This mini-workshop focuses on the limitations of generative artificial intelligence, with a particular emphasis on privacy, ethical considerations, academic integrity, and equity and bias concerns. Participants will be introduced to high-level issues in these areas, preparing them for further extensive training opportunities.
Workshop Outline:
- Academic Integrity
- The role of GenAI in maintaining or challenging academic standards
- How to evaluate student work in a GenAI era
- How students can demonstrate effectively where they have and haven't used GenAI
- How to use GenAI ethically and effectively in classwork
- Bias Concerns
- Examining how GenAI can perpetuate or mitigate biases
- Recommendations for how to prompt to reduce bias in output
- Responsibilities and Risks of Using GenAI
- GenAI is popping up everywhere (Google, Apple)
- Sensitive data types should only be used in U-M tools
- Privacy and Legal Concerns
- Understanding the privacy issues and legal implications associated with the use of GenAI
Audience: Staff, Instructors, and Students
Recommended Prerequisites:
A or B:
A. Introduction to GenAI: Unpacking Key Concepts (Mini Workshop)
B. Generative AI Basics (Full Workshop)