Have you ever been emotionally moved by something you’ve read? If so, you might start to understand why bibliotherapy can be a powerful tool.
Even if you’re not a book enthusiast, there’s probably been a time in life when you’ve read something that resonated with you or related to a situation you’d found yourself in.
The power of words on emotions can be immense. Reading the right words can summon tears, laughter, anger, or a drive for self-change.
Words can educate and provide insight. At times, words can be a valuable source of comfort.
When you’re navigating mental well-being challenges, this power of words could be used in a form of treatment called bibliotherapy.
Also known as book therapy, bibliotherapy was discussed as a psychodynamic model in the 1950s by Caroline Shrodes.
In 1966, it was officially introduced into medical vocabulary as the process of using literature to encourage cognitive change.
In its base conceptual form, bibliotherapy was seen as a way for people to solve personal challenges through directed reading.
Since that time, however, bibliotherapy has evolved.
It’s often used as a supplementary form of treatment in various psychotherapy approaches and could involve everything from reading in private to discussing literature in groups.
While books are one of the most common components of bibliotherapy literature, any format of written work might be used, including:
At its core, bibliotherapy is intended to help bring about personal change through reading.
What this means for you might be different than what it means for someone else. You might not prefer reading poetry, for example, but gain more insight from informational work.
The exact classifications of bibliotherapy vary among scholars but generally fall into two categories split by areas of application:
Clinical: using literature as a means of creating cognitive change related to psychological needs and therapeutic goals
Developmental: informational materials used by both medical professionals and other educators to help assist with natural life transitions, such as puberty
Clinical bibliotherapy might be further broken down into subcategories based on the literature that affects you the most, your preferred style of learning, and the mental well-being challenges you’re facing.
You might benefit from:
Creative bibliotherapy: the use of guided fictional work as a way to address similar scenarios in your own life
Prescriptive bibliotherapy: nonfiction books and literature intended to offer self-help options at home or with professional treatment
Bibliotherapy could be used as a way to provide insight.
You’ve likely heard the quote, “Can’t see the forest for the trees.” This is often used to imply that sometimes we can get stuck looking at what’s happening in the moment rather than at the larger picture.
When you’re stressed and worried, you might not know what to do or where to go. You may not be able to imagine any other scenario than the worst case one.
You might not yet realize the emotional impact your behaviors have on you and those around you.
Literature could help pull back the veil. It could guide you to that next self-help step, or help you experience emotional ramifications through the adventure of a fictional character.
Bibliotherapy isn’t just a mental health term — it’s a tool that could be used in many professions to help encourage learning and personal growth.
Bibliotherapy could help guide things such as relationships and substance use disorder recovery. It could help provide broader scopes of understanding that might help combat negative social constructs, such as racism.
Research has shown bibliotherapy could have a positive impact on:
It’s natural to feel overwhelmed, alone, or lost when you’re going through a big change in life or are experiencing mental health challenges.
Literature — both fiction and nonfiction — might help you develop a higher level of awareness and understanding of your motivations and behavior.
You could learn the “why” behind what you’re experiencing through science-based reading. At the same time, you could have guides, exercises, and coping recommendations on hand for easy reference.
Through fiction, you could view your scenario through the eyes of a character. In many cases, you might reach an emotional release through that fictional journey before you reach it in your own journey.
This emotional experience in fiction is what Aristotle referred to as “catharsis” during his own observations on the impact of stories on human emotions.
When is directed reading not good for mental health?
Literature could be used for both positive and negative outcomes. In fact, experts noteTrusted Source that some bibliotherapy could be harmful.
Propaganda, which is deliberately skewed or misleading information, is often spread through literature. It could be used to encourage unhelpful or harmful beliefs and viewpoints.
A 2020 study suggests that propaganda could be a powerful tool of emotional manipulation.
don’t respond strongly to learning through reading
Many other factors could contribute to the decision on whether to include bibliotherapy in your treatment plan.
You might not yet be at a point where bibliotherapy makes sense. Distressing memories, current stress factors, and your mental well-being could all influence the way literature impacts you.
Bibliotherapy is usually guided by a mental health care professional.
Based on what challenge you’re facing, you’ll likely be given a reading recommendation. In most noninformational and educational cases, the goal is to introduce you to a character — fictional or nonfictional — with whom you might identify.
These characters might be going through a similar challenge as you, for example.
While you navigate bibliotherapy reading, you could experience an array of emotions as you go through the story with the main character.
You might feel their highs and lows, and some of the emotions could be strong as you subconsciously relate them to your own life.
You might also have eye-opening realizations during bibliotherapy. Sometimes hearing an idea in just the right way could really make it “click.”
As your reading progresses, you might find that you could envision alternative options, new paths of thought, or even the growth of hope that things might not be as dreary as they once seemed.
Bibliotherapy could provide you with new rational insight you could then discuss with a mental health care professional.
Bibliotherapy, aka book therapy, is the use of literature to help overcome challenges in everyday life.
Whether you’re living with a mental health condition or simply going through a natural life change, the right reading material could help increase your intellectual insight — toward yourself and the people around you.
While most bibliotherapy in the clinical setting is guided, self-help books and reading literature at home that empowers you could also be considered bibliotherapy.
Monroy-Fraustro D, et al. (2021). Bibliotherapy as a non-pharmaceutical intervention to enhance mental health in response to the COVID-19 pandemic: A mixed-methods systematic review and bioethical meta-analysis. https://www.frontiersin.org/articles/10.3389/fpubh.2021.629872/full
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TikTok is awash with misleading information on ADHD. There’s also a gender bias among doctors. It’s left women in Asia fighting for a diagnosis and help.
Are you clumsy? Do you think your friends secretly hate you? Well, then you must have ADHD. At least, you may think that if you follow videos on social media, like Instagram and TikTok. But don’t fret.
But here’s the thing with ADHD: For a long time, even those officially recognized symptoms have included significant blind spots — most of which affect girls and women. That is, their symptoms have often been dismissed or simply overlooked.
The reason for that lies in a historical understanding that ADHD presents as hyperactivity, making wild, screaming little boys struggling at school the textbook example for people with ADHD.
But daydreaming is a very real symptom of ADHD. Other symptoms include:
forgetfulness and misplacing things a lot
squirming or fidgeting
talking too much
making careless mistakes or taking unnecessary risks
having a hard time resisting temptation
“But the leading symptom is [a person having] trouble managing [their levels of] attention,” says Alexandra Philipsen, Director of the Department of Psychiatry and Psychotherapy at the University Hospital Bonn and an expert in ADHD.
Their fight for diagnosis and treatment
Jnanee from Singapore and Alisha and Sonal from India had to wait until they were adults before they were diagnosed with ADHD. And all those years while they waited, they experienced significant struggles in their personal, educational and professional lives. Among those struggles were problems with maintaining attention and staying focused. Many people can relate to those feelings.
But in this video you will see why that doesn’t necessarily mean you have ADHD, why a diagnosis is quite complex and how these three women from Southeast Asia fought their way to a diagnosis. An ADHD diagnosis certainly isn’t all doom. It’s helped people harness pretty amazing strengths.
Edited by: Zulfikar Abbany
Katja Sterzik Science journalist with a passion for visual storytelling, TikTok/Insta/YouTube and skateboarding
The medical community declared a national emergency in child and adolescent mental health during the COVID-19 pandemic. Now a new report shines a light on another important aspect of the story — the influence that mental health challenges faced by parents and primary caregivers have on teens.
