. It’s the quality of what we produce that matters more than how it is we produced it.

It remains an open question whether it should be admissible to include any machine-generated text in academic outputs. The evidence we’ve seen suggests we already have many academics using generative AI to author parts of their texts in problematic and unspeakable ways. I worry about a situation in which we have a dual consciousness with everybody explicitly stating that we shouldn’t include machine-generated text in our work, and yet a widespread recognition that many people are doing this. It might be that in these situations, they offer an excuse that they were particularly busy, or this was a one-off, or there is some other extenuating circumstance that allows for the use of machine-generated text in this particular output.

This dual consciousness is a familiar feature of professional discussions about how we use technologies which have recently entered our life worlds or how we cope with the shifting technical infrastructure through which we disseminate our work. I have been in editorial board meetings where a lunchtime conversation about the idiocy of metrics is followed by a serious exchange about how we can improve the journal’s impact factor or better publicize the improvements we have already seen. I have encountered academics who I have seen in print and/or speech talk stridently about the dangers of an attention economy infecting higher education subsequently ask with utmost seriousness in a workshop about how they increase their number of Twitter followers.

In fact, I have taken part in these conversations without feeling the cognitive dissonance which it immediately feels they should have provoked when I record the experiences in writing. It is unnervingly easy to fall into this gap between how we talk and how we act, imagining that we are taking an important stance when we criticize something while nonetheless acting in ways which actively endorse it in practice (Bacevic 2020). What matters is how we act rather than how we talk about our action or inaction. It’s not enough to claim we recognize the temptations of using GenAI to increase our productivity, if we fail to examine our actual concrete experiences of that temptation in a way liable to shape the choices we make about how to act.

I certainly understand the temptation. It’s something that I’ve experienced myself. For instance, in a recent writing project, I found myself facing an impending deadline, and despite the fact that I had, on principle, refused to use AI-generated text in my work, I was, when struggling to meet this deadline, suddenly struck by the realization that I could finish this piece and move on with my day in twenty minutes if I were to draw on ChatGPT or Claude to write it for me. The possibility that we could have an immediate resolution to the challenge, that this thing that we’re struggling with, that is making us feel incapable, could be overcome with machine assistance, is very tempting. When we’re busy, when we’re stressed, when we’re rushing, when we’re overworked, we’re likely to face these challenges as a routine part of our work and life. And the possibility that generative AI can then ride to the rescue, alleviating us from our burden, is going to be very enticing.

This is exactly why, if we are to establish norms about the scope of use of generative AI, we need to do whatever we can to ensure that they’re binding, that they’re things that we really mean, that we really want to follow, rather than things that we expect others to do in public discussion, while privately doing something else entirely, and comforting ourselves by saying that we know other people are doing the same. We need to find some way to be consistent, and we need to grapple with the real and serious problems at stake here, rather than offering superficial answers, which we think are what our colleagues want to hear. There are deep issues here, and if we fail to get to grips with them, I’m arguing that not only do we forgo the pleasures that come from writing, we are also at risk of doing fatal damage to the knowledge system over time.

It matters, therefore, what we do in those moments of temptation. It matters that we are able to talk about those temptations, that we are able to recognize that we face common professional problems, and these emerging technologies provide potentially destructive solutions to those problems. It’s only through these discussions that we are going to be able to find professional norms and standards which are adequate to the challenges on the horizon, but it’s also the only way we’re going to be able to elaborate our own reflexivity as writers, as well as the reflexivity of the writing culture within the academy, to meet these challenges. What I frame as the enjoyment of writing is how to find a joyful reflexivity, in which our relationship to the process isn’t just an exercise we methodically plod through as a matter of obligation, but rather an activity we are passionate about.

#academicPractice #digitalScholarship #generativeAI #LLMs #machineWriting #reflexivity #writing

Delighted to be at days 3 and 4 of #ASECS2025! Looking forward to papers on #ThomasGray, the 'low-brow' 18th c., #DigitalScholarship we should be using, the global 18th c., and #DigitalTools for the exchange of ideas.

https://asecs.org/preliminary-schedule-2025/

#c18th #poetry #DH
@asecsoffice