CFP: Bad Ideas about AI and Writing

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Bad Ideas about AI and Writing: Toward Generative Practices
for Teaching, Learning, and Communication

Edited by:

Christopher Basgier

Anna Mills

Mandy Olejnik

Miranda Rodak

Shyam Sharma

First released in 2017, Cheryl E. Ball and Drew M. Loewe’s collection Bad Ideas About Writing sought to overturn persistent myths about writing that circulate publicly and lead to problematic curriculum, pedagogy, and learning. As Ball and Loewe put it, “These publics deserve clearly articulated and well-researched arguments about what is not working, what must die, and what is blocking progress in current understandings of writing” (p. 1). Today, public and institutional conversations about writing are increasingly inflected by generative artificial intelligence (AI) applications such as ChatGPT. Unfortunately, such conversations often include bad ideas about AI, by which we mean ideas that are patently false, ideas with logical leaps that do not hold up under scrutiny, or ideas that are both accurate and logical but lack nuance or include implications that are unethical or downright harmful. Some such bad ideas may exist because of, or exacerbate, existing bad ideas about writing; others may add to the repertoire of bad ideas about writing. Therefore, this collection seeks to reframe bad ideas about AI and writing to provide more generative (that is, evidence-based, logical, constructive, ethical, and compassionate) practices for teaching and learning writing, with or without AI, now and in the future. In so doing, this collection also strives to base its discussions on established and emerging principles and theories of writing pedagogy.

We anticipate that the collection will be organized around the effects of myths about AI and writing on different groups of stakeholders. Sample ideas may include:

  • Bad ideas that impact students

    • AI “writes well” and so can be used to produce texts across all disciplines

    • Writing assignments are easy with generative AI

    • AI is always a valid, unbiased source of truth

    • AI generates original ideas like humans

    • Students naturally want to cheat with AI

    • All AI use is a form of plagiarism

    • AI generates valid citations

    • Any AI use detracts from student learning and voice

  • Bad ideas that impact teachers

    • Instructors should never permit AI in their courses

    • The only way to prepare students for the future is for all instructors to use AI in their classes

    • AI use inevitably works against teaching critical thinking

    • It is okay to feed student work into AI for grading assistance

    • Instructors cannot hold students accountable for AI use

    • AI policies are more important than pedagogy to prevent AI abuse

    • AI levels the playing field for students who haven’t mastered Standardized Edited American English

    • AI means students have to think and struggle less

  • Bad ideas that impact administrators

    • Institutions must either ban or embrace AI

    • AI is a pedagogical or research issue, so it will radically reduce administrative roles

    • AI detectors are valid sources of evidence in plagiarism accusations

    • AI-driven cost savings will not conflict with institutional missions

    • AI will replace universities

  • Bad ideas that impact writing programs (including first-year composition [FYC], writing across the curriculum [WAC], and writing centers)

    • AI can replace writing instruction

    • AI tutors are as good as peer tutors

    • AI negates the need for FYC, WAC, etc.

  • Bad ideas that impact organizations, communities, and publics

    • AI is the great equalizer

    • AI reads, understands, and writes texts as a human would

    • AI will replace all human experts

    • AI is capable of understanding and using all human languages

    • AI is neutral in terms of cultural difference and political bias

    • AI will help nonnative English speakers overcome their language challenges

    • AI is inherently good, bad, or neutral

    • Humans cannot identify AI misuse; only machines can

    • It is hard to distinguish AI text from human writing, so we might as well give up

We invite 250-word proposals on these topics or others. Proposals should 1) name the bad idea about AI pertaining to writing that will be the focus of the chapter, 2) explain how this idea impacts one of the above groups, the work they do, or an educational mission relevant to them, and 3) reframe the bad idea with a focus on articulating a generative idea or practice that can be used in teaching, learning, communication, or the work of writing education more broadly. These “better ideas” about AI and writing should be situated in principles and practices established in rhetoric, composition, writing, or literacy research. Although many of the suggested topics above impact many stakeholders, we ask that you focus predominantly on one group of stakeholders in your proposal. Please note that we anticipate final chapters to be brief, in the 1000- to 2000-word range (excluding references), so craft your proposals accordingly.

Although the primary audience of Bad Ideas About AI and Writing will be teachers, scholars, and administrators in rhetoric, composition, and writing studies, we do anticipate a broader readership. Therefore, proposals (and eventual chapters) should be written in a style that will be accessible to readers from a range of educational backgrounds, social positions, and nationalities.

Please submit your proposals to badideasbook by March 29, 2024. In cases where proposals overlap significantly, we may ask contributors to collaborate on a chapter.

Tentative Timeline:

March 29, 2024 Proposals due

May 10, 2024 Editors’ decisions provided & invitations sent

July 12, 2024 First chapter drafts due

September 15, 2024 Feedback on chapters provided

November 15, 2024 Revisions due

December 31, 2024 Entire manuscript sent out for review