“It’s a fundamental tenet of psychology that children don’t grow up in isolation,” explains Richard Weissbourd, the study’s lead author and faculty director of the Making Caring Common Project at the Harvard Graduate School of Education. “They grow up embedded in families, embedded in communities — and to understand the experience of teens, it’s really important to understand their context.”
The data collected by Weissbourd and the report’s co-authors, through two nationally representative surveys — one with teens and young adults and another with parents/caregivers — reveal parental anxiety and depression rates that are similar to those experienced by teens.
In the survey 18% of parents reported anxiety and 13% depression, while 18% of teens had anxiety and 15% suffered from depression. (Depression and anxiety were defined as being depressed or anxious more than half the time over the two weeks prior to the survey.)
Rates of depression and anxiety were higher for mothers and teen girls than fathers and teen boys.
More than a third of the teens surveyed had at least one parent suffering with anxiety or depression and close to 40% of the teens said they were at least “somewhat worried” about their parents’ mental health.
There is a strong link between the mental health of parents and the mental health of adolescents. According to the study, “depressed teens are about five times more likely than non-depressed teens to have a depressed parent, and anxious teens are about three times more likely than non-anxious teens to have an anxious parent.”
It takes a village — caring for the caregivers
More treatment providers are needed for teens and parents, particularly in under-resourced communities, but the researchers add that a critical way to prevent the many mental health problems that teens are experiencing is to improve the emotional health of parents — “to care for the caregivers.”
They call for broader efforts by organizations including government agencies, policymakers, faith-based organizations, public libraries, employers, and schools, to support parents’ mental health and to assist parents in promoting their teens’ mental well-being.
Five strategies to support parents and help them to prevent anxiety and depression in teens:
Listen to adolescents. In their focus groups and interviews, the researchers heard many young people explain that they need their parents and caregivers to be better listeners and to be more proactive about checking in with them. The reports suggests that parents can become “important sounding boards and advisers to their teens” by approaching them with “openness and curiosity,” listening carefully, and empathizing with them “rather than judging or jumping to solutions.”
Help teens develop coping skills. Parents need basic facts about anxiety and depression, including the different forms and stages of the disorders and how to detect when a teen needs professional help. Governments and community institutions can run public education efforts to better inform parents. Providing resources for caregivers to use with their teens, including cognitive-behavior and stress-management strategies and advice for encouraging good sleep, nutrition, and technology habits, are also helpful. Parents may feel significant shame or stigma about their teens’ mental health struggles and/or their own and may need reassurance that anxiety and depression frequently have “a biological component” and are not a sign of “of weakness or a lack of will.”
Support the mental health of caregivers and families. Mental health providers “far too often” provide programs and interventions that treat teens in isolation rather than in the context of the broader family unit, the researchers say. They suggest expanding family therapy options and prioritizing resources for those at higher risk, including low-income and unemployed parents, parents with infants, new immigrant families, and those dealing with chronic medical problems or trauma. Parents also need help making supportive connections with one another. Reimagined public libraries that serve as community hubs and workplaces that help build community and give parents sufficient time off to create connections with others can help combat isolation and loneliness among parents and caregivers, the researchers say.
Help parents to talk about their own mental health challenges with children and teens. Parents can be helped with age and culturally appropriate strategies for talking with their teens about their own struggles, so their children don’t blame themselves for their parents’ emotional difficulties. It can be helpful to have parents explain directly to their teens that they have an emotional problem that has nothing to do with them, for example. However, the researchers also warn that “too much disclosure can be frightening,” for children.
Help teens find purpose and meaning through service and community programs. Thirty-six percent of the teens surveyed said they found little or no “purpose or meaning in life” and the figure was even higher for the young adults who were surveyed, Weissbourd says. (There is a strong connection between lacking purpose in life and depression and anxiety.) He believes that the “failure to reproduce important aspects of religion in secular life, like coming-of-age rituals, gratitude practices, and communities where people can grieve together,” is part of the problem.
Weissbourd and the other researchers suggest that, to help teens’ mental health, caregivers should steer young people towards activities that provide purpose and offer a break from self-concerns. One idea would be the creation of a federally run national service program that could encourage and incentivize youth to help their communities in some way, he says. High schools could also encourage more students to pursue a service year before going to college and colleges could expand their service programs.
Parents can also help teens “create an ethic of care, an ethic of service,” through less formal means, Weissbourd says. “It could be visiting your grandmother every week, helping out a neighbor with a serious disability, it could be supervising a younger sibling,” he explains.
Steve Jobs said that computers were the bicycles of the mind, because they multiplied the mind’s capacity. Will artificial intelligence (AI) be the airplane of the brain? Or just a distraction? What will be its impact on economic growth, inflation, or inequality? Will it be similar to computers and the internet? Or will this time be different?
The impressive progress shown by AI in recent years suggests that, yes, it may be different this time. AlphaGo was able to beat the world champion of Go, a game so complex that its potential number of positions is 10 and 170 zeros, more than the sum of all the atoms in the universe. ChatGPT has been able to pass the entrance exams for U.S. medical schools and the U.S. bar. DALL-E is capable of generating extremely realistic, high-resolution images from a simple textual description.
Until now, technology was used to automate repetitive activities. Consider, for example, that the word computer comes from “human computers,” the people, mostly women, who computed the necessary calculations armed with paper and pencil or simple calculators. The virtue of the computer was its ability to automate an increasing volume of calculations, replacing increasingly complex tasks. But computers had a limitation: they needed the installation of complementary infrastructure, and humans who knew how to write specific programs to teach them how to perform specific tasks.
The rapidly increasing processing power of microprocessors allowed for significant progress: the first versions of AI based on deep learning and neural networks — computer programs that roughly simulate the way the human brain learns — created programs that learned by themselves, but still required human supervision and specific, structured, and labeled databases. For example, if a neural network was trained with X-rays of cancer patients, the program “learned,” based on repetition and trial and error, to identify them among a variety of other X-rays. These initial versions of AI were limited by the availability of data and the need to structure it.
The most recent versions of AI represent a qualitative leap and use foundational models based on generative AI, among which the large language models (LLMs) stand out. The technique is similar, deep learning with neural networks, but it is qualitatively different because they learn by themselves by being able to process human language — which, by definition, is a database that does not need to be labeled — and can be applied to a large number of tasks, increasing their power and versatility almost without limit. They are models of neural networks with billions of parameters, with a level of complexity that is increasingly close to the human brain, trained with databases that capture a good part of universal knowledge.
The evolution of these models has been very fast. The data used to train them grows exponentially, and artificial data is now being created where data limits are reached. The models’ processing capacity has doubled every six months, four times faster than the famous prediction by Gordon Moore, the co-founder of Intel, that the number of integrated circuit components in microprocessors would double every two years. This allows for an intensity of learning that is hard to imagine: one day of training one of these algorithms is equivalent to 150 years of human video game training.
In addition to its capacity, AI differs qualitatively from computers in two ways. First, they are programs that can be quickly downloaded and installed, not machines that require expensive and complex complementary infrastructure. This has led to extraordinarily fast diffusion: when it was launched, ChatGPT was the fastest application to reach 100 million users.
