Emory Writing Program Basic Generative AI Use Policy Statement

General Policy 

In the Emory Writing Program, we teach students that the composition of writing and multimodal works is, in and of itself, an act of thinking and learning. Some argue that these practices of thinking and learning can be automated through the use of generative artificial intelligence (genAI). However, in the Writing Program, we find that this automation inhibits student development of the skills and conceptual knowledge that underlies excellence in our field. Therefore, in courses in the Writing Program, students may not use genAI to complete coursework. 

In articulating a general refusal of genAI, we are referring to commercialized large-language models that draw from millions of illegally accessed copyrighted materials to turn user prompts into predictively generated text, images, citations, and any other content as part of a profit-seeking business model associated with “Big Tech” in the service of wealth concentration. These platforms might include, but are not limited to: ChatGPT, Gemini, Microsoft Co-Pilot, Claude, Grammarly, Dall-E, AI tools in Adobe and Canva, and many many other commercial applications.   

The overarching Writing Program policy is that students may not use genAI to complete coursework; there are, however, a few exceptions. Students may be asked to use genAI by their instructor for an assignment or activity in which the generated media is itself an object of analysis, or its use is the subject of critical reflection. Students may also be invited to use genAI by their instructor for a task that is explicitly stated to be part of a specific Student Learning Outcome or assignment. All syllabi in the Emory Writing Program include a syllabus statement about instructor-specific policy and assignments. 

Students who object to the use of genAI in assignments that fall under exceptional circumstances will always have the right to refuse to use this software both in their composition and in their instructors’ assessment of their coursework in ENGRD courses. Instructors will not penalize a student for refusing genAI software. In alignment with student requests, students can be confident that instructors will not upload their coursework into genAI software without their consent, nor use genAI to evaluate their coursework without a transparent explanation to the students in the course about how and why the instructor has chosen to do so. 

Our support for student autonomy in refusing genAI is key to educating students in the field of rhetoric and composition. For example, the Conference on College Composition and Communication resolved in 2026 to “affirm the rights of students and teachers to refuse to sign up for, prompt, or otherwise use generative AI in the writing classroom.” 

Leaders in the field of rhetoric and composition argue that the uncritical implementation of genAI in the writing classroom threatens academic freedom, undermines the value of academic labor, homogenizes student expression through adherence to white language supremacy, and promotes corporate profit over student learning (CCCCs). In contrast, student and instructor refusal to use genAI technologies creates opportunities for learning and development in this field.  

Refusal is one way to assert one’s sovereignty within oppressive conditions and to imagine new possibilities and futures for responding to the problems posed by generative AI in our discipline and beyond… Indeed, the refusal of generative AI enables us to take a step back from the compulsory opt-in culture that has become ubiquitous through Big Tech, and it (re)opens possible rethinking around how we interact with and engage corporate proprietary technologies that involve profiting from student and teacher data and intellectual labor, including plagiarism detection software, learning management systems, and telecommunication technologies. 

We support students’ choice to refuse genAI because we support their access to an education in rhetoric and composition in which students can 

• Trust that their instructors are not using AI-detection software that is prone to falsely label student-written work as genAI (Elkhatat et al.) 
• Practice data privacy and autonomy 
• Complete their coursework without having to revise AI-generated output that is, under current corporate models, inevitably inaccurate (Kalai et al.) 
• Train to think creatively (Habib et al) and think critically (Vendrell and Johnston) 
• Develop confidence in their expression of their own thoughts (Osborne and Bailey) 
• Practice accountability for the ethical implications of their choices (Kobis et al.) 
• Identify sources of information and assess whether those sources are reliable, representative, and just (Byrd) 
• Practice research as a process of in-depth learning through inquiry, reasoning, and argumentation (Stadler et al) 
• Analyze information for its meaning, rather than the information “sound[ing] right” (Kidd and Birhane) 
• Stand in solidarity with exploited workers, both with the university labor force (Cutler) and with those who filter and compose “genAI” output abroad (Koebler, Perrigo) 
• Help safeguard environmental resources (Kshetri), including those of our neighboring communities (Skibell) 
• Engage critically with dominant marketing narratives about the inevitable omnipresence of generative AI technology in the workforce and day-to-day life

In summer 2026, the UC Berkeley School of Law developed and published publicly a thorough list of compositional activities that represent students should not use genAI platforms to complete. Based on this list, instructors in the Emory Writing Program expect that students will not use any genAI platform for any of the following tasks:  

• “to brainstorm a paper topic or thesis (prohibited conceptualizing)” 
• “to propose an organizational structure for a paper (prohibited outlining)” 
• “to polish a paper by correcting grammatical mistakes (prohibited editing)” 
• “to translate a paper originally written in another language into English (prohibited translating)” 
• to compose summaries of research articles or other resources/content (prohibited summarizing/research activity) 
• to identify repetitive passages or sentences that should be cut (prohibited revising) 

Given these prohibited uses, students should also avoid inputting ANY instructor created course materials, such as syllabi, readings, assignment sheets, writing prompts, slide decks, worksheets, or any other course-specific content into a commercial genAI platform or software of any kind, including for purposes of content review. Inputting instructors' course content is a violation of professional intellectual property rights and will be reported as an Emory Honor Code violation. 

