Generative Artificial Intelligence (GAI) Policy

Purpose

McNeese State University recognizes the potential for generative artificial intelligence (GAI) to transform higher education practices in teaching, learning, and assessment. The rapid growth and acceptability for use of GAI in the professions necessitates purposeful and diligent integration of GAI tools into the McNeese learning community as a tool to facilitate interactive learning. It is critical for McNeese to prepare GAI-literate students so they are informed about the potential positive and negative implications related to GAI in their field. This policy serves as a general guide for the integration and use of GAI tools.

This policy assumes a common definition of artificial intelligence as the capability of a machine to imitate intelligent human behavior and follows the state of Louisiana definition of artificial intelligence as a machine-based system that can, for a given set of human-defined objectives, make predictions, recommendations, or decisions influencing real or virtual environments. Artificial intelligence systems use machine- and human-based inputs to perceive real and virtual environments, abstract such perceptions into models through analysis in an automated manner, and use model inference to formulate options for information or action. GAI applications can generate content by utilizing Large Language Model (LLM) technology which responds to prompts by a user. The range of available GAI tools is expanding rapidly and can generate not only content, but also create code, images, music, and other media.

GAI Benefits and Limitations

The higher education learning community stands to benefit and must assume leadership for integrating appropriate use of technology, such as GAI, into the curriculum. Students should have a sound understanding of the potential of GAI tools, how to use the tools with integrity, and the limitations presented by the inappropriate use of them.

When using GAI, faculty and students must consider its limitations, such as its generation of incomplete, inaccurate, or false information; its use of inaccurate or fabricated citations; its tendency to include plagiarized text without proper attribution or citation; its reiteration of LLM biases and propensity to use discriminatory language; its inability to replace human expression (but its output does replicate it); its disclosure that it may harvest and share user data; and more.

Responsible and Ethical Use of GAI

Policies related to the use of GAI tools may undergo frequent revisions as needed. The general policy pertaining to the use of GAI tools at McNeese begins with the following:

• There is no blanket ban for the use of GAI tools or blanket requirement to integrate GAI tools. Faculty must communicate clearly to students the stance for use of GAI in the course by incorporating and adhering to their choice of one of the University Syllabus Policy statements regarding GAI for each course. Faculty must provide clearly documented guidance for the use of GAI for assignments and student learning expectations of the course.
• Expectations for upholding academic integrity must be consistent. Content produced by GAI does not represent original content generated by a student and is considered a violation of academic integrity if not cited accurately. Faculty must emphasize academic honesty.
• Submitting GAI generated work by students or by faculty conducting research as one’s own is considered a violation of academic integrity.
• GAI cited resources must be checked for accuracy and originality. The McNeese community is encouraged to use GAI tools with transparency and to adhere to citation guidelines if GAI content is included in assignments or work documents.
• Copyright regulations must be considered when using GAI tools. GAI understanding of copyright or academic integrity is non-existent and frequent acts of plagiarism are known.
• Faculty and students must be informed that GAI tools may access private data. For example, signing up for ChatGPT authorizes ChatGPT to share personal information with third parties without notice. Furthermore, ChatGPT’s parent company, OpenAI, discloses that it can access any information fed into or created by its technology; it uses log-in data, tracking, and other analytics, and the technology does not respond to “Do Not Track” options.
• McNeese takes seriously the need to uphold FERPA, HIPPA, and the privacy of personal information; therefore, GAI tools must be used with the highest regard for ethical considerations such as:
  • Protecting student and personnel information and complying with privacy regulations of such data must be considered and prioritized when using GAI tools.
  • Ethical use of GAI generated information means GAI generated narratives must be evaluated to avoid biases, disinformation, and misinformation and to ensure fairness and accuracy.
  • GAI tools incorporated into course learning objectives and assignments must be designed to enhance student learning and to prepare students for ethical and responsible use of AI tools in the discipline.
  • Faculty should develop a general understanding of LLM learning and how AGI systems generate information and include this information in student learning objectives.
  • Faculty and staff should make efforts to participate in GAI-related professional development to ensure GAI is integrated effectively, ethically, and confidently into the learning and working community.

Specific Restrictions for the Use of GAI

GAI tools, including, but not limited to ChatGPT, Microsoft Copilot, and Gemini, may not be used with personal, confidential, proprietary, restricted, and sensitive information unless provisions allowing such use are included in a University contract specifically designed to protect such data.

For the purpose of this policy, confidential data is defined as information whose unauthorized disclosure would cause serious and adverse effects on the University, third party, supplier, individual, or the state of Louisiana.

Examples of confidential data that may not be used with GAI tools includes, but is not limited to, social security numbers; access device numbers; biometric identifiers; dates of birth; driver’s license numbers; passport and visa numbers; personal vehicle information; financial information such as credit card or account numbers, etc.; information pertaining to legal affairs or institutional relations; contracts; user account passwords; health information including HIPPA information; FERPA information; and details about McNeese infrastructure or operational information.

Restricted data means data that requires strict adherence to legal obligations such as federal, state, or local law, specific contractual agreements, or data specifically designated as restricted data in applicable state or agency policy.

GAI tools may not be used to generate non-public content, proprietary or unpublished research, legal analysis, recruitment decisions, completion of academic works not allowed by the instructor, non-public instructional materials, and direct grading.

Proprietary information as defined by the state of Louisiana means any code, pattern, formula, design, device, method, or process which is proprietary or trade secret information which has been submitted to a public body by the developer, owner, or manufacturer of a code, pattern, formula, design, device, method or process in order to obtain or retain approval of such code, pattern, formula, design, device, method, or process for sale or use in the state.

Additional examples of prohibited data for use with GAI include employee names, annual performance review details, personnel file information, unpublished research data, and internal memos and emails.

Communication

This policy is distributed via the University Policies webpage.