关键词: AI生成短视频, AI披露详尽程度, 参与意愿, 感知内容质量, 感知来源可信度

Abstract:

[Purpose/Significance] Generative AI has revitalized short video creation but blurred the line between authentic and false information. AI disclosure - informing the public of AI involvement via labels - has become a normative tool to mitigate ethical risks. However, current disclosure practices remain overly simplistic and fail to meet users' needs for transparency. How detailed disclosure labels should be designed and how they affect user cognition and behavior is still unclear. Previous studies have largely focused on the impact of whether AI is disclosed or not. Drawing on transparency design, this study further investigates the level of detail in AI disclosure. Theoretically, it confirms the importance of detailed disclosure, reveals the underlying mechanism via the heuristic-systematic model (HSM), and identifies the boundary condition of video type. Practically, it provides guidance for creators in designing disclosure labels and for platforms in effective regulation. [Method/Process] To examine the impact of AI disclosure detail on users' engagement intention, the study adopted an online experiment employing a 2×2 between-subjects experimental design to compare the effects of two types of disclosure labels across different video types. Detailed AI disclosure labels provided information regarding the type of AI technology used, its purpose, and its limitations, whereas simple AI disclosure labels merely indicated the involvement of AI technology. Additionally, the study distinguished between utilitarian and hedonic short videos for further investigation. Participants were recruited through an online experimental platform and randomly assigned to different experimental conditions. In each condition, participants were asked to view AI-generated short videos accompanied by the corresponding disclosure labels and completed a standardized questionnaire. Specifically, the questionnaire assessed participants' perceived source credibility, perceived content quality, and engagement intention, with measurement instruments adapted from validated scales. [Results/Conclusions] The study found that the level of AI disclosure detail has a significant positive effect on users' engagement intention with AI-generated short videos. Detailed AI disclosure enhances perceived content quality through the systematic route, thereby positively influencing users' engagement intention. However, the mediating role of perceived source credibility as a heuristic cue was not significant. Furthermore, this effect showed no significant difference across different types of short videos. The study provides valuable insights into the mechanisms of AI transparency. Future research can consider other dimensions of effective disclosure, explore the effects of dynamic prompts, expand sample coverage to enhance the applicability of conclusions, and conduct empirical tests incorporating actual behavioral data, thereby deepening the understanding of the mechanisms underlying AI disclosure effects.

Key words: AI-generated short videos, level of AI disclosure detail, engagement intention, perceived content quality, perceived source credibility