ARTIFICIAL INTELLIGENCE AND GENERATIVE AND EMERGING TECHNOLOGIES SUPPORT FOR THE CLASSROOM

• More generally, to provide provisional guidance to the university community, the current baseline expectation remains that, unless otherwise clearly attributed, a student is expected to have produced their own text and other content in submitted coursework. Like the unattributed use of any other source, the unattributed use of LLMs in coursework violates academic integrity. Colleges, departments, and instructors are welcome to invite the use of LLMs in their coursework, but if they do so, they ought to make explicit in syllabi (and, ideally, in assignment sheets and verbally as well) what is expected of students regarding this LLM use on specified assignments. In keeping with the necessary honesty and transparency of academic work in general, academic work that allows for LLM use should still attribute such use, as with any other source that scholars use to aid their work. Failure to cite the use of LLMs falls under the usual definition of plagiarism. (Where appropriate, LLMs should be cited using the instructions found on this or similar sites, and adapted as needed for different models.) Instructors permitting or requiring LLM use should also make clear that such permission does not apply outside the assignment(s) or course(s) for which the exception has been made.

• It is hoped that this general way forward will allow instructors in the various disciplines to utilize and experiment with LLMs in their courses if they so choose, while maintaining a baseline of clarity on expectations regarding LLM use about course work, learning outcomes, and academic integrity broadly understood. The deployment, development, and integration of these technologies into various sectors of society will continue to change and evolve, and this statement of guidance will be revised and altered as the university deems appropriate considering the changing situation.
• Finally, we encourage instructors to begin the new year from a place of trust and transparency, inviting students into dialogue about the goals of higher education and working toward them together in these new circumstances. We believe that increased surveillance and suspicion will not lead us to improved student learning and a culture of academic integrity, but rather the fostering of candor and cooperation will do so as we engage in the labor of academic work side by side.

Note: Those who view plagiarism as an unwarranted categorization for LLM use that lacks attribution are asked to revisit the definition of plagiarism and to note in addition that—while the specific text produced by LLMs for a particular prompt may be superficially novel—LLMs do not generate their own responses whole-cloth but are trained on prior humans’ texts and other data, and guided by teams of workers who label that data. That is, other humans’ labor and intellectual property are always implicated and always in use when LLMs are employed, however anonymous and depersonalized those humans become in the black box mediation of an LLM. In addition, the initial human labor and intellectual property was used without those humans’ consent.

• Marquette does not have a policy around the use of artificial intelligence and predictive technologies, as it is an evolving and quickly changing technology.
• As faculty and instructors, you can create your own “policy” around this in the classroom.
• However, we have come up with some recommended language that might support you in the classroom along with some additional information.
• NOTE: If you do not provide any guidance for students in their potential use of these technologies the default of the university will be that any students using AI without permission, without proper citation and credit, and without faculty approval will be vulnerable to an academic integrity violation.
• Set expectations early and often in the classroom via the syllabus and verbally.
• Consider talking with students with complete transparency about the do’s and don’ts of this evolving technology. In other words, provide them with the WHY. For example, we are trying to get students to consider that although these are evolving and oftentimes exciting technologies, we still have the responsibility to help them become citizens of the world with a value system that has the process of work as having as much importance as a final product for a grade. We need to also consider that what they may think of as real data may not in fact turn out to be that.
• Consider the ways in which we have traditionally as universities measured learning. Are there new ways that remove the influence of newer technologies while maintain the learning outcomes and values we are trying to create with them?
• AI and Predictive Technologies RESOURCE PAGE
• Guidance for Teaching in the Era of Chat GPT and other AI Predictive Technologies (includes materials from a workshop held in Spring 2023, courtesy of Dr. Brian Spaid, Manoj Babu, Melissa Shew and other workshop participants).

• Give thought and consideration to determine what use of any generative technologies if permitted or prohibited. State this CLEARLY in your syllabus and verbal announcements in a consistent manner so there is no confusion on the student end.
• We highly recommend you continue to include (or include if you haven’t already) the Marquette Academic Integrity policy on your syllabus which includes copyright and plagiarism language as the use of these technologies will fall within these policies:

  STATEMENT ON ACADEMIC INTEGRITY

  We, the scholars of Marquette University, recognize the importance of personal integrity in all aspects of life and work. We commit ourselves to truthfulness, honor and responsibility by which we earn the respect of others. We support the development of good character in our academic community and commit to uphold the highest standards of academic integrity as an important aspect of personal integrity. Our commitment obliges us as students, faculty and staff to conduct ourselves according to the Marquette University Honor Code set forth below. We do this in pursuit of Marquette University’s mission, which is the search for truth, the discovery and sharing of knowledge, the fostering of personal and professional excellence, the promotion of a life of faith and the development of leadership expressed in service to others.
  Students are asked to commit to academic integrity through the following honor pledge. Faculty may require students to sign the pledge in their courses or for any individual assignment.

• If as an instructor, you decide to allow students to use a form of predictive technology such as ChatGPT you should tell them they must cite any content taken from said technology that will comply with all citation guidelines and copyright requirements. Here is a guide on citing ChatGPA in APA format (as a side note, this is also an opportunity to talk to students about making sure AI-generated information/citations are real and correct as it is not uncommon for ChatGPT-generated information to be nonsense).

Artificial intelligence (AI) language models, such as ChatGPT, may be used for any assignment with appropriate citation. Examples of citing AI language models are available at the APA Style website How to Cite Chat GPT [or provide an alternative reference appropriate for your class].

NOTE: You are responsible for fact checking statements composed by AI language models.

Artificial intelligence (AI) language models, such as ChatGPT, may be used for [assignment types A, B & C] with appropriate citation, but not for [assignment types D, E & F]. If you are in doubt as to whether you are using AI language models appropriately in this course, I encourage you to discuss your situation with me. Examples of citing AI language models are available at the APA Style website How to Cite Chat GPT [or provide an alternative reference appropriate for your class].

NOTE: You are responsible for fact checking statements composed by AI language models.

Artificial intelligence (AI) language models, such as ChatGPT, and online assignment help tools, such as Chegg®, are examples of online learning support platforms: they cannot be used for course assignments except as explicitly authorized by the instructor. The following actions are prohibited in this course [remove bullets as necessary]:

• Submitting all or any part of an assignment statement to an online learning support platform;
• Incorporating any part of an AI generated response in an assignment;
• Using AI to brainstorm, formulate arguments, or template ideas for assignments;
• Using AI to summarize or contextualize source materials;
• Submitting your own work for this class to an online learning support platform for iteration or improvement.

Excerpts from University of Minnesota. (2023). ChatGPT Syllabus statements.
https://provost.umn.edu/chatgpt-syllabus-statements