Hidden Labor behind the Hype: Understanding AI Side Hustles through Platform Narratives and Worker Practices

要旨

AI side hustles are increasingly promoted on social media as accessible, empowering, and profitable opportunities. This paper examines the gap between such platform narratives and workers' lived experiences through a mixed-method study of 7,938 RedNote posts and 16 semi-structured interviews. Our analysis identifies monetization typologies and rhetorical strategies that portray AI work as simple and rewarding, while interview data reveal hidden labor, unstable income, and the devaluation of human contributions. By juxtaposing platform narratives with lived experiences, we show how these narratives structurally foreground ease and reward while downplaying the precarity embedded in actual AI work. This study contributes a critical account of how AI side hustles are framed and experienced, and offers design implications for HCI: platforms should moderate promotional content and provide clearer risk communication, while designers of human–AI collaboration tools should highlight and value human input rather than allowing it to remain invisible.

著者
Xiaoyu YANG
The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China
zelin zhao
The Hong Kong University of Science and Technology (Guangzhou), guangzhou, China
Weipeng CHEN
The Hong Kong University of Science and Technology(Guangzhou) , Guangzhou, China
Corey Kewei Xu
The Hong Kong University of Science and Technology (Guangzhou), Guangzhou,Guangdong, China
Pan Hui
The Hong Kong University of Science and Technology, Hong Kong, China

会議: CHI 2026

ACM CHI Conference on Human Factors in Computing Systems

セッション: Labor, Equity and the Hidden Economy

P1 - Room 116
7 件の発表
2026-04-14 20:15:00
2026-04-14 21:45:00