Combating Bias in AI-Generated Content
Alternative Title
Combating Bias in Artificial Intelligence (AI)-Generated Content
Contributor
University of Central Florida. Faculty Center for Teaching and Learning; University of Central Florida. Division of Digital Learning; Teaching and Learning with AI Conference (2025 : Orlando, Fla.)
Location
Universal Center
Start Date
29-5-2025 4:00 PM
End Date
29-5-2025 5:00 PM
Publisher
University of Central Florida Libraries
Keywords:
Bias detection; AI literacy; Educational strategies; Misinformation; Content evaluation
Subjects
Artificial intelligence--Social aspects; Artificial intelligence--Study and teaching; Artificial intelligence--Educational applications; Artificial intelligence--Moral and ethical aspects; Media literacy--Study and teaching
Description
As AI-generated content becomes more ubiquitous within and outside academic and professional settings, the need to have an information-literate, savvy population will be vital in combatting bias and misinformation in the coming years. In this poster presentation, we will show how to uncover different types of bias and prepare educators to assist their students in learning how to evaluate AIgenerated content for bias. Participants will walk away with strategies for how to handle and respond to bias in AI.
Language
eng
Type
Poster
Rights Statement
All Rights Reserved
Audience
Faculty; Students
Recommended Citation
Steele, Vanessa and Korslund, Stephanie, "Combating Bias in AI-Generated Content" (2025). Teaching and Learning with AI Conference Presentations. 157.
https://stars.library.ucf.edu/teachwithai/2025/thursday/157
Combating Bias in AI-Generated Content
Universal Center
As AI-generated content becomes more ubiquitous within and outside academic and professional settings, the need to have an information-literate, savvy population will be vital in combatting bias and misinformation in the coming years. In this poster presentation, we will show how to uncover different types of bias and prepare educators to assist their students in learning how to evaluate AIgenerated content for bias. Participants will walk away with strategies for how to handle and respond to bias in AI.