Guidelines for Academic Use
GAI and Pro Humanitate: Guidelines for Academic Excellence
Adapted from the AI Working Group for Academics Final Report (March 2025)
The guiding principles in our vision – honoring human dignity and wellbeing, embracing transformative learning and meaningful work, and advancing the ethical pursuit of knowledge – ground our uses of GAI such that we realize its revolutionary potential for good without losing sight of our human and educational purpose. In keeping with those principles and Wake Forest University’s values and mission, the following guidelines articulate expectations and recommendations for academic work.
Include GAI expectations and policies on each course syllabus
- Address issues such as: the types of resources students can use for which assignments; how and when GAI platforms may be used; how and when students can work together on assignments; appropriate citation methods, etc. Syllabus statements provide clarity for all students and support their success.
- Situate these expectations within the larger context of academic and professional integrity as well as support for student learning.
- Consult with peers and other professional resources for best practices.
- As courses fulfill various roles in our curricula, the permitted uses of GAI may not be the same in every course or on every assignment in a course, and permitted uses of GAI may change over time.
- Within the overlapping frameworks of academic freedom, course coordination, and department/unit curriculum and policies, instructors set expectations for their classes, and these expectations can differ.
- Syllabus statements provide clarity for all students and support their success.
- The absence of GAI guidance in a course undermines the ability to recognize and adjudicate instances of academic misconduct.
Provide clarity on academic misconduct with GAI
- While each school maintains its own system, evidentiary standards, and procedures for identifying and adjudicating cases of academic misconduct, the College and each school should ensure that existing processes and criteria in judicial frameworks and academic honor codes are adequate to address academic misconduct with GAI. The following points represent a core set of GAI-related issues that should inform judicial standards and honor codes.
- Clearly state the definition of Academic Misconduct relative to GAI: GAI may impact learning contexts and assessments in ways that require new structures for producing authentic student work that are distinct from those described in existing honor codes and definitions. A definition may be as simple as naming the use of GAI (much like any other technology) for academic purposes without permission. For example: “The unauthorized use of generative AI platforms by a student, whether in the classroom, laboratory, studio, intern- and externships, independent research settings, or other spaces identified as serving educational goals.”
- Instructors and students share responsibility for communicating about GAI use. With wide range of possible applications in learning contexts, it is important to establish the responsibility of both instructors and students for communicating and clarifying acceptable GAI use and boundaries.
- Instructors are responsible for communicating their policies and guidelines to students. In order to substantiate cases of academic misconduct, instructional materials (such as the course syllabus, assignment prompts, and/or verbal instructions) need to include directions regarding the authorized use of GAI, including method(s) for disclosing or citing such use; in short, when and how GAI tools can be used, along with when and how such use should be acknowledged. The instructor should be able to demonstrate that students had a reasonable opportunity to know the rules and expectations of the given context.
- Students are responsible for requesting clarification when they are uncertain about the appropriateness of a given use of GAI for a particular assignment (as well as when they have questions about maintaining academic integrity more broadly). Students should be able to demonstrate that they took reasonable steps to know the rules and expectations regarding GAI in a given situation.
- Insufficiency of GAI Detectors: AI detectors are principally problematic for the high numbers of false positives they currently return (as of February 2025). Sharing student work and data with AI detectors also brings up serious ethical considerations for privacy, intellectual property, and adding student work to AI training materials.
- Evidentiary standards for academic misconduct should not allow for AI detectors alone to constitute a sufficient standard of proof. GAI detector results may be included as evidence but are insufficient on their own.
- Address multiple, possible sources of evidence for consideration in conjunction with AI detection, such as course materials, student work, credible witness accounts, and faculty expertise in their fields; additional sources of evidence that are demonstrated to be reasonably additive to the case.”
Ensure Equity and Access
- All students need equitable access to key resources when GAI is taught or used as well as guidance on protecting their own and others’ privacy and data.
- Any instructor whose course explicitly includes the use of GAI tools is expected to ensure that all students have access to the necessary GAI tools. The instructor is also responsible for collaborating with appropriate campus partners (IS, CLASS, etc.) to implement accommodations or identify accessible alternatives to their chosen GAI tools for students with disabilities.
- If any fee-based GAI tools are used for a particular course, instructors should follow existing university processes for transparency about the cost of required course materials. Instructors are asked to use university-licensed or university-recommended free tools whenever possible.
- Share university resources for students that explain best practices for protecting their privacy, as well as personal and university data when using GAI tools.
