This is a reading list of essays, resources, and full-hatched policies at other institutions for AI and ethics. It is meant to provide a background for those interested in developing an AI policy for their courses or for their institution. I think it is important to understand the risks of using AI as well as the potential benefits. By understanding the two together, I think we will see that developing ways to mitigate the dangers is absolutely critical. The purpose of this list is strictly utilitarian and not exhaustively academic. I am interested in striking a balance between student care and innovation. I think the readings below reflect that balance. I have written more on the local college policy issues as well has a number of posts on the ethical issues an AI but also with education tech in general elsewhere on this blog.
AI Ethics Guidelines Global Inventory. (2021). Algorithm Watch.
This is useful for looking at issues with AI from around the world. Looking at other policies allows us to view how other organizations and governments have sought to solve problems: problems we may not have yet considered.
Artificial Intelligence Policies: Guidelines and Considerations. (2024). Learning Innovation and Lifetime Education. Duke University.
I included this as a mature, thought-out plan that seems to account for a number of approaches that faculty might need depending on what and how they are teaching.
Atwell, Sue. (2024). From Principles to Practice: Taking a whole institution approach to developing your Artificial Intelligence Operational Plan. National Center for AI.
This article is useful for mapping out how to bring in all of the users and stakeholders into the planning process. Gathering the local voices is important for cultivating buy-in to any policy. It is also an inclusive, shared-governance way of helping faculty and staff evolve their thinking about new technology.
Antoniak, Maria. (2023). Using Large Language Models With Care: How to be mindful of current risks when using chatbots and writing assistants. Medium.
The list of ten risks are useful in discussions about why a policy on AI is needed. This is a good introductory essay on ethical issues around AI.
Bender, Emily M. et al. (2021). On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? ACM Digital Library. Association for Computing Machinery.
This is a thorough and close look at the ethical issues around AI and what to do about it. This is a seminal paper on the topic and is a “must read.”
Brandon, Esther et al. (2023). Cross-Campus Approaches to Building a Generative AI Policy. Educause Review.
Again, leadership in developing policies should always ask “who have we included in the policy making procedures?” It is too easy to exclude voices in the name of expediancy.
Cardona, Miguel A. et al. (2023). Artificial Intelligence and the Future of Teaching and Learning. Office of Education Technology. Department of Education.
This is a good 300 ft view of AI in education and includes a balance of opportunities, challenges, and risks.
Eaton, Lance. (2024). Syllabi Policies for AI Generative Tools. Google Form.
A Google form and spreadsheet of hundreds of examples of course policies on AI. “This resource is created…for the purposes of sharing and helping other instructors see the range of policies available by other educators to help in the development of their own for navigating AI-Generative Tools…”
Ethical AI for Teaching and Learning. (nd). Center for Teaching and Innovation. Cornell University.
A thoughtful assessment of the issues: “Building literacy in Generative AI includes addressing ethics, privacy, and equity with intention. There are many open questions, including legal questions, regarding the ethical design, development, use, and evaluation of generative AI in teaching and learning. While generative AI may potentially be powerfully useful, concerns and sensitivities surround a number of key issues…”
Ethics guidelines for trustworthy AI. (2019). European Commission.
Again, looking at AI and ethics through the lens of other cultures than the U.S.A can help us be aware of issues that our own biases may not allow us to see. “The Guidelines put forward a set of 7 key requirements that AI systems should meet in order to be deemed trustworthy.”
Gašević, D., Siemens, G., & Sadiq, S. (2023). Empowering learners for the age of artificial intelligence. Computers & Education: Artificial Intelligence, 4, 100130.
This paper includes a discussion about how generative AI’s weaknesses can be turned into possible strengths given the proper training of teachers and students in its use.
K-12 Generative AI Readiness Checklist. (2023). The Council of the Great City Schools.
This is an important document because it shows the stark difference between how K-12 adopts technology v. Higher Ed. This represents a thoughtful investigation and method in how to gather the voices and concerns around the adoption of new technology. We need a version of this for colleges.
U.S. University Policies on ChatGPT. (2023). Scribbr. Google Spreadsheet.Scribbr-
We have the Eaton spreadsheet (above) for class policies; this is a useful collection of college policies. “This spreadsheet details the AI policies of 100 American universities. It is current through June 2023 and updated as circumstances change.”
If you have a resource that you think we should be looking at in addition to these, feel free to add it by commenting below or dropping me a line. Thanks!