The second advantage is that these applications do not require sophisticated programming. LLMs are queried in human language and respond in human language or images. For example, ChatGPT can be asked: “Write a 1,200-word article in English on the macroeconomic impact of artificial intelligence in the style of Angel Ubide in El País.”
For now, I am not going to reveal if what you are reading has been written by ChatGPT, or by me.
The way these applications work is “simple”: they are probabilistic models that predict which letter, word, pixel or image comes after the previous one. At all times, models such as ChatGPT, or autonomous driving applications, decide what is the “most reasonable continuation” of the last text or image they have generated, based on the model of understanding the world they have created with the database they have been trained with. As such, any activity that is likely to become a prediction problem falls within the realm of AI.
These new generations of AI are therefore revolutionary: they do not automate repetitive tasks, but creative tasks. It is the democratization of intelligence. Suddenly anyone can write with the style and vocabulary of Nobel laureates, write computer programs like top engineers, design images like artistic geniuses. Among the most repeated verbs in AI patents are recognize, predict, detect, identify, or generate — all creative tasks. With AI, the level of execution of these tasks can be raised to best practices, benefiting all workers and reducing disparities with experts. Consider, for example, that with AI powered navigation systems, the barriers to entry to becoming a taxi driver have collapsed. And now extend this example to all the activities you can think of. Of course, these models are not perfect, and sometimes give incorrect or non-existent answers (the models “hallucinate,” in AI jargon). In part, because the models have been trained in what they have to do, not in what they don’t have to do, one of the pending challenges for this technology.
The macroeconomic impact can be significant. The empirical evidence on the effect of these new generations of AI is that it reduces the time to execute tasks and increases its quality, boosting productivity per hour worked. In addition, it can accelerate the innovative capacity of society — discovering relationships and patterns of behavior in data never imagined before — and, if combined with advances in robotics, the improvement in productivity and potential growth can be exponential, raising neutral interest rates while keeping inflation low. On the other hand, it will be necessary to reconsider models of organization of work, learning, and education, and income distribution policies. And, like any technological transformation, AI carries risks. The dispute over the use and ownership of the data, the potentially malicious use of the algorithms, the ecological impact of its high computational intensity, the inherent bias in datasets, will all require a regulation that puts this process on the right path.
It’s entirely possible that this was written by ChatGPT while I was at the beach. But no, it has not been the case. Hopefully next time.
On Twitter: @angelubide
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Sunday Brendan O’Connor radio interview with Shane O’Mara. Before I read his book, I will pursue a journey on my WordPress which acts as my consolidated memories over time.
Broca’s Aphasia
Broca’s aphasia is primarily an expressive language impairment, meaning it mostly affects speaking and writing – the two ways we produce, or express, language. Comprehension of language remains relatively intact in Broca’s aphasia, while repetition of words and sentences is usually poor. People with Broca’s aphasia are often very aware of their difficulties, and that can lead to high levels of frustration and sometimes depression.
Broca’s aphasia is also known as non-fluent aphasia. Speech is effortful and sounds rather stilted, with most utterances limited to 4 words or less. A person with Broca’s aphasia relies mostly on important key words (nouns and verbs) to communicate their message. Function words, such as prepositions and articles, are often omitted. This pattern of using only content words creates what’s known as telegraphic speech – recalling a time when people paid for each word when sending a telegram.
Laura Hartenberger is a writer and lecturer for the University of California, Los Angeles Writing Programs.
As soon as I sit down to write, I feel compelled to scrub my bathtub and reorganize my filing cabinet — the most tedious chores suddenly become more appealing than the task at hand. Writing can feel so daunting that we’ve invented the term writer’s block to describe the unique sensation of its challenge,and we debate whether the ability to write well is learned or simply innate. The work requires long stretches of intense focus and undivided attention, and doing it well usually involves a prolonged process of revision. For many of us, writing feels like one of the most burdensome activities we can do.
Generative AI tools like ChatGPT offer the seductive possibility that we can optimize this laborious process. But while it can clearly optimize the time and effort of writing, ChatGPT cannot necessarily optimize writing quality. The program produces highly competent prose that usually passes as human-generated, but so far, the quality of its writing — beyond the novelty of being authored by an algorithm — is mostly unremarkable.
At the University of California, Los Angeles, where I teach writing, the common sentiment among faculty is: “Sure, ChatGPT can write — but it can’t write well.” Some professors caution students against using the tool by appealing to their egos: “You could use AI to cheat on your essay, but do you really want a C+?”
Others, recognizing that AI tools will characterize the working world into which students will graduate, are beginning to allow their use in constrained ways, framing them as automated writing tutors or advanced grammar-checking tools. But even AI enthusiasts tend to advise students to maintain authorial control by editing any AI-generated output for accuracy, style and sophistication.
The flat, conventional feel that characterizes most AI-generated writing stems from the predictive nature of the algorithm. Trained on vast databases of human texts, from books to articles to internet content, programs such as ChatGPT, Bard, Bing, and Claudefunction like sophisticated autocomplete tools, identifying and predicting phrase patterns, which makes their output feel somewhat predictable, too.
But does predictable writing necessarily mean bad writing? When we talk about good writing, what exactly do we mean? As we explore new applications for large language models and consider how well they can optimize our communication, AI challenges us to reflect on the qualities we truly value in our prose. How do we measure the caliber of writing, and how well does AI perform?
In school, we learn that good writing is clear, concise and grammatically correct — but surely, it has other qualities, too. Perhaps the best writing also innovates in form and content; or perhaps it evokes an emotional response in its readers; or maybe it employs virtuosic syntax and sophisticated diction. Perhaps good writing just has an ineffable spark, an aliveness, a know-it-when-you-see-it quality. Or maybe good writing projects a strong sense of voice.
But then, what makes a strong voice, and why does ChatGPT’s voice so often fall flat?
The Value Of Human Error
“The Elements of Style,”the classic reference book on writing by William Strunk Jr. and E.B. White, lays out a series of concrete rules. To write well, the authors say, you should abide by certain conventions, such as grouping your sentences into single-topic paragraphs. You should adhere to certain grammatical rules, like, “Do not join independent clauses by a comma.” You should “omit needless words” and write in an efficient, organized, streamlined manner.
These rules take effort for any human writer — we all miss the occasional comma splice, use a few more words than necessary or bury our main point in the middle of a paragraph. ChatGPT, by comparison, rarely makes rhetorical moves that stray from Strunk and White’s conventions unless instructed to do so, and the speed with which it spews forth efficient, grammatically correct sentences is impressive, unsettling and perhaps mildly humiliating to us error-prone human writers. For teachers trying to catch cheating students, the total absence of typos and grammatical flubs is often what raises suspicions.
We seem to tolerate and even expect a certain amount of idiosyncrasy in our writing, and the conventions themselves can be murky and variable— the Oxford comma, for instance, maintains a devoted cult of enthusiasts even while some style guides discourage its use, and languages like African American Vernacular English have their own coherent grammatical structures that differ from those of so-called standard American English. Conventions can also evolve over time — we now commonly treat “they” as a singular pronoun when a short time ago it was exclusively plural.
“As we explore new applications for large language models and consider how well they can optimize our communication, AI challenges us to reflect on the qualities we truly value in our prose.”
Writing that consistently adheres to convention is effective because its predictability makes it easy to read. If you expect to find the main point of a paragraph in its opening, you can read faster than if you had to spend time hunting for it.
