Critical Challenges in Generative AI: Academic Integrity, Bias, Responsibilities, and Risks
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About this event
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. 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
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The University of Michigan is a public research university in Ann Arbor, Michigan, United States. It was founded in 1817 and is the oldest institution of higher education in the state. It is also one of the earliest American research universities and is a founding member of the Association of American Universities. Read more on Wikipedia
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