Adoption
Control: attitude toward AI
The contributions of this study are as follows:
Investigated all stages of the complete process of the influences of AI-suggested content, from the factors impacting the adoption of AI-suggested content to the subsequent effects of the adopted AI-suggested content.
First explored the impact of AI-suggested content on attitudes and opinions, along with the underlying mechanisms.
First interrogated the determinants of AI-suggested content adoption under a solid theoretical framework.
With the rapid development of language models and AI content generators such as ChatGPT, AI content generators have become a common tool used by over 180 million monthly users to seek information (DemandSage, Medium, 2024). It is foreseeable that AI-generated content or AI generators will even be embedded in social media platforms to enhance users' experience. Existing literature in this area primarily focuses on the factors affecting the adoption of AI-generated content, particularly in terms of smart replies in work or life settings, as well as the influence of positivity bias in AI-generated replies (Hohenstein & Jung, 2018; Mieczkowski et al., 2021; Wenker, 2023). However, what variables will impact the adoption of AI-generated content when it comes to scientific matters or social events? Furthermore, what influences do AI-suggested content have on people in the context of social media? These are the research questions that this study seeks to address.
RQ3: Any interative influences?
Theory/Mechanism: Self-concept change (public commitment and internalization)
H8: Ephemerality increases AI-suggested content internalization.
H7: Identity-revealed social media platform leads to AI-suggested content internalization.
H6: The number of likes to the post positively affect AI-suggested content internalization.
RQ2: How issue involvement, cognitive overlaod, and time pressure influence AI-content adoption interactively?
Adopted
Visible number of likes vs. no such a feature
RQ1: How issue involvement and time pressure influence AI-content adoption interactively?
H5: Time pressure and cognitive overload postively affect AI-suggested content adoption.
H4: Cognitive overload and issue involvement negatively impact AI-suggested content adoption.
H2: Cognitive overload result in higher chance of AI-suggested content adoption.
H3: Time pressure increases the likelihood of adopting AI-suggested content.
H1: Higher issue involvement lowers the likelihood of AI-suggested content adoption.