Information shared by humans vs Artificial Intelligence (AI) on social networking sites – The impact of message acceptance, perceived intrusiveness and relevance on user action
(A2023-114257)

AUTHORS

Hanne Knight, University of Plymouth; Stefan Hoffmann, Kiel University; Mohamed Haddoud, The British University in Dubai

ABSTRACT

The papers main aim is to establish whether the Computers Are Social Actors (CASA) paradigm (Reeves & Nass, 1996) can be applied to artificial intelligence (AI) on social networking sites (SNS). We are reviewing the impact of perceived message acceptance, relevance and perceived intrusiveness of information shared by artificial intelligence (AI) and humans on user action. We further show that age is a moderator that influences this relationship. Based on a sample size of 505 active social media users we have employed PLS-SEM. We have identified that the CASA paradigm strongly holds for AI on social networking sites as users do seem to be equally influenced by AI and humans to share information. We also found that older users perceive messages suggested by AI as more relevant and are more likely to share that information than those suggested by humans.