The rapid evolution of generative AI offers transformative opportunities for research and education while presenting significant challenges. Our program is committed to harnessing AI’s potential responsibly, ensuring transparency, and safeguarding academic integrity. This document is intended as a living guideline—a dynamic framework that will be promptly updated as AI technology and its applications evolve.

Student Guidelines

Note: Each Faculty is responsible for defining what is permissible and what is prohibited for the use of AI in their course. The following section represents only suggestions that can be adopted or modified by the faculty. The faculty is also responsible for informing the students on their final recommendations.

• Permissible Use and Disclosure:
  

  • Students are encouraged to integrate AI tools as supplements to their original work. When using these tools:
    • Disclosure: Every submission must include an “AI Contribution Statement” that specifies which parts of the work were AI-assisted, along with appropriate citations.
    • Verification: Students must independently verify and validate AI-generated content to ensure its accuracy and relevance before inclusion in their final work.
    • Plagiarism: AI tools can plagiarize original work. It is the student’s responsibility to ensure that proper citations are included, and original authors are acknowledged.
    • Examples of acceptable use of GenAI:
      • Literature Search and Summarization: Use AI tools to help identify relevant academic publications, extract key findings, and summarize complex literature. This can save time during the initial research phase. However, students must independently verify the information and always cite the original sources.
      • Text Refinement and Language Editing: Leverage AI to proofread, correct grammar, and enhance the clarity and style of written work. While AI can assist in refining language, the intellectual content must remain the student's own, and any AI-suggested modifications should be critically reviewed to ensure they align with the student's intended message.
      • Argument Construction and Idea Development: Employ AI to generate preliminary outlines or to explore potential structures for arguments and hypotheses. AI-generated frameworks can serve as a starting point, which students should then refine, expand upon, and substantiate with evidence, ensuring that the final work reflects their original reasoning and critical analysis.
      • Data Organization and Visualization: Utilize AI for organizing research data and creating visual representations such as charts, graphs, or conceptual maps. These tools can aid in clarifying complex datasets, but students must verify the accuracy of the output and ensure that visualizations are correctly interpreted and integrated into their analysis.
      • Brainstorming and Concept Exploration: Use AI as a creative tool to generate diverse ideas or research questions during the brainstorming phase. While AI can propose innovative directions, students should critically assess and develop these ideas further, ensuring that the final project reflects their personal insight and scholarly rigor.

• Best Practices for AI Integration:

  • Transparency: Clearly delineate the role of AI in your research, writing, or project development.
  • Documentation: Maintain a log of your interactions with AI tools—including tool version, purpose, and specific contributions—to aid in review and reflection.
  • Supplementary Learning: Use AI as a tool for brainstorming or drafting but engage critically with the material to ensure authentic learning and personal insight.

• Prohibited Practices:

  • Problem solving: Using AI tools to solve homework problems, quizzes or exams is prohibited.
  • Overreliance or Misrepresentation: Work that is primarily or solely generated by AI without clear disclosure, that fabricates data, or that obscures personal analytical contributions is unacceptable.
  • Misuse in Assessments: Any attempt to bypass genuine learning through improper or undisclosed use of AI will be treated as a violation of academic integrity.

• Student Support and Resources:

  • Guidance Documents: Detailed instructions, case studies, and examples on proper AI usage will be provided on the program’s online portal.
  • Feedback Channels: Students are encouraged to seek clarification regarding AI use and should consult designated support channels (see Faculty Recommendations for the AI Contact).
     

Recommendations for Faculty

• AI Literacy and Ethics Training:

  • Department Seminars: Organize and participate in regular seminars focused on the technical and ethical use of AI. These seminars should include practical demonstrations, case studies of effective and problematic AI integration, and discussions on the best practices.
  • Designated AI Contact: Appoint an AI-knowledgeable person within the department to serve as a point of contact for both students and faculty. This individual will provide up-to-date resources, answer AI-related queries, and advise on emerging trends.

• Reflective Practices and Transparent Disclosures:

  • Require students to submit brief reflective essays alongside their work that detail the benefits, challenges, and ethical considerations encountered while using AI.
  • Ensure every assignment includes an “AI Contribution Statement” to document the extent and nature of AI involvement.
  • Update course syllabi to include any specific prohibitions on the use of GenAI and consequences for violating those prohibitions.

• Enhanced Evaluation Methods:

  Develop and implement innovative assessment tools that prioritize oral presentations, interactive Q&A sessions, and hands-on laboratory demonstrations.
  Rationale:

  • Authentic Skill Assessment: These methods better gauge practical knowledge, communication skills, and real-time problem-solving abilities.
  • Mitigating AI-Generated Content Risks: Emphasizing live, interactive evaluations minimizes the risk of overreliance on written submissions that could be predominantly AI-generated.
  • Increased Engagement: Dynamic assessments promote critical thinking and ensure active student participation, reflecting the interdisciplinary and applied nature of our field.
     

• Limitations of Automated AI Content Detection Tools:
  

We do not recommend the use of automated tools to flag undisclosed AI content for several reasons. First, the rapid advancement of AI technologies renders these tools increasingly ineffective, as new models quickly bypass detection mechanisms. Second, current legal precedents indicate that it is extremely challenging—if not impossible—to prove conclusively that a text was generated by AI, raising significant legal and ethical concerns. Finally, focusing on automated detection risks embroiling our academic processes in legal conflicts, whereas our priority should remain on education, transparent practices, and fostering genuine academic integrity.

Recommendations for the College and University

• Unified and Adaptive Policy Framework: 
  Collaborate with central offices (OIT/UIS/OGC) to ensure our guidelines align with university-wide policies. Commit to regular review cycles that allow rapid updates in response to emerging AI developments.
• Infrastructure for AI Training and Research:
  Invest in comprehensive training programs and workshops aimed at bolstering AI literacy for both students and faculty. These initiatives should be designed in partnership with campus entities such as the Library and IT departments.
• Support for Novel Evaluation Methods:
  Allocate resources for the research and development of innovative assessment tools that emphasize oral presentations, interactive Q&A, and hands-on demonstrations. This strategy is essential for fostering authentic skill acquisition and reducing reliance on written submissions susceptible to AI generation.
• Living Document Commitment:
  Establish clear mechanisms for the continuous update and refinement of this guideline. Engage a diverse group of stakeholders—including faculty, students, industry experts, and ethics boards—to ensure our policies remain responsive to technological progress and emerging best practices.

By integrating these comprehensive guidelines and recommendations, our program is dedicated to fostering a responsible, innovative academic environment. This framework not only prepares our graduates for an evolving professional landscape but also ensures that the use of GenAI enhances learning outcomes while upholding the core values of academic integrity and rigor.

* Note: In this document, generative AI is abbreviated as GenAI, a term that is more commonly used; the acronym GAI used by the College can easily be mistaken for General Artificial Intelligence.