- The University will take a proactive approach to the accessibility of GAI tools by:
- Building capacity and specialized knowledge of GAI among departments that typically respond to questions of technology accessibility (e.g. IS Technology Accessibility, CLASS, the Instructional Technology Group).
- Offering student-facing resources that identify common barriers to accessibility in GAI tools and offering guidance on how to select tools that best fit the needs of students who use assistive technology.
- Consider ways to utilize the multi-modal capabilities of GAI tools for instructors, students, and staff to make materials and projects accessible to classmates and to a broader audience, e.g. generating a transcript for a podcast or video, generating written descriptions for a visual project.
- CLASS Office resources on accessible classroom inclusivity
- Technology Accessibility at WFU for basic principles of digital accessibility and contact information for accessibility testing for departments and instructors selecting new GAI tools.
- Instructional Technology Group for instructors and departments in the College
Provide and utilize professional development opportunities for instructors
The University should empower instructors to investigate and explore GAI tools and to
develop pedagogical skills for equipping their
students to engage thoughtfully with the use and implications of GAI for critical thinking, learning, creative production, privacy concerns, and broader civic or societal responsibilities through a range of ongoing professional development opportunities.
Engage and support Discussion Framework conversations
- Advance understanding of how GAI 1) is taught and experienced by students across courses in academic programs and 2) is changing faculty work relative to teaching, research, scholarship, creative activities, and administrative tasks through ongoing conversations among program faculty.
- The AI Working Group for Academics recommends the Provost, Deans, and other academic leaders support the generation of GAI Discussion Frameworks among faculty connected by school, department, area, or program.
Discussion Framework: recommended GAI Topics for ongoing conversations
The Working Group advocates for the value of faculty having program- or discipline-based, collective discussions in academic units, departments, or programs with the goal of sharing ideas and concerns, developing an array of innovative and appropriate solutions to challenges, and understanding how GAI may be taught and experienced by students across courses in the program. In short, “start a conversation” is our recommended first step.
The Discussion Framework tool has been developed to provide prompts that academic programs can consider together on how GAI is impacting their teaching and research in ways specific to the discipline(s) and curricula they share. GAI in academic contexts spans many dimensions of faculty work, and groups will not be able to cover everything at once. We recommend that academic units plan for an ongoing way to continue to address GAI impacts together, select individual topics to review over time, and give progress updates in annual reports.
The following topics align with the guiding principles and address areas of program-level opportunity and concern for all instructors. The topics are neither required nor exhaustive and are intended to support productive conversations among colleagues.
- Academic integrity and learning: Students need clear guidance in every class regarding the permitted use of GAI technology, its role, if any, in their learning and skills development, and they need clear communication about the consequences of inappropriate use of GAI technologies. Department or program discussions will provide an opportunity for instructors to share a range of perspectives and scenarios for the permission or prohibition of GAI in the pursuit of course or program outcomes.
- Program discussions should strive, where possible and relevant, for consensus on approaches to GAI uses in multiple-section courses, especially those that serve as prerequisites to other courses.
- A critical discussion topic includes how GAI may affect typical disciplinary assessments and demonstrations of learning and if that projected impact requires the development of additional or alternative measures for making learning visible.
- How do students show the expected learning in various assignments that are typical in the curriculum?
- Faculty should review guidelines from school/College honor codes and judicial frameworks (per university-wide recommendations above, these groups may set new expectations for GAI-related academic misconduct)
- Resources
- Equity and access: University expectations state that when GAI is taught or used in assignments, instructors have a responsibility to ensure that students will have equitable access to tools and resources, including options for disability accommodations. Department or program conversations addressing recommended GAI tools and accessibility options further these equity and access goals. Agreement on using the same tools across courses in the curriculum, where possible, also improves equitable access, especially if multiple courses in the same program require the use of fee-based GAI platforms.
- Using GAI as a learning tool and an appropriate professional skill: GAI may not be an appropriate learning or skills development tool in all courses, but program instructors should be aware of GAI use across their shared curricula. As students are already using GAI across all disciplines, the AIWG strongly recommends departments include instruction in GAI use and best practices somewhere in their curriculum.
- Discussion should support an understanding among instructors of the range of GAI use across the program’s curricula. Where is GAI taught and used in the curriculum? In which courses are students using GAI to learn course material? In which courses are students specifically not using GAI? In which courses is GAI itself a subject of the course material? What GAI experiences might students bring to courses at different points in the curriculum?
- Identify ways GAI is best used or not used to enhance learning in this field/discipline.
