Giving Voice to Generative AI Refusal in Rhetoric and Writing Studies

by Maggie Fernandes and Megan McIntyre

Episode 4: An Interview with Dr. Michael Black

Listen to Episode 4

For this episode of Everyone's Writing with AI (Except Me!), we spoke with Dr. Michael Black, who is an Associate Professor of English at the University of Massachusetts Lowell. Dr. Black specializes in studying the intersections between computing and writing. According to the publisher's summary, his 2022 book, Transparent Designs: Personal Computing and the Politics of User-Friendliness documented the rhetorical history of usability and highlighted "how the concept of usability has been leveraged historically to smooth over conflicts between the rhetoric of computing and its material experience." Prior to joining the faculty at UMass Lowell, Dr. Black served as an Associate Director for the Institute for Computing in Humanities, Art, and Social Science at the University of Illinois at Urbana–Champaign. We wanted to talk to Dr. Black because his book invites readers to think about how ease of access and user-friendliness can obscure (sometimes intentionally) the ways that particular design choices or features undercut users' agency. As Dr. Black argued in the Coda to Transparent Designs, "software designers often structure our relationship to software to maximize their momentum and minimize our agency so that we experience designers' constant interventions in our lives as inevitable and unavoidable" (p. 222). Additionally, we wanted to hear Dr. Black's thoughts on the connections between his work on the development of the field of usability studies and his understanding of the current generative AI moment.

Our conversation with Dr. Black made us think more concretely about a few dimensions of generative AI in writing studies:

• The generative AI moment might be analogous to other tech hype cycles, including the rise and fall of MOOCs (Lederman, 2013), the emergence of digital humanities, and the founding of Uber and Lyft. None of these analogies are perfect, of course, but each offers potentially useful ways of thinking about the role of tech hype in our current generative AI moment.
• Generative AI raises a whole host of labor questions (Hao & Seetharaman, 2023). For a discipline that has long been invested in conversations about labor—especially contingent and graduate student labor—in the discipline and in higher education, it feels particularly important that we grapple with the ways that genAI is both adding labor to already overworked teachers and reshaping our relationships with the fruits of our labor.
• Prompt engineering effectively requires a high level of writing skill, experience, and confidence, meaning we should continue to offer opportunities for learning and practice to students as we have always done.
• As Dr. Black astutely points out, generative AI tools emphasize product above all else. For a discipline whose entire foundation is built on teaching writing as a process, this fundamental dissonance seems important to talk about.