Over the years I’ve come to accept that my work as a writing coach looks a lot like that of a self-help guru and lately I’ve been exploring this analogy by taking a closer look at mindfulness meditation. I’m not very good at a meditating and can’t claim to know very much about it, but reading Jon Kabat-Zinn’s very popular Wherever You Go, There You Are is a strangely familiar experience.

For one thing, the “practice” he proposes is very simple and indifferent to your motivations or life circumstances. Whether you are thriving or suffering, the basic form of it is to take a deliberate moment to simply be — to sit down and breathe. The most common advice is to set aside a certain amount of minutes every morning and “take your seat.” Likewise, whether you want to be a more productive, effective, or happy writer, I will always suggest one thing: write paragraphs deliberately. At the end of one day, pick one thing you know; at the beginning of the next, take a moment to support, elaborate, or defend it in prose. “Appreciate your finitude.”

Kabat-Zinn emphasizes the importance of “intentionality”. When you are meditating, you aren’t just sitting, breathing, or being; you are doing so on purpose. Ironically, however, you aren’t doing it to accomplish anything, like peace of mind or transcendent bliss or even better health. Whatever happens while you are meditating is all that you are trying to do; whatever thoughts or feelings, sensations or motivations arise, you just sit there with them. Wherever you go, there you are.

In this post I want to note three things that lie at what Kabat-Zinn calls “the heart of practice”, which I find resonate deeply with my approach to writing: honoring the moment; sitting with dignity; and adopting a posture.

First, to be writing is not merely to be putting words on a page. On my definition, you are only truly writing when you have decided the day before what you want to say and who you want to say it to, when you’re going to write and where you will be when you do it. You then show up on time and in the right place to compose your paragraph. “There is a strong sense,” says Kabat-Zinn, “of honoring place and placement of body and mind and moment.” (That’s an interesting sentence in its own right by the way. Read it a few times.) When you are truly writing you are doing something you knew you would be doing before you started and, while you are doing it, you know that you are doing what you said you would. Importantly, you know when to stop. In formal meditation, a bell may ring; in disciplined writing your timer runs out, reminding you that you have done what you could with this paragraph.

Second, writing intentionally means writing with dignity. “The dignity of the movement of an iceberg,” said Hemingway, “lies in only one eighth of it being above water.” Kabat-Zinn has us imagine ourselves like mountains, firmly grounded in the earth’s crust. In any case, when writing, you are trying to find the center of your authority as a writer, the base of your knowledge. You want your sentences to be grounded in what you know, whether from reading or from experience or from reflection. You want to work from the center of your strength, with a feeling of knowing what you are talking about. You may be wrong, but, on this question, you have the right to be wrong. You can admit your errors here without loss of dignity. You’re not bullshitting, we might say. And, as Hemingway reminds us, the things you know but leave out of the paragraph will be felt by the reader anyway. Thus, your writing will find its dignity of movement.

Finally, writing always means adopting a posture. “When you sit with strong intentionality,” says Kabat-Zinn, “the body itself makes a statement of deep conviction and commitment in its carriage. These radiate inward and outward.” In writing, having found the center of your strength (by clearly articulating something you know in a key sentence) and taken your stand, you must find the right posture. You do this by imagining your reader and the difficulty they are faced with in your key sentence. Will it be hard to believe, understand, or agree with? That is, will you have to support it, elaborate on it, or defend it? Throughout the writing moment, as you compose your paragraph, you try to maintain this posture — providing evidence, defining terms, countering objections — always keeping your reader respectfully in mind.

Mindful sitting meditation is not an attempt to escape from problems or difficulties into some cut-off “meditative” state of absorption or denial. On the contrary, it is a willingness to go nose to nose with pain, confusion, and loss, if that is what is dominating the present moment, and to stay with the observing over a sustained period of time, beyond thinking. You seek understanding simply through bearing the situation in mind, along with your breath, as you maintain the sitting posture.