But simply abiding by the rules doesn’t make excellent writing — it makes conventional, unremarkable writing, the kind usually found in business reports, policy memos and research articles. In his review of AI-generated novel “Death of an Author,” Dwight Garner describes the prose as having “the crabwise gait of a Wikipedia entry.”Even when a user prompts ChatGPT to include specific grammatical errors or to stray from certain norms, its writing tends to carry a certain flatness. By design, the program relapses to a rhetorical median, its deviations mechanical whereas ours are organic.
That’s not to say that convention flattens prose. In fact, convention lies at the root of much of the best writing — it’s rare to see acclaimed texts that stray dramatically from grammatical and stylistic norms.
Structural convention also underlies much of what we call good writing. Most prize-winning literature innovates within classic story arcs: Aristotle’s three-act structure (beginning, middle and end); Freytag’s five-stage structure (exposition, rising action, climax, falling action and resolution); or a screenwriter’s six categories of dramatic conflict (conflict with self; with others; with society; with nature; with the supernatural; and with the machine).
Indeed, the fact that AI, which is trained to detect and replicate underlying patterns in our writing, can produce such coherent prose is a testament to just how much we rely on convention, both at the sentence and structural level.
Experimental works that abandon traditional narrative structures can be critically successful but tend not to receive popular readership — for instance, Jon Fosse’s “Septology,”a seven-volume, 800-plus page novel written as a single sentence, was a finalist last year for the International Booker Prize and the National Book Award but has only a few reviews to date on Amazon. We tend to admire writing whose predominant feature is experimentalism, but readability seems to matter to us, too — how great can a piece of writing be if few have the capacity or inclination to finish it?
Using formulaic elements to produce language doesn’t necessarily mean the writing will sound formulaic — in fact, constraints can be useful creative tools. The Oulipo poets use formulas to innovate in their writing, applying algorithms like “snowball” (increasing each line length by one word), “lipogram” (avoiding words that use specifics letters), and “n+7” (replacing every noun in a text with the noun appearing seven entries away in the dictionary) to generate writing that often feels surprising and fresh.
Oddly, ChatGPT is not very good at producing writing under Oulipian constraints — it failed to generate correct responses to all of these formulas. In response to my prompt, “Write a sentence that doesn’t use any words containing the letter “E,” it wrote:
Sure! Here’s a sentence without the letter “E”:
“The big brown dog ran swiftly through the grassy field.”
In this sentence, none of the words contain the letter “e.”
The overly enthusiastic “Sure!” and the affirmatory closing line make this sample feel like it was written by a mischievous child hoping the reader won’t notice that three out of the ten words in the sentence use “E”. Whatever limited sense of spark this passage has can be attributed to the AI’s failure to adhere to the constraint, to the human-like energy that comes from its error.
The student essay is another form of constraint. To earn a passing grade, writers must conform to its rules, but to excel they must innovate within and beyond them. Students must use specific citation methods, adhere to conventions of academic writing and ensure their responses fully address a prompt’s question; at the same time, they must offer sufficiently interesting variations on the theme, evidence of original thought and dynamic phrasing that commands attention — a delicate balance most do not consistently achieve.
Occasionally, students surprise me with an unexpected idea or turn of phrase, but more often I’m struck by the similarity of their ideas and voices. And, of course, their writing is similar: They learn a standard high school curriculum. They’re mostly the same age, at the same place in life, with similar life experiences and challenges. They’ve been programmed with the same data and they’re responding to the same prompts.
“Even when a user prompts ChatGPT to include specific grammatical errors or to stray from certain norms, its writing tends to carry a certain flatness.”
Reading a batch of undergraduate essays is not unlike commanding ChatGPT to “regenerate” its response to the same prompt in new words — the program is eerily skilled at saying the same thing in countless new ways. Like students, it can meet the basic requirements of generic essay prompts but struggles to innovate beyond them; to walk the line between predictability and surprise; to keep one foot inside the box and the other outside it; to move from a C+ to an A+.
Broadly, good writing seems to require a balance of conformity and nonconformity, and at times, deliberate rule-breaking. A certain amount of Strunk and White-style convention is necessary to convey ideas coherently — after all, language is a shared system of meaning, and straying too far from its rules risks losing connection with readers or becoming unreadable altogether.
But good writers recognize that grammatical rules are dictated by problematic power structures and are not independent measures of correctness. Good writers assess the rhetorical context for their writing and make deliberate decisions about where to conform and where to stray.
The opening line of Charles Dickens’ “A Tale of Two Cities” is a horrifically long, repetitive sentence, but deliberately so:
It was the best of times, it was the worst of times, it was the age of wisdom, it was the age of foolishness, it was the epoch of belief, it was the epoch of incredulity, it was the season of Light, it was the season of Darkness, it was the spring of hope, it was the winter of despair, we had everything before us, we had nothing before us, we were all going direct to Heaven, we were all going direct the other way — in short, the period was so far like the present period, that some of its noisiest authorities insisted on its being received, for good or for evil, in the superlative degree of comparison only.
The unwieldy length and repetitive nature of the sentence is its point. Its cascade of contradictory clauses violates most basic writing advice, and its flagrant comma splices override Strunk and White’s rules. But these moves mirror the meaning of the sentence and establish rhythmic momentum, allowing Dickens to characterize the period as a chaotic, contradictory, overflowing moment through both the phrasing of the language and its meaning.
Literature and writing courses teach the art of “close reading,” or looking to sentence-level elements like punctuation, diction and syntax, for insight into the deeper meaning of the text. Perhaps a key criterion of good writing is that which rewards close reading with rich congruity between syntax and story — in other words, writing with intention.
I teach my students to understand writing conventions well enough to stray from them in deliberate, nuanced, powerful ways. ChatGPT can understand grammatical conventions, imitate them and break them on command. But because it has no intention, it can’t be purposeful in how it adheres to or strays from the rules. Its arguments are built not from critical thought, but from predictive phrase sequences — it doesn’t “know” what its passages are really about, only that their words tend to occur together, so it lacks the meta-cognitive awareness needed to selectively break the norms of composition to add layers of meaning.
When I command ChatGPT to “Write the opening to a novel set in the current moment using a series of repeated clauses,” it writes:
In the midst of chaos, where uncertainty lurked around every corner, where hope and despair danced an intricate tango, where time seemed both fluid and stagnant, a new chapter began. A chapter etched with the echoes of a pandemic that had reshaped the very fabric of our lives, where masks adorned faces like silent guardians, where distance became the bitter mediator between loved ones, where solitude embraced us with its relentless grip.
The result isn’t terrible, but it has an overly familiar feel; the “new chapter” and “fabric of our lives” are tired phrases, and the repetition is not as musical or energetic as the Dickens opening. Elevating the writing with textual layers and nuanced opportunities for close reading would take word-by-word human editing.
“ChatGPT can understand grammatical conventions, imitate them and break them on command. But because it has no intention, it can’t be purposeful in how it adheres to or strays from the rules.”
Writers who use AI as a drafting tool might be seen as intentionality remixers, drawing copy from ChatGPT as raw material and weaving purpose into the syntax and language. But so far, the chatbot on its own, or even with the support of savvy prompt engineering, does not excel at this particular task.