Our positions and policies on genAI use are subject to revision, update, and reflection as the platforms evolve and as options for AI use continue to change. 

“2026 Resolutions.” CCCC Annual Business Meeting, 6 Mar. 2026, Cleveland, Ohio, Conference on College Composition and Communication, National Council of Teachers of English, https://cccc.ncte.org/cccc/2026-resolutions/. 

“Artificial Intelligence Policy.” UC Berkeley School of Law. Summer 2026. https://www.law.berkeley.edu/wp-content/uploads/2026/05/AI-Final-Policy-26.pdf. 

Byrd, Antonio. "Truth-telling: Critical inquiries on LLMs and the corpus texts that train them." Composition Studies, vol.51, no. 1, 2023, pp. 135-142. 

Cutler, Sonel. “Graduate Students Went on Strike. Then a Dean Suggested That Professors Use AI to Keep Classes Going.” The Chronicle of Higher Education, 29 Mar. 2024, https://www.chronicle.com/article/graduate-students-went-on-strike-then-a-dean-suggested-that-professors-use-ai-to-keep-classes-going. 

Elkhatat, Ahmed M, et al. “Evaluating the efficacy of AI content detection tools in differentiating between human and AI-generated text.” International Journal for Educational Integrity, vol. 19, no. 17, 1 Sept. 2023, https://doi.org/https://doi.org/10.1007/s40979-023-00140-5. 

Habib, Sabrina, et al. "How does generative artificial intelligence impact student creativity?" Journal of Creativity, vol. 34, no. 1, 2024, https://doi.org/10.1016/j.yjoc.2023.100072. 

Kalai, Adam Tauman, et al. "Why language models hallucinate." arXiv preprint arXiv:2509.04664, 2025, https://doi.org/10.48550/arXiv.2509.04664. 

Kidd, Celeste, and Abeba Birhane. "How AI can distort human beliefs." Science, vol.380, no. 6651, 23 June 2023, pp. 1222-1223, https://doi.org/10.1126/science.adi0248. 

Köbis, Nils, et al. "Delegation to artificial intelligence can increase dishonest behaviour." Nature, vol. 646, no. 8083, 2 October 2025, pp.126-134, https://doi.org/10.1038/s41586-025-09505-x. 

Koebler, Jason. “'AI Is African Intelligence': The Workers Who Train AI Are Fighting Back.” 404 Media, 12 Mar. 2026,https://www.404media.co/ai-is-african-intelligence-the-workers-who-train-ai-are-fighting-back/. 

Kshetri, Nir. "The environmental impact of artificial intelligence." IT Professional, vol. 26, no. 03, 2024, pp. 9-13, https://doi.ieeecomputersociety.org/10.1109/MITP.2024.3399471. 

Osborne, Merrick R., and Erica R. Bailey. “Me vs. the machine? Subjective evaluations of human- and AI-generated advice.” Scientific Reports, vol. 15, no. 1, 1 Feb. 2025, https://doi.org/10.1038/s41598-025-86623-6. 

Palumbo, Elizabeth. “A Student’s Right to Refuse Generative AI.” 29 Aug. 2025, Refusing Generative AI in Writing Studies, https://refusal.blog/. 

Perrigo, Billy. “Exclusive: OpenAI Used Kenyan Workers on Less Than $2 Per Hour to Make ChatGPT Less Toxic.” Time, 18 Jan. 2023, https://time.com/6247678/openai-chatgpt-kenya-workers/. 

Sano-Franchini, Jennifer, et al. “Refusing GenAI in Writing Studies: A Quickstart Guide.” Refusing Generative AI in Writing Studies, https://refusal.blog/2025/08/29/a-students-right-to-refuse-generative-ai/.  

Skibell, Arianna. “A Data Center Drained 30m Gallons of Water Unnoticed — until Residents Complained about Low Water Pressure - Politico.” Politico, Axel Springer SE, 9 May 2026, www.politico.com/news/2026/05/08/georgia-data-centers-water-00909988. 

Stadler, Matthias, et al. "Cognitive ease at a cost: LLMs reduce mental effort but compromise depth in student scientific inquiry." Computers in Human Behavior, vol.160, no. 108386, 30 Jul. 2024, https://doi.org/10.1016/j.chb.2024.108386. 

Vendrell, Mireia, and Samantha-Kaye Johnston. "Scaffolding critical thinking with generative AI: Design principles for integrating large language models in higher education." Computers and Education: Artificial Intelligence, vol. 10, no. 100572, 7 Mar. 2026,  https://doi.org/10.1016/j.caeai.2026.100572