This session argues that in AI-mediated composition classrooms, reading must be reconstituted as a visible, collaborative, and rhetorically generative practice in order to sustain students’ interpretive agency. It builds on scholarship in rhetoric and composition that emphasizes the interdependence of reading and writing, including work by Howard Tinburg, Ellen Carillo, the MLA Institutes for Reading and Writing, and the CCCC Position Statement on the Role of Reading in College Writing Classrooms. It also draws on research in critical algorithm studies, such as Safiya Noble’s work, and on transnational and decolonial pedagogies.

The rationale for this session emerges from a growing pedagogical concern and engages the MLA 2027 presidential theme, Emancipatory Narratives, by examining how reading and writing can sustain interpretive agency in AI-mediated classrooms. As the theme emphasizes, emancipatory narratives are grounded in both description and action, requiring not only articulation of lived experience but also the capacity to respond, resist, and reimagine. In contemporary classrooms shaped by AI, this dual commitment is increasingly at risk, as algorithmically generated summaries and interpretations can flatten complexity and displace students’ interpretive labor. Across the panel, reading practices, whether through counter-storytelling, comparative analysis of AI-generated texts, or collaborative annotation platforms, function as forms of “antagonistic cooperation,” where students learn to read both with and against dominant algorithmic narratives. In this sense, the session takes seriously the theme’s call to become “careful listeners” who push interpretation toward greater complexity and responsibility. By centering emancipatory and counter-narratives in reading and writing, the session demonstrates how writing classrooms can cultivate the kind of rhetorical agency described in the presidential theme: one that is conscious, responsive, and willing to take intellectual risks.

The session is organized around two complementary approaches to sustaining interpretive agency in AI-mediated classrooms. The first, a platform-based approach, examines how digital annotation tools such as Perusall and Hypothesis can structure reading and writing as reciprocal practices, moving from reading to write and writing to read exercises. The second, a content-based approach, focuses on how counter-storytelling and comparative analysis of AI-generated texts engage students in critical reading practices that foreground bias, power, and representation.

Within the first, platform-based approach, Eman Al-Drous, Assistant Professor of Rhetoric and Composition at the University of Tampa, presents “All Write, No Read? Reclaiming Reading in the Age of AI through Collaborative Annotation,” which positions Perusall as a framework for reading-to-writing practices. Through structured annotation assignments, students engage texts, respond to peers, and track interpretation, making reading visible and accountable as the foundation for writing. Drawing on WPA assessment work, the presentation shows how annotation anchors writing in shared textual engagement and counters surface-level or AI-generated responses.

Complementing this model, Rusty Michalak, Director of Library and Archives at Goldey-Beacom College, presents “Annotating Against the Algorithm: Hypothesis, Critical Reading, and Rhetorical Agency at an Emerging Hispanic-Serving Institution,” which conceptualizes Hypothesis as enabling writing-to-reading practices. Students compose through annotation to question algorithmic interpretations, negotiate meaning, and assert interpretive authority. Here, writing produces reading, foregrounding interpretation as a contested, dialogic process shaped by power and perspective. This approach positions annotation as rhetorical production and a critical response to algorithmic mediation.

Within the second, content-based approach, the focus shifts from platform to practice, with presentations that explore how counter-storytelling and comparative engagement with AI-generated texts invite students to read both with and against dominant narratives.

Session presider Iswari Pandey, Professor of English and Faculty Director of First-Year Writing at California State University, presents “Reading Against the Machine: Fighting Algorithmic Bias in the Writing Classroom,” which advances the panel’s content-based approach through counter-storytelling. By assigning emancipatory/ counter-storytelling narratives, students interrogate dominant and algorithmically shaped discourses, developing rhetorical agency. Drawing on transnational and decolonial pedagogy, the presentation shows how attention to voice and identity supports critical reading practices that resist bias and inform more authentic writing.

Susmita Davi Trisha, a PhD student in Rhetoric and Writing at the University of Nevada, presents “If Students Don’t Read, They Can’t Write: Re-centering Reading in Composition Classroom in the Age of AI,” which demonstrates assignments that ask students to compare assigned texts with AI-generated summaries, positioning reading as an active process through which they identify omissions, question simplifications, and reconstruct meaning in their own writing.

The panel assembles interdisciplinary participants with diverse professional roles and career stages, representing a range of institutional contexts, including public and state universities, private liberal arts colleges, and teaching-focused institutions. The session is structured around four presentations of approximately 10–12 minutes each, followed by 15–20 minutes of open discussion.