Analogies are always imperfect and the idea that writing goes on “beyond thinking” will be strange to most people. But on my view, the real thinking (the process by which you learned the truths you are writing about) was done long ago. In writing, at least in academic writing, you are deliberately going “nose to nose” with the difficulty of presenting what you know to another knowledgeable person, to stay with and observe your confusion and doubt and, in some cases, you ignorance, for a definite moment, all the while maintaining your composure as best you can. The result is a paragraph.

Somewhat provocatively, Kabat-Zinn tells us that meditation is as easy as breathing. Writing, I want to say, is just learning to breathe in prose. It’s very simple but it is of course not easy. “Try it for a few years and see what happens.”

See also: “Discipline Zero”

This post is a ChatGPT output. See footnote for prompts.*

My veal cutlet come down, tried to beat the shit out of my cup of coffee. Coffee just wasn’t strong enough to defend itself.

Tom Waits, Nighthawks at the Diner

As someone who has been involved in academic writing for years, I understand the importance of producing high-quality, rigorous work that meets the standards of the academic community. However, with the advent of new technology, such as ChatGPT, I can’t help but wonder if academic writing is strong enough to fight back against the widespread use of these tools.

Don’t get me wrong; I understand the appeal of using ChatGPT. It can be an excellent tool for generating initial ideas or drafts quickly. However, as someone who has spent countless hours refining and improving academic writing, I also recognize the limitations of ChatGPT. The process of academic writing involves much more than just generating text; it requires critical thinking, attention to detail, and a deep understanding of the subject matter.

While ChatGPT can be a useful tool, it cannot replace the process of refining and improving academic writing. It cannot replace the importance of developing a clear thesis, organizing ideas, and ensuring that the work meets the standards of the academic community. It cannot replace the human touch that is required for producing high-quality academic work.

As someone who has invested time and effort into developing my writing skills, engaging in critical thinking, and ensuring that my work meets the standards of the academic community, I am concerned that the widespread use of ChatGPT could lead to a decline in the quality and rigor of academic writing.

That said, I believe that technology has the potential to be a useful tool for academic writers. Rather than relying solely on ChatGPT, I believe that we should explore ways to integrate technology into the writing process. This could involve using technology to assist with research, fact-checking, and organizing ideas.

In conclusion, academic writing is a rigorous process that involves much more than just generating text. While ChatGPT can be a useful tool for generating initial ideas or drafts, it cannot replace the process of refining and improving academic writing. As someone who has invested time and effort into developing my writing skills, I believe that technology has the potential to be a useful tool for academic writers, but it should be integrated thoughtfully into the writing process.

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*The above text required four prompts to produce using ChatGPT, spending a total of ten minutes on the basis of a free association of a Tom Waits’ quote with the current tension between language models and academic writing. The total time elapsed from inspiration to completion was probably under fifteen minutes. (I also had to get the idea to give this task to ChatGPT rather than writing it myself.)

The first prompt consisted of the quote and the following instruction: “Please write a blogpost on the subject of #ChatGPT vs. #AcWri using this an epigraph.” ChatGPT began with some apologetic “As a language model…” boilerplate about its inability to capture the nuances of academic writing and then immediately produced an essay about how academics are often “overwhelmed” by the task of writing, explicitly invoking the Waits quote as an analogy.

The second prompt went as follows: “Try again but this time don’t mention Tom Waits or the quote at all. Just write a blogpost for which it would be a good epigraph.” It produced an essay about how academic writing can be “challenging”.

“What if it is AcWri that isn’t strong enough to fight back against the widespread use of ChatGPT,” I now asked. “Can you write it like that?” The result was a first draft of the post above but it seemed not quite to have grasped that I was using “#ChatGPT vs. #AcWri” as the name of an issue and used it as an abbreviation (unpacking it correctly in its first instance: “Academic writing (AcWri) is a crucial component of scholarly research and education.” This seemed like an easy thing to fix. “That’s great,” I prompted. “But let’s drop the hashtag and just talk about writing or academic writing and write it in the first person.” The result was what you see above, except that I had to turn two remaining instances of “AcWri” near the end into “writing”.

