AAAL 2027: Invited Colloquium
Convened by Jennifer-Sano Franchini, Maggie Fernandes, & Megan Mclntyre
Refusing Generative AI and the Fight for Academic, Creative, Linguistic, and Collective Freedom
AAAL Strand: Language and Technology (TEC)
Conveners:
Jennifer-Sano Franchini, West Virginia University
jennifer.sanofranchini@mail.wvu.edu
Maggie Fernandes, University of Arkansas
mbfern@uark.edu
Megan McIntyre, University of Arkansas
mm250@uark.edu
Colloquium Abstract
Generative AI represents a key concern and ongoing challenge for literacy and language teachers and practitioners, particularly given the increasing evidence of its contributions to labor exploitation, cognitive and mental health harms, environmental degradation, and linguistic, stylistic, and representational homogenization. This colloquium brings together scholars and teachers from rhetoric and writing studies and digital literacies to discuss generative AI refusal as a multifaceted response to the imposition of generative AI on language and literacy classrooms and practices. This colloquium will open with a brief introduction by the conveners, followed by four 20-minute presentations. The colloquium will end with an open discussion among speakers and the audience.
Investment by Refusal: Negotiating Identity, Capital, and Ideology in Agentive GenAI Practices
Ron Darvin, The University of British Columbia
ron.darvin@ubc.ca
Drawing on Darvin and Norton's (2015) model of investment, this paper takes up refusal as a productive lens to examine how language learners can invest in agentive GenAI practices that resist the full delegation of meaning-making to technology while asserting their own identities, intentions, and resources. Rather than positioning refusal as the act of opting out, this paper argues that it constitutes a spectrum of agentive practices through which learners can interrogate the power relations embedded in human-AI interactions: recognizing how platform designs, algorithmic logics, and training data reproduce dominant ideologies of language and knowledge, and how unequal access to devices and platform features circumscribes the extent to which learners can exercise meaningful agency. By foregrounding the entanglements of identity, capital, and ideology in human-AI interaction, refusal enables learners to invest in critical digital literacies that affirm learner agency as a form of freedom: the freedom to resist being positioned by algorithmic logics, to claim ownership over one's own meaning-making, and to participate in language learning in more equitable and self-determined ways.
Reference:
Darvin, R., & Norton, B. (2015). Identity and a model of investment in applied linguistics. Annual Review of Applied Linguistics, 35, 36–56.
Love in a Time of Data Centers: Toward Techno-Affects of Refusal
Wilfredo Flores, University of North Carolina at Charlott
wflores1@charlotte.edu
The speaker uses the affective turmoil of forced GenAI adoption as a productive springboard for forging new ethics of technology use via three attunements grounded in the Indigenous practice of refusal in the face of settler colonialism. The speaker primes the data center expansionism of Big Tech as site of generating affects that engender anticolonial attitudes and uses of technology set to the pace of corporeal, sovereign, and glitchy attunements to technology. The speaker concludes by advancing "rhetorical flops" as a practice of shutting down pro-GenAI discourses and for setting an agenda wherein likeminded interlocutors might work together to create a better technological future together.
Resisting Gen AI’s Linguistic Enslavement and Neocolonialism through Scientific Socialism
Alfred Owusu-Ansah, University of Denver
Alfred.Owusu-Ansah@du.edu
While many have touted Gen AI as a linguistic tool whose application could have liberating results (Joseph & Mani, 2025; Kennedy & Gupta, 2025), there are those who have rightfully cautioned that Gen AI is more likely to be shackles with which humans may be linguistically imprisoned (Nhemachena, 2022). In addition to its exploitative nature, these scholars point out that the definitive power granted to Gen AI is actively working at limiting what can and cannot be done with language. The goal of this talk is to suggest that scientific socialism as propounded by thinker, freedom fighter, and the father of political Pan-Africanism, Kwame Nkrumah is a potent tool for resisting linguistic enslavement and linguistic neocolonialism. To make this argument, the talk will trace the material, affective and historical connections between the application of Gen AI as a writing technology and other literacy technologies that have served the colonialist goals of the modern empire. The talk forwards that Gen AI refusal should be grounded in egalitarian practices that reinforce the value of all humans, suggesting how refusal for the post-colony may present itself in varied forms. The talk concludes with an outline of what these forms of refusal may look like in our reimagination of language policy within this neocolonial era.
References:
Joseph, L., & Mani, B.P. (2025). AI unleashed: will it empower us and promote social independence, or enslave us? AI & Soc 40, 2343–2344. https://doi.org/10.1007/s00146-02402092-x
Kennedy, K., & Gupta, A. (2025). AI & Data Competencies: Scaffolding holistic AI literacy in Higher Education. Thresholds in Education 48(2) 182–201.
Nhemachena, A. (2022). African sovereignty at stake: technologies of enslavement and destruction in twenty-first century Africa. In A. Nhemachena, O. Mtapuri & Mawere (eds.)
Sovereignty Becoming Pulvereignty: Unpacking the Dark Side of Slave 4.0 within Industry 4.0 in Twenty-First Century Africa. Langaa.
Refusal as Liberatory Praxis
Jennifer-Sano Franchini, West Virginia University
jennifer.sano-franchini@mail.wvu.edu
Maggie Fernandes, University of Arkansas
Megan McIntyre, University of Arkansas
mm250@uark.edu
Since the publication of their website on Refusing Generative AI in Writing Studies, the speakers have noted how refusal, as a concept and a term, engenders a wide range of responses from relief to suspicion to ambivalence to outright hostility. In this presentation, argue for the value and urgency of refusal, as a term and as a set of practices, for responding to the imposition of generative AI across seemingly all spheres of life. The speakers analyze how the language of refusal has been taken up, forwarded, and critiqued in the context of conversations about generative AI. As they do so, they consider: What is refusal good for? What does the language of refusal do? What is being refused? And what are those who refuse choosing instead? For example, the speakers discuss how refusing generative AI is a way of refusing the scaled-up automation of white language supremacy (Kynard, 2023), and how responses to generative AI refusal frequently echo past and ongoing hostilities toward antiracist projects. Ultimately, this talk argues that a hopeful, refusal-oriented future involves recognizing the value of registering disgust, anger, and disagreement in the face of AI Empire (Tacheva and Ramasubramanian, 2023) and worsening attacks on academic, creative, intellectual, and collective freedom. The speakers conclude by discussing how refusal opens up new, more hopeful futures, following scholars like Ruha Benjamin (2024), Yanira Rodríguez (2019), and Sara Ahmed (2023) rooted in care, consent, and collective liberation.
References:
Ahmed, Sara. (2023). The Feminist Killjoy Handbook: The Radical Potential of Getting in the Way. Hachette UK.
Benjamin, Ruha. (2024). Imagination: A Manifesto. W.W. Norton & Company.
Kynard, Carmen. (2023). When robots come home to roost: The differing fates of Black language, hyper-standardization, and white robotic school writing (yes, ChatGPT and his AI cousins). Education, Liberation & Black Radical Traditions for the 21st Century. http://carmenkynard.org/when-robots-come-home-to-roost/
Rodríguez, Yanira. (2019). Pedagogies of refusal: What it means to (un)teach a student like me. Radical Teacher, 115, pp. 6–12.
Tacheva, Jasmina & Ramasubramanian, Srividya. (2023). AI empire: Unraveling the interlocking systems of oppression in generative AI's global order. Big Data & Society, 10(2), pp. 1–13.