Making Intentional Choices
Beyond simply deciding whether to adhere to convention, good writers make countless subtle rhetorical choices. What accounts for these choices — why is one iteration of a sentence better than another that says the same thing with slightly different diction, punctuation or structure?
The seeming subjectivity of the answer is at the root of what frustrates many students about graded writing assignments and most folks who compose things more intensive than a Slack message — but the subjectivity is the point.
How we measure successful writing changes depending on what the writer is trying to accomplish, and good writers are flexible enough to adapt to different scenarios. They make intentional decisions around three elements: audience, purpose and context. Who am I writing for, to what end and in what circumstance? Answering these questions can offer guidance on, for instance, when to use a particular word rather than its synonym.
Consider the Dickens sentence above: If the author were writing for an audience of children rather than adults, he might have used simpler sentence structures; if he were writing an op-ed meant to persuade rather than a novel meant to entertain, he might have avoided the antitheses; and if he were writing a novel in 2023 rather than 1859, he might have used a different cadence and register.
It’s difficult to determine a text’s quality without considering the context in which it was written. In an ambitious attempt to create a universal measure of good writing, regardless of discipline or genre, the American Association of Colleges and Universities (AAC&U) developed a rubric whose categories focus on intentionality.It rewards writing that demonstrates “control” over syntax and mechanics; “attention” (but not necessarily blind adherence) to genre and disciplinary conventions; and “a thorough understanding of context, audience, and purpose that is responsive to the assigned task(s) and focuses all elements of the work.”
In other words, good writing isn’t about sophisticated sentences or complex ideas; it’s about unifying all elements into a coherent whole. You can write a poignant, lyrical, oblique sonnet about the rain, but if your purpose is to inform newspaper readers about the weather forecast, that’s not good writing.
ChatGPT produces weaker writing when it hasn’t received instructions about audience, purpose, and context, and must “decide” for itself what they are. Its writing improves as a user gives it more information about who it’s writing for, why and in what situation. But as these elements get more specific, it becomes harder to tell ChatGPT enough for it to generate an adequately tailored response.
The chatbot can write passable essays for standardized testsbecause the purpose and context are so general — they need to be for humans to produce texts that can be compared and ranked in an equitable way.
But in a highly specific context like a novel or a letter, ChatGPT can’t know enough to create sufficient nuance. Writing a prompt with all relevant information would be nearly impossible, and suboptimal for a technology meant to optimize our time. For creative, expressive, or exploratory writing tasks, using ChatGPT is like supervising a bumbling assistant who needs painfully detailed, step-by-step instructions that take more effort to explain than to simply do the work yourself.
Pinning Down Voice
We often say that good writing has a strong sense of voice. Speaking voices can be recognized from their tone and pitch, but what rhetorical features define a writer’s voice on the page?
I sometimes ask students to underline selections from their drafts that they believe represent their voice. Sometimes they notice patterns or tics, stylistic quirks, a repeated word or sentence structure. Some highlight sections in which they convey strong opinions or a particularly well-defined point of view. Sometimes they label whole drafts as their voice — after all, they wrote it.
Others cannot find their voice at all — it was a class assignment, so they were writing in the voice of their academic alter-ego. Those who lack confidence sometimes point to grammatical errors as examples of their voice. Their wide-ranging answers showcase how difficult it is to pin down what makes a distinctive voice.
“For creative, expressive, or exploratory writing tasks, using ChatGPT is like supervising a bumbling assistant who needs painfully detailed, step-by-step instructions that take more effort to explain than to simply do the work yourself.”
It’s a complex equation that’s impossible to catalogue definitively: Voice manifests as degrees along the scales of rhetorical and stylistic qualities — whether the register is more on the formal or informal side; whether sentences are long and varied or short and repetitive; whether the diction is simplistic or sophisticated.
Voice also comes through in the specific balance of scene and exposition, discourse and metadiscourse and in the specific argumentative angles the writer tends to take. To complicate things further, a writer can have many voices at once — a novelist who writes in the first person, channeling their narrator’s voice, is often still recognizable even through the mask.
Can ChatGPT teach us anything about what makes writing sound like one person versus another? The program is a masterful ventriloquist — its ability to imitate style is one of its most impressive and delightful features. It does so by using “unsupervised learning” to detect rhetorical patterns from its massive database of various kinds of writing, without being told what to look for.
The frustrating part is that it can’t tell us precisely what it notices — it can only deliver text that imitates these patterns, often with startling aptness. It can write recognizably in the voice of any number of characters, real or imagined, historic or contemporary, from Oprah to Jane Austen, Holden Caulfield to Matthew McConaughey, and can emulate the style of texts from the Bible to a Fox News comments section to a wedding toast.
When I input the prompt, “Write a speech about potatoes in the style of Donald Trump,” ChatGPT’s response sounds like the script from a “Saturday Night Live”sketch: “Folks, let me tell you, nobody loves potatoes more than me, believe me. I’ve been eating them my whole life. Best thing you can put on your plate. And let me tell you, our farmers, they grow the best potatoes. The best. They’re huge, they’re beautiful, they’re red, white, and yellow.”
What exactly makes this language sound like Trump — the content? The syntax? The colloquial diction — “folks” and “let me tell you”? The rhythm and repetition of “They’re huge, they’re beautiful, they’re red”? All the above? What’s striking about this example is that ChatGPT is not so much imitating Trump’s voice as exaggerating its features into a caricature, almost as if the chatbot has picked up on the man’s very essence.
Good character impressions delight us because they illuminate something fundamental about the person they imitate. Alec Baldwin claimed that the secret to his masterful Trump impression was to unlock an element of his character: “You can kind of suggest the voice, or suggest the way they look, but you’ve got to try to think of who he is,” Baldwin said in an interview. “And to me, Trump is someone who is always searching for a stronger, better word, and he never finds it.” Somehow, ChatGPT gets to that core in its potato speech, repeating the word “best” three times in three sentences.
William Zinsser, in his classic book, “On Writing Well,” explains that “we express ourselves as we do” because of the “subconscious mind.” Perhaps ChatGPT’s deft impressions show us that our language patterns reveal more about our character than we might realize. And its facility at imitating style has implications for copyright — to what extent should we view the rhetorical tendencies that make up one’s writing voice as proprietary?
Some writers seem unsettled when faced with AI renditions of their own style. Douglas Hofstadter, author of “Gödel, Escher, Bach: An Eternal Golden Braid,” noted that GPT-4, when prompted to write in his voice, produced what he termed a “Hofstader façade,” or a series of “vague generalities that echo phrases in the book” rather than a seemingly authentic replica of his writing style. And songwriter Nick Cave called ChatGPT’s attempt to write lyrics in his style “a grotesque mockery of what it is to be human.”
But the technology’s capacity for imitation will likely continue to improve: New Yorkerstaff writer Kyle Chayka observed that ChatGPT was not very effective at mimicking his own writing voice, but the AI startup, Writer, created a bot trained on his own writing to produce text in his voice that, while not perfect, was still “unnervingly effective.” Chayka expressed mixed feelings about this capability: “The robot has made me acutely self-conscious. I recognize my A.I. doppelganger, and I don’t like it.”
“Perhaps ChatGPT’s deft impressions show us that our language patterns reveal more about our character than we might realize. And its facility at imitating style has implications for copyright — to what extent should we view the rhetorical tendencies that make up one’s writing voice as proprietary?”
