From Seeing to Signing Up: The Co-Creative Dance of Humans and AI in Cultivating Symbiotic Uniqueness for Enhanced User Engagement

Abstract

The advent of generative Artificial Intelligence (AI) marks a new era where users transition from passive consumers to active creators of digital art. This evolution prompts an inquiry into the distinction between generative AI and its traditional counterparts. We contend that the essence of this difference is captured by the concept of “Symbiotic Uniqueness,” which we introduce to underscore the dynamic interplay between human input and the AI’s ability to generate unique and random outputs. We argue that the two pillars of this concept are the effectiveness of the AI in meeting user intentions and the inherent randomness that fuels the creation of one-of-a-kind results. To empirically investigate the impact of these elements on user engagement, we designed a field experiment with a dual-axis framework: content visibility and loss framing. Our findings reveal that displaying AI-generated content upfront significantly boosts user registration, underscoring the allure of immediate evidence of the AI’s effectiveness. Moreover, a mixed strategy that combines both the revelation and concealment of content suggests potential advantages, slightly enhancing user registration rates. The application of loss framing, which plays on the randomness of AI-generated content, markedly amplified sign-up rates by tapping into the users’ fear of missing out on unique creations. Surprisingly, the combination of content visibility and loss framing appeared to dilute the efficacies, pointing to a possible substitution effect. This implies that the sense of urgency induced by loss framing may diminish when users’ expectations are already met by the visible outcomes, thereby reducing the influence of additional motivational prompts. Additionally, we examine scenarios requiring minimal user effort, demonstrating that both content visibility and loss framing are ineffective without active user participation in the co-creation process. This highlights the critical importance of co-creation in generating symbiotic uniqueness to foster user engagement. Additionally, we employed machine learning techniques for image analysis and discovered a positive relationship between the perceived quality of images and user registration rates. This correlation was particularly pronounced when coupled with loss framing, suggesting that the quality of AI-generated content is a critical factor in attracting users, especially when the potential for uniqueness is emphasized.

Keywords: Generative artificial intelligence (AI), symbiotic uniqueness, content visibility, loss aversion, user engagement