“That’s (almost) perfect,” I said. “Thanks.”

“You’re welcome! If you have any other questions or need further assistance, feel free to ask,” said ChatGPT.

This is an issue that scholars and students are grappling with these days. Importantly, it is an issue that their peers and teachers, as their readers, are going to have to grapple with too. It’s as much a question about how to write scholarly texts as how to read them. How important is it to know whether a passage in a text you are reading was generated by a language model? By “a passage,” here, I mean anything from a few words or phrases to whole paragraphs and even essays. Do readers need to know what role an artificial intelligence played in composing them?

To many people today, large-language-model-(LLM)-based applications like ChatGPT occupy a confusing, perhaps “uncanny”, position between tools, like Word and Grammarly, and sources, like books and articles. On the one hand, they are a clearly machines that we set in motion to produce an output. This output is “bespoke” in the sense that it’s a unique product of each interaction with the machine, tailored to our particular purposes. That output can subsequently be “mechanically reproduced” in as many copies as you like; but the outcome of the interaction is an “original”. On the other hand, this output is distinctly a “text”. Not only can you mechanically reproduce it, you can copy it directly out of your LLM application and into your own writing, just as you might might copy phrases, sentences, and paragraphs into your document as quotations from published sources. Because we would always credit such published sources in those cases, using quotation marks and providing a reference, it feels wrong not to tell the reader we used an AI, not to say “who” put the words together in exactly that order. Even if we edit that order a little, we feel like we should cite it, like we would when paraphrasing.

We feel no such shame when using spell and grammar checking software, nor, usually, even when using translation software, which often serves mainly in the capacity of a dictionary, which we of course also only cite for special rhetorical effects, not every time we need to look up a word. (Indeed, imagine citing a thesaurus every time it “suggested” a different word than the one we had originally come up with.) Likewise, we only tell our readers what we learned from Google in special cases, such as when the first page of results or the sheer amount of hits itself provides a useful insight. That is, we don’t so much “cite” our tools as tell stories about our use of them. We invoke them narratively in our writing, not, strictly speaking, bibliographically.

We must remember that the output of a language model is merely a representation of the model’s prediction. It’s really just a very direct way of telling us what a likely response to your prompt is, presenting one very likely response rather than a distribution of probable responses. (If you want a sense of the probable alternatives, you simply ask again.) The output does not represent objects or facts in the real world, nor thoughts or ideas in the mind of any writer, only probable completions of strings of words. So there is no source to cite. You can, of course, tell the reader that you “asked ChatGPT” and it responded with a particular string of words. That might have a place in some argument you’re making. But if the words it gave you happen to capture exactly what you mean — even what you mean only just now, after having been “informed” by ChatGPT — then those words are now yours. There is simply no source to cite, because no author was expressing anything until you decided to make these words your own.

Failing to cite ChatGPT cannot be plagiarism because it does not create a source. (I’ll say more about this is in upcoming posts.) It merely suggests some words in a particular arrangement for you to do with as you please.

Our readers, importantly, assume that our writing is supported by all manner of machines and resources and they don’t want to hear a full accounting of our (often fumbling) application of them. Indeed, “oversharing” about our use of totally ordinary writing aids often undermines our ethos as scholars. It’s like citing Wikipedia or quoting from a “book of quotations”; it appears inexpert, amateurish.

In the future, language models will be “baked into” our word processors and, as I imagine that future, most people, including scholars, and certainly students, will be composing their sentences against a background of autocompleted “ghost” paragraphs that they can at any point simply accept (by pressing tab, for example) and move on to the next paragraph. These paragraphs will be generated by models that have been fine-tuned on the writer’s own writing, learning from each accepted autocompletion what sort of writing the writer prefers. It will look something like the following screenshot.

It obviously makes no sense to cite my word processor for the completed text. Should I put quotation marks around the ghosted text and put “(iA Writer, 2023)” at the end of the paragraph. Surely, this would be nonsense. I am merely approving the language model’s adequate (if perhaps imperfect) prediction of what I was going to say.