When a human mimics the style of another writer, the imitation can be seen as flattery, elevating the original writer’s work through its homage; when an AI does it, the act feels more like a flattening, a reduction of our voices to its discovered patterns of idiosyncrasies and tics, our variability and range limited in favor of recognizability.
Intimacy Through Writing
What is the voice of ChatGPT? When it lacks instructions to imitate a particular voice, it presumably imitates all of us, averaging our voices together into an indistinct default. Conversing with the chatbot feels like encountering someone you recognize but have never met — a voice of the masses, distant yet familiar.
(But of course, it’s not really the voice of the masses — the algorithm inherently prioritizes the writing patterns of those that have published most often, letting them dominate over underrepresented groups and writing styles.)
When speaking as itself, the chatbot sounds neutral, unanimated, optimistic, but not especially enthusiastic to be talking with you. It often opts for lists sandwiched between a clear introduction and conclusion.
When asked to comment on controversial or debatable issues, it resists taking a strong stance, instead describing tradeoffs or multiple points of view; although, it’s also been reported to have liberal-slanting political views.Its tendency to explain things in a flat, monotone style can make it sound a little condescending, yet it also apologizes when corrected — it seems to want to be helpful.
But something critical is missing from its voice: a certain sense of connection. At its core, writing is about creating intimacy between writer and reader. It’s a relational act, not a one-sided performance, and its power is in the exchange of ideas. It’s the closest we can get to inhabiting the mind of another human, the closest to escaping our own egos.
“So what?” is the common refrain of writing teachers. “Why should your reader care?” A key way that good writing achieves connection is by creating stakes, or engaging the reader by showing them why your ideas matter.
Fiction creates stakes through establishing consequences — what does the protagonist stand to lose in their journey? Argumentative writing creates stakes by establishing significance — what are the implications for the individual or society? The stakes don’t need to be high, but for the writing to be engaging, they should be urgent and viscerally apparent.
Stakes are the parts that reach up off the page and out into the world to connect with the reader, to shift their interior state, to make us want to keep reading. Without emotional stakes, even virtuosic texts can feel difficult, off-putting or cold; the emotional payoff is low relative to the energy they take to read.
We appreciate literary prowess, but engaging the reader matters more — we seem to want more than just spectacle from good writing. As readers, we need to feel like the writer is paying attention to us, trying to connect. ChatGPT cannot build a real connection with its reader — it can only imitate one.
Reading ChatGPT’s writing feels uncanny because there’s no driver at the wheel, no real connection being built. While the machine can articulate stakes, it is indifferent to them; it doesn’t care if we care, and somehow that diminishes its power. Its writing tends not to move us emotionally; at best, it evokes a sense of muted awe akin to watching a trained dog shake a hand: Hey, look what it can do.
Narrative writing tends to become more relatable and engaging as it gains specificity — but ChatGPT is a collective voice, not a specific one, and so even as the algorithm improves, we will likely continue to find its writing emotionally inadequate. Perhaps the ineffable spark of good writing and the spark of a romantic connection are related — both involve a certain energy exchange, a sense of connection across individual minds, a balance of surprise and familiarity.
ChatGPT gets closest to achieving a sense of spark when asked to juxtapose incongruous topics and styles. When commanded to compose a sonnet about McDonald’s, for instance, it writes:
In golden realms where cravings find their bliss,
Where hunger’s fire meets flavor’s sweetest kiss,
There stands a haven with arches of gold,
McDonald’s, where delights and dreams unfold.
The writing isn’t Pulitzer-worthy, but it has a certain energy that perhaps stems from the surprise of seeing how the program tackled the prompt’s challenge — you can’t help but feel like ChatGPT is in on the joke. It’s almost as if a personality starts to form — a little cheeky, willing to embarrass itself to make us laugh.
“As readers, we need to feel like the writer is paying attention to us, trying to connect. ChatGPT cannot build a real connection with its reader — it can only imitate one.”
“You silly humans,” the chatbot seems to be saying. “Using the greatest technology of our generation to create funny memes. But okay, I’ll play along.” These moments convey a sense of energy that makes it hard for me to believe I’m not chatting with a sentient being. Perhaps having a strong voice simply means writing in a way that makes you seem alive.
If this poem were written by a human, its voice probably wouldn’t have the same strength — it might feel cheesy and oddly reverential of the fast-food chain. Once we know ChatGPT generated the poem, however, its quality improves — we get the feeling the technology is unwittingly commenting on our world, illuminating the categories we use to understand it.
The McDonald’s sonnet isn’t interesting as a poem — it’s interesting as the output of an algorithm programmed with knowledge of our writing and our world. Perhaps AI-generated writing has the potential to be interesting or meaningful in contexts where the chatbot’s lack of awareness and intentionality matters; when the fact that the machine is not sentient amplifies the impact of its output; when the writing is, in some sense, about AI-generated writing.
But AI-generated writing about AI-generated writing is a narrow niche and there are limits to how long we’ll find it compelling.
Ethics Of Plagiarism
We tend to believe that good writing is original and thus advise writers to avoid clichés — phrases used so often we’ve come to see them as unoriginal and thoughtless. Clichés spring to mind too easily, careening along well-paved neural pathways, whereas original phrases must be pulled from the quicksand of our brains with significant effort.
We scorn clichés not because they’re bad descriptions — indeed, the reason they linger is probably because they’re pretty decent — but because their familiarity is off-putting, a sign of writerly laziness. Even when ChatGPT doesn’t use clichés, its writing still echoes of them; there’s usually the sense that there might be a fresher, more original way to say things.
Good writing, we believe, not only avoids phrases taken from the general consciousness, but also avoids language taken from individual writers unless acknowledged by quotation marks, and it credits others for their ideas with citations.
We expect students to read widely and build arguments that use others’ texts as support for their own. But to maintain so-called “academic integrity,” they must do this using fresh language and draw explicit distinctions between their own ideas and others’ — with the exception of information that is considered general knowledge. But what is general knowledge in a world where virtually any information is freely accessible online?
ChatGPT, in a sense, plagiarizes our voices as it parrots the writing it was trained on. It tends not to cite the specific sources it synthesizes to craft its phrases, and when it does, they are unreliable — the MLA Style Center website cautions writers to “vet” any secondary sources that appear in AI-generated text, as the programs have the occasional tendency to “hallucinate” false sources and provide information of questionable accuracy. Given the opacity of the AI’s sources, a student who tries to pass off AI-generated text as their own may be inadvertently performing a multi-dimensional transgression, plagiarizing an AI that itself is plagiarizing others.
The ethics of training AI on copyrighted materials are murky, too. Platforms like Reddit are pushing back against AI developers’ use of their content, and Sarah Silverman and other authors recently sued OpenAI for electronically ingesting illegally uploaded versions of their books from the internet to use as training data for ChatGPT. The Writers Guild of America, on strike since May, seeks to regulate the use of AI, both by preventing human-authored scripts from becoming AI training data and limiting AI tools in the writer’s room.
But if generative AI becomes as widely adopted as the Google search engine, will authors still want to opt out of contributing to it, or will serving as a model for the algorithm become a way to amplify their own literary influence, an honor akin to being ranked at the top of a Google search result? Should we work to protect the right to be excluded from AI training data, or the right to be included in it?
