Summary of Recommendations
This subcommittee makes the following recommendations for institutions interested in developing AI policies or guidelines, keeping in mind that not all suggestions in this chapter will be appropriate for all institutions.
- Develop policies and guidelines with the engagement and input of a variety of campus stakeholders, including faculty, staff, students, and administrators.
- Recognize that there is not a one-size-fits-all solution; policies/guidance may be needed at different levels (institution, school, college, division, department, course) and for different disciplines.
- Consider existing policies that address or can be modified to address AI use.
- Examine how AI is used in existing systems across the institution (not necessarily for teaching and learning) and its repercussions on data security.
- Address procedures for obtaining permission before others’ content is used in prompts or training data.
- Provide or procure educational opportunities for campus community members to learn how AI works, as well as its strengths and weaknesses; encourage faculty to align potential AI use with learning goals.
- Avoid AI detection tools and de-prioritize detection of cheating; instead, focus on how students are learning in this landscape (Trice, 2025).
- Consider mechanisms or processes for the institution to support faculty as they use AI and as it is used in their classes (e.g., processes for addressing academic integrity).
- Ensure that policies or guidelines are flexible/adaptable to account for the rapidly evolving AI environment.
- Ensure that any policies or guidelines are easily discoverable and accessible to the institution’s community members; it is important to have transparency throughout the process.
- Provide transparency in communicating how AI is used on campus, as well as during the policy development process. It is helpful for campus constituents to be aware of AI and its role at the institution and to have the opportunity to offer constructive feedback.
