Artificial Intelligence (AI) Taskforce: AI Policy

This study conducts a comparative analysis of national policies on Generative AI across four countries: China, Japan, Mongolia, and the USA. Employing the Qualitative Comparative Analysis (QCA) method, it examines the responses of these nations to Generative AI in higher education settings, scrutinizing the diversity in their approaches within this group. While all four countries exhibit a positive attitude toward Generative AI in higher education, Japan and the USA prioritize a human-centered approach and provide direct guidance in teaching and learning. In contrast, China and Mongolia prioritize national security concerns, with their guidelines focusing more on the societal level rather than being specifically tailored to education.

There seems to be an emerging consensus among students to use the tool, and among educators to treat its use as plagiarism. Our findings offer insights that could guide policy discussions addressing the integration of artificial intelligence into educational frameworks.

In April 2023, WCET undertook a national survey to ascertain how and why postsecondary institutions are using Artificial Intelligence to support instruction and learning, what policies are in place, and what are the perceived barriers to, and benefits for, its use. This report highlights the survey results plus six in-depth interviews conducted post survey.

The Student Guide to Artificial Intelligence is an initiative of Elon University‘s Imagining the Digital Future Center, in partnership with the American Association of Colleges and Universities (AAC&U). It is a continuation of a 2023 global collaboration that established a statement of principles to guide development of AI policies and practices in higher education. The statement was released at the United Nations Internet Governance Forum in Kyoto, Japan, and was supported by more than 140 higher education organizations, administrators, researchers and faculty members from 48 countries.

Harvard Business School supports responsible experimentation with generative AI tools, but there are important considerations to keep in mind when using these tools, including information security and data privacy, compliance, copyright and academic integrity. Generative AI is a rapidly evolving technology and HBS’ policies may be updated from time to time. Students are expected to remain informed.

You have the discretion to define how, if, and when generative AI may be used in your courses. However, the Duke Community Standard has been updated to include the unauthorized use of generative AI as a form of cheating. Plus, the Office of Undergraduate Education offers a syllabus language menu that identifies considerations for writing an AI policy. (NetID login required).

This page outlines existing policies governing what you may and may not do when using generative artificial intelligence (AI) tools and services. These policies safeguard institutional data, which everyone in the university is legally and ethically obligated to protect. All university faculty, staff, students and affiliates must follow these policies.

To give sufficient space for instructors to explore uses of generative AI tools in their courses, and to set clear guidelines to students about what uses are and are not consistent with the Stanford Honor Code, the BCA has set forth the following policy guidance regarding generative AI in the context of coursework:

Penn embraces innovations like generative artificial intelligence (“AI”) models in teaching, learning, research, and the effective stewardship of Penn’s resources. To this end, this document provides guidelines for members of the Penn community who are using, or interested in using, AI in pursuit of Penn’s mission.

This page aims to provide you with a better understanding of generative AI and how to use it safely and responsibly at Iowa University. Included link to 'Guidelines for the secure and ethical use of Artificial Intelligence'

The following examples represent a range of options one could adapt or adopt, based on their teaching context and course’s student learning objectives.

Although the Artificial Intelligence (AI) landscape is evolving rapidly, one clear impact is that this technology is already being integrated into the academic lives of both students and faculty. As a result, all instructors should consider how they will provide clear guidelines concerning the use of generative AI in academic work for every class they teach.
Here are a few things to keep in mind when addressing AI and academic integrity in your course.

A resource to guide educators in reviewing/revising existing academic integrity policies to address threats from AI.

AI brings both opportunities and challenges in the context of academic integrity. While it can assist in identifying and preventing dishonest behaviors, its use also raises ethical questions, especially when it comes to privacy and surveillance. Moreover, it is important to remember that AI tools can support, but not replace, the work of teachers and administrators in promoting academic integrity. Ensuring honesty in academic work also relies heavily on creating a culture of integrity and setting clear expectations for ethical behavior.

There has been a significant increase in the popularity and availability of a variety of generative artificial intelligence (AI) tools, including ChatGPT, Sudowrite and others. These tools will help shape the future of work, research and technology — but when used in the wrong way, they can stand in conflict with academic integrity at Ohio State.

The following guidelines for developing an AI policy for your syllabus include examples of generative AI policies from instructors, universities, and centers of teaching and learning.

The following syllabus statements were developed by the Senate Committee on Educational Policy as a resource for faculty and instructors, with options ranging from “no restrictions” to “ChatGPT and other AI tools may not be used under any circumstances.” These statements may be adopted or adapted to reflect a given instructor's course learning objectives and instructional / assessment style.

There is likely no “one size fits all policy” for AI uses in higher education. Much like attendance/participation policies, AI policy statements will be determined by individual instructors, departments, and programs.

Examples for Open, Moderate and Strict AI Use guidelines

As an instructor, communicating decisions around the use of AI in your course is critical to the success of your students. A working group of faculty and instructional staff have crafted guidance for a syllabus statement. The sample statements range from forbidding the use of AI to examples of light, moderate, or heavy use of AI in a course. Whichever path you chose it is important to discuss the decision with students and post reminders on each assignment as reinforcement.