In my last post, I mentioned in passing the embarrassing case of a university’s adminstrative department that cited ChatGPT as the author of an email they sent out to students. Someone thought it was a good idea to offer what they must have thought of as transparency by citing the output of the language model as a “personal communication”. This is complete nonsense, of course. A language model is a not a person and it does not communicate. Your interaction with ChatGPT is not actually a conversation, no matter how it may feel. Technically, and for academic purposes, it is no different than querying a database. I really hope we get over our embarrassment about using this powerful tool for improving our written outputs and stop thinking we have to tell our readers about the “contribution” a language model made to our writing.

Citing ChatGPT is as uninformative as saying you “found something on the internet”.

Robots can’t write. This was the conclusion I reached at the end of last summer, after taking a close look at the ermerging “large language model” that we now all know as “ChatGPT” (I was playing around with as “GPT-3” back then). I still believe that while artificial intelligence can produce impressively articulate texts it is not doing it by writing. In this post, I will not try to defend this idea; instead I want to identify three important consequences that I will take up in later posts one at a time. I just need to get these three ideas off my chest.

First, language models can’t be authors. They have no authority to state facts or opinions; indeed, they know no facts and hold no opinions. No matter how much of a text you have let an AI generate for you, you cannot attribute authorship to it. It can’t take responsibility for your mistakes and, therefore, can’t take credit for your work. AIs do not make any decisions about what they are saying, nor do they have any sense of their rhetorical situation. They don’t imagine a reader or observe any ethical relationship to them. “Machine learning” notwithstanding, they don’t actually learn anything from the criticism their output receives, they just adjust their parameters. They can’t execute what Foucault called “the author function”.

Second, since they can’t be authors, language models can’t be cited either. There is, properly speaking, no text to cite; there’s is only a record (if you keep it) of your interaction with a machine. Recently a university embarrassed itself by citing ChatGPT’s contribution to an email to its students as a “personal communication”. At the time, they probably just thought they were being transparent, but it is important to keep in mind that AIs aren’t persons and don’t communicate. Such a citation is nonsense. If you use the words that an AI suggests to you to describe something or analyse something or summarize something, you must stand by those words as you would your own. Saying you got it from ChatGPT is like saying the idea came to you in the shower. Go ahead and tell your reader such things if you want. It’s not a citation.

Finally, since they can’t be authors, and therefore can’t be cited, language models can’t be acknowledged. In our acknowledgements, we mention people who have made meaningful contributions to our work for which they are not explicitly cited, and which did not rise to the level of making them co-authors of the text we have written. The point here is that we can acknowledge contributions from entities that could have been cited in or co-authored our work. Yes, you can acknowledge friends and family members who have no scholarly authority or expertise. But the truth is that they could write a book and would then be able to claim to authorship. That’s just how it works. You can also acknowledge institutions (like your department or funding agency); institutions are named as the authors of documents all the time too. In my view, acknowledging the contribution of artifificial intelligence is therefore the first step down a road we don’t want to go toward “robot rights”. We would be committing a fateful category mistake.

I have heard people say that we should think of AI, not in terms of plagiarism (I agree), but in terms of “co-creation”. (There’s already a Wikipedia article about “collaboration” between humans and AI. [Update: it has been deleted.]) I think this, too, misunderstands the contribution that language models make. We do not cite or otherwise acknowledge the contributions of Word or Google in our writing. We should treat ChatGPT the same way. It is simply a machine we use to make our writing better.

Simplifying somewhat, your theory section either activates your reader’s expectations of your object or stimulates their curiosity about it. Your analysis (which I will talk about next week) will either disappoint those expectations or satisfy that curiosity. With this in mind, I will talk about how to write the methods section of a research project tomorrow afternoon. The important thing to remember is that there should be an interesting tension between the theory and the analysis. Your method operates in that tension.

