Participants of the Critical AI Literacy for Reading, Writing, and Languages Workshop, convened in 2024 and funded by the NEH, include members of the MLA-CCCC Joint Task Force on Writing and AI (AITF) and representatives from a variety of humanities professional organizations. Together, they wrote this third working paper.
Workshop Participants and Authors of Working Paper 3:
- Kofi Adisa (AITF)
- Antonio Byrd (AITF)
- Estela Ene (TESOL International Association)
- Leonardo Flores (AITF)
- Joanne Giordano (Two-Year College English Association)
- David Green (AITF)
- Holly Hassel, co-chair (AITF)
- Jason Hendrickson (College Language Association)
- Sarah Z Johnson (AITF)
- Matthew Kirschenbaum (AITF)
- Elizabeth Losh, co-chair (AITF)
- Temptaous Mckoy (Association of Teachers of Technical Writing)
- Anna Mills, (AITF)
- Lilian Mina (Council of Writing Program Administrators)
- Sherry Wynn Perdue (International Writing Center Association)
- Judy Ruttenberg (Association of Research Libraries)
- Zhaozhe Wang (CCCC Second Language Writing Standing Group)
- Jervette Ward (College Language Association)
- Jen William (Association of Language Departments)
Participating Professional Organizations of Working Paper 3:
- Two-Year College English Association
- TESOL International Organization
- College Language Association
- Association of Teachers of Technical Writing, the Council of Writing Program Administrators
- International Writing Center Association
- Association of College and Research Libraries
- CCCC Second Language Writing Group
- Association of Language Departments
This working paper advocates for a comprehensive and critical approach to integrating AI literacy objectives in higher education. Recognizing the sudden and profound influence of AI technologies on academic, professional, and civic life, we articulate specific learning outcomes for formulating shared goals. The challenges involved in fostering critical generative AI literacy among students, educators, programs, and institutions should be recognized on as ongoing. We also emphasize that this literacy should be critical in its orientation and acknowledge the importance of legitimating forms of resistance and refusal to the integration of AI tools, platforms, and systems. As in the case of earlier working papers, we assert that responsibility for AI literacy should fall not only on students and their instructors – who are often the most precarious members of the academy – but also on programs and institutions, who must provide resources and infrastructure and uphold fundamental values in fair communication and ethical research.
The working paper delineates literacy outcomes for students, encouraging them to engage thoughtfully and ethically with generative AI (GAI), enhancing their ability to assess AI-generated content for accuracy, relevance, and bias. Students are urged to develop a nuanced understanding of GAI tools, including privacy considerations and adapting to rapid technological changes. Recognizing GAI’s limitations and maintaining critical reflection on their use within the learning process are central components. Additionally, students should learn to acknowledge GAI use transparently in academic work, aligning with specific academic integrity policies.
For educators, the document outlines the importance as well as the challenges of pedagogical and ethical readiness. Teachers are encouraged to not only understand GAI’s functionality but also to approach it critically, assessing how it may impact students’ creativity, access, and linguistic justice. Professional development in AI literacy is recommended, alongside an emphasis on transparency and ethical considerations. Educators should model responsible AI use, helping students grasp the ethical complexities surrounding intellectual property and privacy. The report also advocates for the continued necessity of shared governance in creating equitable, adaptable GAI guidelines within departments and courses.
At the program and departmental level, the document advises integrating critical GAI literacy into curricula—as opposed to allowing students to encounter the technology piecemeal—and supporting learning continuity across courses. Programs should align GAI literacy with existing learning outcomes, avoiding redundant or merely reactive instruction. Coordinated program-wide strategies are essential to support the diverse needs of students, particularly ESL learners, and those in writing centers. Departments are encouraged to develop shared resources, including syllabi and curricular models, to embed critical GAI literacy consistently, fostering a culture of transparency and critical engagement.
Institutionally, the report underscores the importance of promoting ethical AI use, particularly in decision-making processes related to hiring, admissions, and student services, where algorithmic bias may pose significant risks. Institutions are called to support the development of critical AI literacy across all disciplines, fostering cross-departmental collaborations, and they are reminded that much current AI research is taking place in writing centers, libraries, and community colleges and other access-oriented institutions. Institutional strategies should aim to build inclusive, accessible AI frameworks that recognize the impact of GAI on underrepresented and at-risk communities and how transnational corporate partnerships pose risks to human and environmental rights. Recommendations include creating policies that reflect ethical standards, support student agency, and provide continuous learning opportunities for faculty.
In conclusion, the document calls for a balanced, critical approach to AI in academia, advocating for collaborative, informed, and pragmatic policies that prioritize human oversight. It does not endorse reflexive or uncritical or mandatory adoption of GAI. Faculty governance and the importance of individual instructors making informed decisions about their classroom environment remains uncompromised. The working paper instead seeks to underscore the importance of a critical AI literacy framework that values ethical decision-making, transparency, and responsible integration of GAI, preparing students and educators to navigate an increasingly AI-replete world with informed perspectives.