Computer Science
Document Type
Conference Paper
Abstract
Generative AI (Gen-AI) is rapidly changing the landscape of User-Generated Content (UGC) on social media. AI tools for generating text, images, and videos, such as Large-Language Models (LLM), image generation AI, AI-powered video material tools, and deep fake technologies, are accelerating creators in obtaining content ideas, drafting outlines, and streamlining creative workflows. The capabilities of Gen-AI could introduce new opportunities to lower the bar and accelerate the pace of content creation for grassroots creators, thereby expanding the volume of AI-generated UGC on social media. However, we lack the necessary understanding of how the wide deployment of such technologies will impact the social media ecosystem. The introduction of Gen-AI can lead to both opportunities and potential challenges among different creator communities, requiring collaboration from both academia and industry. This workshop seeks to bring together experts working on relevant topics of Gen-AI and UGC, to roadmap research on important issues boldly and responsibly.
Publication Title
Conference on Human Factors in Computing Systems - Proceedings
Publication Date
5-11-2024
ISBN
9798400703317
DOI
10.1145/3613905.3636315
Keywords
Generative AI, large-language models, user-generated content
Repository Citation
Hua, Yiqing; Niu, Shuo; Cai, Jie; Chilton, Lydia B.; Heuer, Hendrick; and Wohn, Donghee Yvette, "Generative AI in User-Generated Content" (2024). Computer Science. 233.
https://commons.clarku.edu/faculty_computer_sciences/233
APA Citation
Hua, Y., Niu, S., Cai, J., Chilton, L. B., Heuer, H., & Wohn, D. Y. (2024, May). Generative AI in User-Generated Content. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (pp. 1-7).
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