So far, universities mostly seem to categorize the unacknowledged use of AI as traditional plagiarism and continue to treat it as unacceptable, with students receiving Fs or even suspensions if caught. While software has been developed to detect AI-generated text, ChatGPT’s chameleonic potency makes the accuracy of these programs questionable.
“Writing is more than simply a sequence of words — it’s synonymous with thought. To steal others’ language is to take not just their words but also their ideas, the essence of who they are.”
Their relevance is debatable, too — what’s the value we’re trying to preserve by differentiating human writing from AI? Is it really plagiarism not to cite an AI-generated phrase? Is plagiarism still the crime we think it is?
Perhaps the ethics of using generative AI depend, again, on intention. An anonymous professor recently queried The New York Times Magazine’s “The Ethicist” advice column about whether it was ethical to use ChatGPT to generate administrative reports and proposals. Kwame Anthony Appiah’s response differentiated between writing that aspires to be original versus that which does not. He authorized the letter writer to use the tool with the rationale that “many administrative documents, though they may have signatories, aren’t thought of as original compositions,” pointing out that these texts often use templates as a starting point anyway.
But this distinction troubles me: How can we tell what kinds of writing are meant to be original and which are not? What exactly does originality mean? More practically, why do so many workplaces ask us to produce such unoriginal texts – what kind of value do they produce?
Writing As Thought
Historically, we have viewed plagiarism as an egregious offense. At most universities, students caught plagiarizing receive Fs or even suspensions, and outside academia, the act can result in book recalls and career-ruining embarrassment.
Why do we consider it so disgraceful? Because we believe writing is more than simply a sequence of words — it’s synonymous with thought. To steal others’ language is to take not just their words but also their ideas, the essence of who they are.
Our tendency to conflate writing with thought is why text-generating AI programs like ChatGPT give off the impression of sentience while image-generating programs do not, and why large language models are the primary targets of recent petitions to slow and regulate AI advancement. If ChatGPT can write coherently, our intuition tells us, surely it can think — and if it can think, how can we possibly maintain control over it?
I like to say that I’m not teaching my students how to write — I’m teaching them how to think; how to be observant; how to question the systems around them; how to interpret and build meaning; how to relate to others; how to understand and differentiate themselves; how to become agents of change. But ChatGPT, by producing competent writing with apparent thoughtlessness, threatens the idea that critical thinking is the core of good writing.
With its startling ability to regenerate responses by paraphrasing the same ideas in new words ad infinitum, it mocks the weight we put on paraphrasing to avoid plagiarism. We task students with summarizing texts in their own words to demonstrate their understanding of the material — but ChatGPT shows us that it’s possible to explain others’ ideas without understanding them; to build arguments from their content without metacognition.
Its revelation is reversing how we tend to think writing works: First, you come up with an idea. Second, you find the words to articulate it. But ChatGPT inverts this process. It begins with the words and builds its arguments and narratives based on language patterns, letting its ideas emerge from the text it uses to produce them.
When I write, I imagine reaching up to a higher plane to access my thoughts and assign words to them, yet the words I find are approximate and never capture the ideas as fully as they appear in my mind. This is why writing feels so hard to me: Its labor involves grasping for a perfect translation and always falling short. But ChatGPT reminds us that language is a lens, and our thoughts and perceptions are almost certainly shaped in some way by its conventions and metaphors. It shows us that writing influences our thoughts even as we use it to describe them.
We tend to view writing as hyper-personal, a conduit for our unique thoughts. But ChatGPT, through its own training, reminds us that we learn to write through imitation, the same way we learn to smile or eat or walk. Children grow up speaking with the accent of their peers, not their parents; in the same way, writing is a networked, communal act, inseparable from others’ writing.
We write in conversation with what we read, and good writing balances our own words with others’. We summarize their ideas, using them as springboards and support for our arguments. We take language from others, too, and not just as quotations: The English language is a colonial artifact that swallows up other languages. It’s full of stolen words and idioms and familiar, tired phrases — things we say because others say them.
“Perhaps the ineffable spark of good writing and the spark of a romantic connection are related — both involve a certain energy exchange, a sense of connection across individual minds, a balance of surprise and familiarity.”
As AI technology progresses, we will need to reconsider our conceptions of authorship and intellectual property. If you command unique text into existence by inputting a prompt into ChatGPT, have you authored that text? If ChatGPT edits or rewrites your work, is it still yours? If not, what kind of attribution would be valuable? Does the premise of intellectual property still hold water in a world with generative AI? Where’s the line between a “fair use” iteration of someone else’s text — a creative remake of a Shakespeare play, for instance — and more problematic appropriation?
Large language models challenge our understanding of originality and ask us to reexamine what value it adds to good writing. Is an original thought in the kernel of the idea or its phrasing? What makes a phrase original — the novelty of a word sequence, the context of its use or the readers’ perception of it? Are there any new ideas, or just new ways of saying them? Can AI generate original ideas by remixing old phrases? How original should good writing be, regardless of whether the author is human, AI or a combination?
Costs Of Optimization
It’s an incongruous time to be alive. We’re watching technology evolve in a more sophisticated way than we can understand or even track, and yet, our environmental, political and economic systems feel on the verge of collapse. We now live in a world where a free online program can generate convincing human-like prose more quickly than any human can read or even think.
Meanwhile, about one in 10 people worldwide — 773 million adults, mostly women— are illiterate. Almost a third of the world’s population, or 2.9 billion people, have not been on the internet in the past three months, if ever. Let’s not forget that optimization tools mostly impact the productivity of those with access to them.
Even if writing quality isn’t optimized, these tools save us time and effort — and the savings are significant. While immersed in the process of writing, you might experience a “flow” state in which the task of assigning words to thoughts becomes so absorbing that your sense of time passing falls away — but meaningful time gets lost when we spend time reflecting and writing instead of accumulating lived experiences. Life is short and writing time has a real cost: The hours I took to compose this piece could have been spent with family or friends, volunteering or working on any number of other projects or hobbies.
I’ve heard writer-parents say having a baby is equivalent to losing two books’ worth of time. And time is worth money: Full-time writing is a privilege that few can afford, with most writers stealing scraps of time between day jobs.
Optimizing the effort involved with writing is no small thing, either. The process requires an unparalleled level of focus, and for many it ushers in feelings of inadequacy and self-doubt. We take writing failures personally because we see writing as thought, so failing to express ourselves well in writing can sting more than other forms of expression. As a result, many end up terrified of the blank page, and AI becomes a tempting corrective.
Automation promises to accelerate time-consuming tasks and make us more productive. But when it comes to writing, do we need more productivity? If chatbots become widely adopted, who’s going to read all that text?
Anyone who’s published knows that readership is a rare gift. Reading is work — valuable work — but like writing, it requires exertion and takes time away from other tasks.Many of us already feel saturated with content; we consume so much information through screens that our daily attention spans feel fragile and limited. There’s a certain respect we hold for writers who are careful not to publish too much, who honor their readers enough to self-censor and share only what’s really worth our attention.
And what will become of our own writing after reading so much AI-authored prose? Will we begin to write more like ChatGPT in a linguistic mise en abyme? Will we lose the sense that reading and writing offer a solution to loneliness, the chance to connect deeply with another human’s inner world, given the growing uncertainty about whether a human is even present behind a given text?
Perhaps something meaningful is lost when we use AI to reduce the time and effort spent writing. Writing well takes practice, and I see the most significant progression in students who spend the most time writing, reworking draft after draft. To “essay” is to try — perhaps good writing is about trying, about process as much as outcome.
