Preston Taylor Stone, Ph.D.

Instrumentalizing ChatGPT for Academic Identity Formation in First-Year Composition

Inspired by my years of experience as an instructor of English composition, this IRB-approved study hypothesizes a measurable increase to students’ writing self-efficacy, self-concept, and participation in academic community when supported by integrating ChatGPT into the first-year writing classroom.

First proposed for medical students to improve their professional identity formation (PIF), I predict that ChatGPT-as-a-life-coach (ChatGPT-LC) will enhance writing skills by providing opportunity for metacognition even as it does not de-center students’ agency as their form their own academic identities. I use a self-regulated learning (SRL) model and insights from early adopters of generative AI in writing pedagogy to position ChatGPT-LC as a classroom aid. An empirical study based on this research is in-progress.

Queer Refractions: Queer Storytelling in the Age of AI

Given AI-generated texts are often marked by a sense of the uncanny, familiar yet eerily strange, this uncanniness queers conventional forms of communication by introducing ambiguity and instability into otherwise structured language forms. Speculative AI is at the nexus of understanding a new age of writing, storytelling, and constructions of (anti)normativity. My second monograph project is tentatively titled Queer Refractions.

I use tools like Sudowrite and Squibbler, which both claim to generate full novels in users’ own style in mere seconds, to critically examine the potential and limitations of generative AI to produce queer/non-normative narratives. By generating and then close-reading corpora of creative writing focused on LGBTQ+ themes, I interrogate how these AI-generated texts ultimately fail to reflect the complexity of queer storytelling. Instead, I argue, these present what I call a refraction of queerness, rather than a reflection of it. In line with emerging subfields of queer AI and critical AI, the book exposes the heteronormative constraints embedded in these tools.

I end the monograph with potential fixes for this issue. One such solution I anticipate including based on my background in critical Indigenous studies will be the incorporation of Indigenous ways of knowing into the design of generative AI. By integrating Indigenous epistemologies – which is to say prioritizing relationality, multiplicity, and storytelling as acts of communal memory – I suggest that generative AI could move beyond linear, normative narratives toward more expansive, inclusive approaches to creativity. This reimagined framework not only challenges the dominant cultural assumptions embedded within current AI systems but also opens up possibilities for AI tools to co-create narratives that honor the fluidity and intersectionality of queer identities. The monograph thus advocates for a broader, more ethical engagement with AI in creative writing, urging developers, writers, and publishers to consider how marginalized perspectives can transform the future of emerging technologies.