Do You Mind a ‘Maybe’ AI? Comparing User Responses to Algorithm-based and User-based AIGC Disclosure
Abstract
The adoption of AI-generated content (AIGC) is rapidly increasing for marketing as it enables companies to produce visually appealing content that resonates with their audience. However, concerns exist regarding its authenticity, potentially alienating audiences. Therefore, practitioners are enhancing AIGC transparency and disclosure, particularly through insights from digital platform algorithms and users. Prior research has primarily focused on interactive AI-enabled applications, while it remains unclear how users respond to non-interactive AIGC, especially in social media marketing contexts. Motivated by these concerns, this study investigates how algorithm-based and user-based AIGC disclosure influence users' social and commercial behaviors. We develop a research model based on the Stimulus-Organism-Response (SOR) framework and literature on AI disclosure, algorithm-based versus human-based judgments, and social media marketing. An experiment is designed to test the model.
Recommended Citation
Zhou, Ya; Luo, Cheng; and She, Junyi, "Do You Mind a ‘Maybe’ AI? Comparing User Responses to Algorithm-based and User-based AIGC Disclosure" (2025). SIGHCI 2024 Proceedings. 9.
https://aisel.aisnet.org/sighci2024/9