If AI becomes commonplace, perhaps we will wind up most admiring those writers who proclaim to do the hard work of generating their own prose from scratch, slowly and painfully. Like organic produce or designer handbags, perhaps human-authored text will someday carry labels certifying its authenticity. Or maybe our preference for the real over the artificial will simply fade as differentiating between the two becomes increasingly difficult.
But even if a reader can’t be sure whether a text had AI support, the writer knows, and producing unassisted writing can feel deeply gratifying. We run marathons and climb mountains for the sake of it; because they’re hard. Maybe the parts of writing that feel so burdensome — the effort to think deeply, to sit still with our thoughts, to articulate them and revise them until they say exactly what we want, until we figure out what we’re trying to say at all — are the parts that we value when we praise good writing.
Perhaps the time spent writing matters as much as having written; there is a vague sense of being, in the moment of writing, the most authentic version of yourself.
Writing To Differentiate Ourselves
What makes good writing in a world with generative AI? Perhaps writing classes of the future will lean into the subtle ways in which human writing surpasses AI-generated writing and challenge students to write better than the machine.
Perhaps they will teach students to be AI curators and remixers, teaching the prompt engineering skills they need to leverage the technology most effectively, in preparation for the kind of sparkless, functional writing they will produce post-graduation — contracts, reports, meeting minutes, instructional manuals.
Perhaps the college essay will be retired in favor of other assignments that demonstrate knowledge, critical thinking and argumentation skills — speeches, hands-on activities or multimedia creations. It seems likely we will continue to teach students to read widely and study textual patterns and conventions closely — the same way we train AI to write.
But perhaps ChatGPT also shows us that at a certain point, reading has diminishing returns. Maybe we also need to be trained on other kinds of data in order to write well, data that comes from being alive in the world over time, from accumulating enough experience to differentiate our own voice from others.
Writing courses are different from other disciplines — they’re not so much about transferring knowledge or conveying conceptual frameworks. Instead, they aim to create a space in which students can practice differentiating themselves.
Teaching writing usually involves one-on-one meetings, a structure that allows me to build relationships with students. Through reading their writing and talking about their ideas, I watch them begin to fill in the templates of their personalities and experiment with specificity, trying out various attitudes, disciplines, hobbies, relationships, styles and habits, and in the process, becoming themselves. They hone their craft not only by learning about writing conventions but also by learning about who they are and what they think, by figuring out how their perspectives align and differ from others’.
Generative AI complicates this mission, but it doesn’t terminate it. The division between the words and ideas that belong to us versus others has always been more ambiguous than we’d like to think, and ChatGPT blurs that line further. Even if we use AI to make writing feel easier, we still need to do the hard, lifelong work of becoming ourselves.
To write well, you need the specificity of perspective that comes from communicating critically with others over an extended time. AI might make writing faster, but figuring out who we are in relation to others cannot be accelerated.
We may see writing as equal to thought, but it is also synonymous with power. Allowing AI to write for us gives away our power and the opportunity to assert control over the way we represent ourselves to the world.
As we continue to debate whether using AI violates university policies on academic integrity, I am reminded that the word “integrity” means not just honesty and moral uprightness, but also wholeness, an integration of parts. Education is about recognizing the limits of our own subjective impressions, inhabiting others’ perspectives, and aligning them with our own. Perhaps writing with integrity means integrating our selves with others through the act of writing to form a coherent whole.
The tension between the individual and the collective, between novelty and familiarity, drives the arc of our lives. We are conceived from the text of others’ DNA and emerge with our own combinations. We grow up learning to imitate those who raise us, then rebel from them as we battle to find ourselves amid the influences of society. We use writing to differentiate ourselves, to respond to others, weaving their words with our own, synthesizing their ideas, adding new ones and exploring where we align and diverge.
Beyond mirroring elements of our voices, maybe AI also mirrors the tensions we feel between ourselves and others. Perhaps large language models, if we interact with them critically, will open new frames through which to explore the balance between the ways we conform and the ways we break free, adding depth to the mission of self-discovery that defines our lives.
Michelle, Thank you for your comment, which has now been reviewed by the Editor and has been posted on the relevant site discussion area.
— Original Message —
Yet another group of people gathering together to make a plan for ‘US’. I have encountered so much inability by those that represent the mentally ill to converse with us. The problem clearly is fear.
A programme was run by the Centre for Women Studies in Trinity in 1996 concerned with the re-integration of women and depression back into society. I was one of the first 15. It carried on for another couple of years but the NRB found it to costly to implement. Without it I could never have gone to Trinity College Dublin – the syllabus provided me with the necessary coping mechanisms but alas the inability of academia to meet the needs of those with disability particularly mental illness, and their inability to correspond and to consistently ignore your emails forces me to write and ask people to take on board the systems and representative organisations that excludes people.
We need an inclusive society. Research by sociologists re. mental health should involve people who have had mental health problems on an equal footing. The question needs to be asked who decides what is to be researched; who funds it; what are the motives? The concept of the research making up the questions to my mind skews it. I of course may be wrong……. Everyone has talents – a Platonic regimented approach to education does not invoke the best in people and is blatantly not suitable to young people who could be described as having say a sensitive nature. I wrote to compliment an academic on a paper regarding rights for the like of me and many more and I have received not even an acknowledgement based on principle and courtesy – it has been to no avail. This is ignorance and from the legal profession. I even raised it at a Fine Gael meeting on Crime.
Charles Murray referred to the creation of the Underclass in America in the 1960’s – we are doing the same here. Mental illness is about stigma, shame, labels, limited if any insurance required, Church hostility when marriage goes wrong. It is about an adversarial system that is penal to the person who is part of the revolving door of psychiatric. People must wake up. We are losing too many men to suicide.
A child of 13 who had been raped at 10 is one of the latest to take her life. No one listens or cares as long as the presentation of the document for the meeting is acceptable. We are too far removed from reality. Shame – it is absolutely a disgrace about the woman arrested and held for 10 hours re. the hoax calls. We also must think about John Carthy.
In England they speak about Mental Health Survivors – we need to be talking Survivors here. In order to survive you need rehabilitation like the Trinity Horizon programme. One final point. Why is alcoholism and drug addiction (illegal) not included with mental illness. A recent study shows that women enter mainly as depressives while men enter hospitals as alcoholics. Of course men are likely to have the large salaries etc. The link is very close between depression and alcohol. What skews this research? It is coping strategies that people ought to be looking at. Michelle
Quote: Goethe:
‘Treat people as if they are what they ought to be and YOU WILL HELP THEM BECOME WHAT THEY ARE CAPABLE OF BECOMING’
Thank you for your comment, which has now been reviewed by the Editor and has been posted on the relevant site discussion area.
— Original Message —
A Judge recently referred to Divorce being an ‘Armageddon for Children’.
To hear that approx. 1,000 children in Dublin are presently homeless, is an absolute disgrace. Something must be done and soon.
In no way can the possibility be sanctioned by the people of the Island of Ireland that our present Government can facilitate the removal of rent allowance and ensure that more children are to be found homeless.
It is time for people to think. Children are to be cherished. Parents must be empowered to provide for their children. Someone needs to start working in Government offices about the potential workforce.
Gandhi: You have got to be change you want to see.
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