This workshop focuses on the limitations of generative artificial intelligence, with a particular emphasis on ethical considerations, academic integrity, equity, and bias concerns. Participants will be introduced to high-level issues in these areas, preparing them for further extensive training opportunities.
Critical Challenges in GenAI: Academic Integrity, Bias, Responsibilities, and Risks
ITS Instructional Support Workshop
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
Recommended Prerequisites
Introduction to GenAI: Unpacking Key Concepts (Mini Workshop)
-- OR --
Generative AI Basics (Full Workshop)
Topics
Audience
- Instructors
- Staff
- Students
Level
- Beginner/Core