- Identify the skills and approaches necessary to use GAI successfully in relevant fields, disciplines, or professions. How are your fields and professions using GAI that students should learn about?
- Where will students learn about any recommended disciplinary or professional practices for using GAI resources?
- Are there standards for verifying and citing results obtained by GAI that should be taught in your curriculum?
- Long term, what is the role of GAI in your curriculum? Is GAI a part of the program’s learning outcomes now or in the future?
- How can or should the program coordinate GAI learning across courses to address both reinforcement of skills and issues of duplication?
- Faculty use of GAI as a resource for teaching, research, scholarship, creative activity, and administrative work: All faculty should be aware of the increasing number of ways faculty may choose to use GAI to enhance all aspects of their work, along with the opportunities and the risks that GAI technologies provide relative to teaching, research, scholarship, creative activities, and administrative tasks. Ongoing discussions in the program should include peer and other professional association guidance on the appropriate use of GAI technologies in these areas, especially as might impact the evaluation of activities in line with tenure and promotion criteria.
- Identify and discuss the ways faculty might use GAI in teaching support work (outside the classroom, such as preparing syllabi, designing assignments, grading, writing letters of recommendation, etc.) and administrative tasks. Understanding that GAI is useful in many areas and that the tools are embedded in our day-to-day software (Google suite, Canvas, etc.), conversations focused on best practices and risks, data security, and privacy will help faculty make informed choices. In line with the Statement of Principles, commitment to meaningful and person-centered faculty-student engagement should guide these applications of GAI technology.
- What are the ethical considerations guiding these uses of GAI technology?
- Where can GAI provide benefits to faculty work without compromising engagement with students and their learning?
- What are the expectations for disclosure of GAI usage in these contexts?
- Are there any areas of GAI use the department considers inappropriate?
- In performing administrative and operational work for the university, faculty should consult the university’s Administrative Use GAI Guidelines, especially for considerations of information and data security and privacy, university licenses and contracts, and procurement processes for purchasing GAI tools.
- What are emerging professional standards in our fields for GAI in research, publishing, citation, and intellectual and creative authorship?
- Identify and discuss the ways faculty might use GAI in teaching support work (outside the classroom, such as preparing syllabi, designing assignments, grading, writing letters of recommendation, etc.) and administrative tasks. Understanding that GAI is useful in many areas and that the tools are embedded in our day-to-day software (Google suite, Canvas, etc.), conversations focused on best practices and risks, data security, and privacy will help faculty make informed choices. In line with the Statement of Principles, commitment to meaningful and person-centered faculty-student engagement should guide these applications of GAI technology.
The Provost’s Office organized an Artificial Intelligence Working Group for Academics that met from November 2023-February 2025 to discuss the risks and opportunities associated with GAI in teaching, learning, and research and its relationship to Wake Forest’s mission and goals. The group’s final report, delivered to the Provost and Deans in March 2025 reviews some impacts of GAI on Wake Forest’s educational enterprise, articulates principles based on our mission and values to guide our practices for engaging with GAI, and offers specific recommendations for maximizing the benefits of this technology while mitigating the likely harms associated with it.
- Kendra Andrews, Assistant Teaching Professor of Writing, College
- Betsy Barre, Assistant Provost and Executive Director of the Center for the Advancement of Teaching
- William Cochran, Assistant Teaching Professor of Computer Science, College
- Davita DesRoches, Alternative Media Specialist, Center for Learning, Access, and Student Success
- Mohamed Desoky, Academic Director and Professor of the Practice in Financial Technology and Analytics, School of Professional Studies
- Elizabeth Ellis, Teaching Librarian, ZSR Library
- Anne Hardcastle, Associate Provost for Academic Affairs, Committee Chair
- Ellen Kirkman, Professor of Mathematics, College
- Shannon McKeen, Professor of the Practice and Executive Director, Center for Analytics Impact, School of Business
- Mur Muchane, Vice President of Information Technology and Chief Information Officer
- Keith Robinson, Associate Dean for Research and Professor of Law, School of Law
- Fred Salsbury, Graduate Director and Professor of Physics, Graduate School of Arts & Sciences
- Melva Sampson, Assistant Teaching Professor of Preaching and Practical Theology, School of Divinity
- Erica Still, Associate Dean for Faculty Recruitment, Diversity, and Inclusion, Honor and Ethics Council, College
- Mark Vail, Worrell Chair of Politics and International Affairs, Judicial Liaison, College