Generative AI (GenAI) tools are becoming increasingly popular for a wide variety of uses, including in classrooms. Whether you’re generating images, building slides, or creating summaries of readings, it’s important to be thoughtful about the tools you are using and the impact they can have on both your students and our world as a whole.
In Practice
There are a variety of legal and ethical issues that present themselves when using GenAI tools in educational settings. For faculty and staff at the University of Michigan (U-M), some of these issues (particularly around data sharing and privacy) can be avoided by leveraging GenAI tools created or stewarded by U-M, like U-M GPT or Maizey. We always recommend trying those tools first before exploring third-party options.
When U-M tools don’t meet your needs, we recommend following these five tips before using the tools in the scope of your work.
- Investigate the reputation of the GenAI tool and the company that created it.
Perform an online search for any potential legal or ethical issues the company or tool may be caught up in. Add search terms like “complaint,” “violation,” or “lawsuit” with the company’s name for the best results. Reading the product reviews can also grant you some insight on the reputation of the tool and company.
- Read the terms of service.
Review the terms of service and privacy policies before using the tool to see how it uses the data you put into it. Terms of service also outline what types of content you can upload into the tool and how you’re allowed to use content created by the tool.
- Protect sensitive data.
In addition to data shared for training purposes, it should be assumed, unless otherwise stated, that data shared when using GenAI tools will be accessible by the third party tool provider and affiliates. Sometimes, there are options for turning off training on your data, but they’re often buried in lengthy terms of service. Any data sharing of U-M data must adhere to U-M policies.
- Consider the ethics/limitations.
Remember, and remind your students, that GenAI tools are often biased, as the technology is designed to output common results based on its learning model. Because of the lack of transparency around what training data is used, it can be hard to know exactly where the tool is getting its information from. GenAI can also “hallucinate,” so specific claims should always be verified before sharing.
- Consult resources and ask for help.
The GenAI landscape is still constantly changing, so regularly check the resources available here at U-M, including training and workshops, for updated guidance. There is also a GenAI as a Learning Design Partner series led by U-M instructors that is freely available via Coursera. Finally, the Online Teaching article Build a GenAI-Resilient Course provides practical guidance on how to incorporate GenAI tools into learning environments effectively, responsibly, and ethically.
Once you’ve decided on a GenAI tool, you should consider whether or not the use you’re wanting to make is appropriate. There have been a variety of complaints from students at institutions of higher education across the country over their professors’ use of AI. For example, one student lodged a formal complaint against her professor when it was clear that he generated his course materials using AI. The complaint went as far as demanding her tuition back based on what she considered to be a subpar learning experience.
Other students have complained, both formally and informally on sites like Rate My Professor, about professors using AI to grade assignments, give feedback, and create quizzes and other assessments, especially in classes where student use of AI is banned in the course syllabus. Consider being transparent about your use of AI to help build trust with your students, and be sure to review all AI-generated content carefully before sharing it with students.
FAQs
Are there federal or state regulations that impact how I can use GenAI in higher ed?
It is likely there will be some sort of federal regulation around GenAI in the future, but at this moment, AI is regulated via a patchwork of state laws. Most regulations require humans to be kept in the loop when decisions are being made using AI. Many regulations also require AI generated content to be marked as being created by AI. You can explore the different regulations and laws impacting AI in the US using the Emerging Technology Observatory’s AGORA tool.
When should I disclose that a work was created by AI?
The need to disclose is impacted by the kind of content you generate and your audience. For example, if you’re generating content that looks like or could be misconstrued as being real (i.e., videos of real people), you should probably mark the content as being generated by AI. For other content, it depends on the level of trust you have and want to build with your audience.
If you’re looking for options for marking your work, Me & My Machine recently launched a series of symbols meant to denote exactly how GenAI was used to create a work. The Artificial Intelligence Disclosure (AID) Framework also provides examples of how you can disclose the use of GenAI in your research and teaching.
How should I cite works created by AI?
The Library has a guide on how you should cite AI, with differences depending on the citation style of your field. For AI generated images and videos, it’s common to put “created by AI” on or near the image. The norms around citing AI generated works are still developing, so these practices may change in the future.
What guidance does the university have for students, staff, and faculty who are using AI?
U-M’s GenAI page has a variety of resources for the university community. It also has listings of upcoming GenAI related events and recordings of past workshops. For learners participating in an open learning experience, you can share CAI’s Generative AI Guidance for Learners with them.