About the Session
Students’ informed consent is often not considered when talking about the use of AI in teaching.
Educators can be quick to initiate conversations about the benefits of new AI tools, however, when those tools have serious psychological, physical, and social impacts, everyone involved should understand the risks and give informed consent. If the student and instructor decide the risks are worth the proposed benefit, then the next step in any research protocol is to mitigate potential harm as much as possible while still retaining proposed benefit.
In this workshop we will look at what information is necessary for informed consent if you’re integrating AI into assignments or discussing this with students and colleagues. Bring any assignment or application for which you would like to develop informed consent, and we will write example statements and brainstorm harm reduction strategies.
By the end of this workshop, participants will:
- Gain a framework for assessing the risk-benefit ratio when considering implementing “AI” in educational contexts
- Have an improved understanding of information required for informed consent regarding “AI” use
- Reflect on harm reduction strategies for “AI” use in educational contexts
References
Bo, Jessica Y., Majeed Kazemitabaar, Mengqing Deng, Michael Inzlicht, and Ashton Anderson (2026). Invisible Saboteurs: Sycophantic LLMs Mislead Novices in Problem-Solving Tasks. Ithaca: Cornell University Library, arXiv.org. https://go.exlibris.link/7376KyGx
Abdulhai, Marwa, Isadora White, Yanming Wan, Ibrahim Qureshi, Joel Leibo, Max Kleiman-Weiner, and Natasha Jaques (2026). How LLMs Distort our Written Language. Ithaca: Cornell University Library, arXiv.org.
Budzyń K, Romańczyk M, Kitala D et al. (2025). Endoscopist deskilling risk after exposure to artificial intelligence in colonoscopy: a multicentre, observational study. The Lancet Gastroenterology & Hepatology, 10, 896-903. https://doi.org/10.1016/S2468-1253(25)00133-5