Academic Integrity and Generative AI
There are implications for academic integrity when considering Generative AI. Below are resources to help faculty/instructors and students understand how to properly use Generative AI for teaching and learning.
- Introduction to Academic Integrity (U-M Library page)
This page from the U-M Library provides an overview of academic integrity, academic ethics, and plagiarism and includes a discussion of ChatGPT.Citation help will be updated often as styles adopt new guides. - AI Detection Tools (UM-Flint)
This resource discusses AI detection tools. AI detection tools, designed to identify AI-generated content, currently face reliability challenges. These tools often struggle with distinguishing between AI-generated written text and high-quality student work, potentially leading to false positives that can unfairly penalize students. - IT User Advocate/ITS IA Academic Integrity Support Principles
The IT User Advocate works with the University of Michigan community to ensure that U-M information technology policies and guidelines are followed and responds to reports of abuse and misuse of U-M IT resources.- As necessary and appropriate, ITS Information Assurance (IA) supports U-M schools, colleges, and administrative units in academic misconduct investigations. IA staff adhere to the guiding principles outlined the ITS IA Academic Integrity Support Principles when engaging in the investigation of academic misconduct.
- Academic Integrity Resources for Students
The IT User Advocate works with the University of Michigan community to ensure that U-M information technology policies and guidelines are followed and responds to reports of abuse and misuse of U-M IT resources. - Academic Integrity Resources for Students (LSA Technology Services page)
The page provides a list of FAQs for students in regards to academic integrity.
