Monthly Readings

Each month, we will focus on one of the three parts of AI and Writing. For each session, we recommend four resources that relate directly to what Dobrin discusses in each section. (Explore the 3-part schedule here.) Those are meant to supplement your reading of his book. Feel free to engage with these sources as much or as little as your time and energy allows.

Guiding Discussion Questions

As you are reading Dobrin’s book AI and Writing, we ask you to keep these three questions in mind, which we would like to explore throughout the book club:

• Considering the diverse social contexts (e.g., socio-economic background, cultural and linguistic diversity, geographical location, disability and accessibility, digital literacy) of students and faculty, how can we ensure equitable access and fair use of generative AI technologies in higher education?
• How do we address the potential biases in AI outputs and their impact on marginalized communities?
• If we separate our conversation about "AI ethics" from the teaching of writing with AI, are we creating a division that can encourage a kind of intellectualization of ethics that will exist separately from the actual practice of AI in writing education? In his book, Dobrin doesn’t explicitly discuss AI bias until the last part (chapter 8).

NOTE: Part of these questions were constructed with the assistance of ChatGPT 4, James Wright, and Hannah Mueller. The output created by ChatGPT 4 has been edited and revised by Dr. Isabell May.

Additional Resources

We have curated a list of additional resources about GenAI for you. Feel free to browse around these at any time. We have provided a short summary of each resource for you and have organized them by genre. We hope this might help you in choosing the resources that are right for you.

• Article: Alexander, J. (2023). Students’ Right to Write. Inside HigherEd. – “Writing therefore becomes one of the most powerful ways through which we not only connect but continue to develop a capacity to know the self in relation to others.”
• Article: Hayes Jacobs, H., & Fisher, M. (2023). Prompt Literacy: A Key for AI Based Learning. ASCD, 70(9). – introduces a model for building prompt literacy: CAST (Criteria, Audience, Specifications, Testing).
• Blog: Bali, M. (2023). What I Mean When I Say Critical AI Literacy. –explores the term “critical AI literacy” as a shared goal for students and instructors, with links to related resources.
• Blog: Litt, G. (2023). ChatGPT as muse, not oracle. – offers insight to this question: what if we used AI to help ourselves be more creative, to ask us thought-provoking questions?
• Blog: Mina, L. (2023). Generative AI and Teaching College Writing. – a Two-Week Unit for English MA Students. (requires subscription).
• Blog: Myers, A. (2023). AI-Detectors Biased Against Non-Native English Writers. – summarizes a research study by Stanford researches on the bias of AI detectors. Includes links to the full study.
• Blog & Infographic: Eaton, S.E. (2023). 6 Tenets of Postplagiarism: Writing in the Age of Artificial Intelligence. – Eaton summarizes six tenets of postplagiarism, a term that she first explored in her book Plagiarism in Higher Education: Tackling Tough Topics in Academic Integrity (2021). Includes translations in to French and Spanish.
• Data: PEW (n.d.). Research Topic: Artificial Intelligence. – links to studies conducted by the PEW Research Center on a variety of AI-related topics. Worth exploring!
• Google Document: Rutgers AI Council. Working Document. – “This document offers a provisional set of resources to help instructors make informed decisions and equip themselves for productive discussions as they prepare for a new semester.”
• Infographic: M, & Eason, R. (graphics/design). How smart is ChatGPT? Visual Capitalist – visual overview of how well ChatGPT has performed on a variety o standardized tests used across academic disciplines and fields.
• Press Release: Coley, M. (2023, August). Guidance on AI Detection and Why We’re Disabling Turnitin’s AI Detector. – from Vanderbilt University, a statement on their decision not to use AI detection software, with resources and citations.
• Resource Page: Mills, A. (curator) (2022. Last Updated November 18, 2023.). AI Text Generators and Teaching Writing: Starting Points for Inquiry. WAC Clearinghouse. – a treasure trove that consists of links to relevant articles, blog posts, videos, and other resources as well as to opportunities to engage with others on GenAI related content.
• Working Paper: MLA-CCCC Joint Task Force on Writing and AI Working Paper: Overview of the Issues, Statement of Principles, and Recommendations. (2023). – members of the Modern Language Association (MLA) and the Conference of College Composition & Communication (CCCC) have developed this working paper.

February 23: Part 1