This week, the conversation around the use of Generative Artificial Intelligence (GAI) in academia is taking a substantial step forward. Drawing inspiration from Cornell University’s approach, which offers a broad framework for integrating GAI into educational settings, the focus is shifting towards explicitly incorporating these technologies into academic curriculums, with specific guidelines for faculty members.

Expanding Learning Outcomes: The integration of GAI into teaching requires a reevaluation of learning outcomes. Instructors are advised to adapt their educational goals to prepare students for a future where GAI plays a significant role. This entails not only equipping students with the knowledge and skills necessary for emerging industries but also emphasizing critical thinking and higher-level learning objectives.

Emphasizing Safety and Ethics: As GAI technologies evolve, the importance of addressing ethical considerations and safety concerns becomes paramount. Faculty members are tasked with educating students about the limitations and potential risks of current GAI technologies, fostering a critical approach to their usage, and rigorously validating GAI-generated information.

Setting Clear GAI Usage Policies: Faculty should articulate clear, consistent policies regarding GAI use in their courses and assignments. This includes defining acceptable and unacceptable uses, ensuring students understand the boundaries of academic integrity, and emphasizing the importance of proper attribution when GAI tools are employed.

Recommendations for Faculty Implementation

• Defining Expectations: Faculty members should clearly state their expectations for GAI use in their courses, possibly tailoring guidelines to specific assignments. This clarity helps students understand when and how they can responsibly use GAI tools.
• Documenting and Attributing GAI Usage: When GAI is allowed, it’s crucial for students to document their use of these tools and correctly attribute the generated content. Faculty should provide guidelines on how students should validate GAI outputs.
• Encouraging Ethical Discussions: Incorporating discussions on the ethical implications of GAI use in education should be a continuous effort, helping students understand the broader impacts of these technologies.
• GAI for Assessments: Recognizing GAI’s potential to enhance education, we recommend its structured integration into assessments to effectively supplement learning outcomes. Faculty should establish clear guidelines ensuring GAI supports, rather than replaces, essential learning processes.

These expanded guidelines aim to foster a more informed, ethical, and practical integration of GAI into academic practices, preparing students not just to use these technologies, but to understand their implications deeply. The ongoing dialogue and adaptation of these recommendations are expected to evolve as GAI technologies and their applications in educational contexts continue to develop.