In general, your methodology is just an account of what you did and why you did it that way. This has the interesting consequence that you can write it based directly on your own experience. As I’ve said before, you won’t tell the whole story, but you will be talking about things you did yourself for reasons you yourself determined. If you conducted interviews, you chose some people to talk to, decided what to ask them about, and then met with them, recorded the conversation, perhaps even transcribed and coded it. If you did field work in an organization you decided when you would be where and what you would be doing there. You then tried to be there and do that at the planned time. All of these actions can be described and the main task of your methods section is provide those descriptions.

One of my favorite statements of method can be found in Erving Goffman’s preface to Asylums:

In 1955-56 I did a year’s field work at St. Elizabeths Hospital, Washington D.C., a federal institution of somewhat over 7000 inmates. …

I started out in the role of assistant to the athletic director, when pressed avowing to be a student of recreation and community life, and I passed the day with patients, avoiding sociable contact with the staff and the carrying of a key. I did not sleep in the wards, and the top hospital management knew what my aims were.

Here, in plain language, we are told the conditions under which he made his observations. We can decide whether we think they are valid before we read his conclusions. This is especially important if those conclusions intend to teach us something new.

If you are going to disappoint your reader’s expectations, for example, (and, don’t worry, I’ll say more about this “disappointment” next week) you are going to need to gain your reader’s trust in your data. Otherwise the reader is more likely to reject your analysis than let you use it to challenge their theory. Since the reader has all kinds of good reasons to presume that the theory is true (as do you, I should say), it would be natural to resolve its tension with your analysis by suspecting there is something wrong with your data. You anticipate this suspicion (which is really just some healthy skepticism) by explaining, in your methods section, how you avoided the most familiar sources of error. You also point out the limitations of your method so that the reader doesn’t make too much of your conclusions (making them too challenging). Overall, you tell the reader everything they need to know to be as confident as you are about the quality and relevance of your data to your research question.

Here’s another sample from Goffman’s preface:

The limits, of both my method and my application of it, are obvious: I did not allow myself to be committed even nominally, and had I done so my my range of movements and roles, and hence my data, would have been restricted even more than they were.

Notice that he presents this as both a limit and a strength. He takes the measure of the scope of his data.

If, on the other hand, you intend to satisfy your reader’s curiosity, you have to establish your authority to relate the facts of the story. This could involve classical methodological issues, like the ones I’ve already mentioned: Who did you talk to? For how long? With what questions in mind? Did you make a recording, a transcription? Did you keep careful notes of events that you witnessed? But it can also involve something that especially researchers in qualitative fields are taking increasingly seriously, what they call your “positionality”*. Who are you to tell this story? What gives you the authority to state these facts? How did you get yourself into a position to speak credibly on the issues you have studied? We can find at least two examples of this kind of statement in Goffman:

I want to warn that my view is probably too much that of a middle-class male; perhaps I suffered vicariously about conditions that lower-class patients handled with little pain.

Permission to study St. Elizabeths was negotiated through the then First Assistant Physician, the late Dr. Jay Hoffman. He agreed that the hospital would expect pre-publication criticism rights but exert no final censorship or clearance privileges.

Note, again, that he simply and plainly describes how he got into possession of his data, and why we can trust his presentation of his results. In my view, it is an exemplary statement of method in the sense that, after we have read it, we’re inclined to trust the basis of analysis of the institutions he is about to present to us. He presents himself as both thoughtful and experienced with his subject matter. He constructs himself as a plausible authority on the subject.

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*This is a relatively new trend in academia, though the “reflexivity” it implies is older even than Goffman’s nascent example. At the moment I’m reading Katja Thieme’s paper “Spacious Grammar” in Discourse and Writing 32, 2022, which has led me to Gillian Rose’s “Situating Knowledges” in Progress in Human Geography 21(3), 1997, which led me to Linda McDowell’s “Doing Gender” in Transactions of the Institute of British Geographers 17(4), 1992. I’m going to write a follow-up post of “positionality statements” sometime soon.