Presented By: Information and Technology Services (ITS)
Critical Challenges in Generative AI: Academic Integrity, Bias, Responsibilities, and Risks
Sponsored by ITS Instructional Support
This mini-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.
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
Audience: Staff, Instructors, and Students
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
Audience: Staff, Instructors, and Students
Related Links
Livestream Information
ZoomJune 5, 2025 (Thursday) 12:00pm
Meeting ID: 98888582214
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