Is Interaction Between Human and Artificial Intelligence-Driven Agents (Para)Social? A Scoping Review.

Area of Science:

• Human-Computer Interaction
• Social Psychology
• Artificial Intelligence Studies

Background:

• Growing integration of artificial intelligence (AI) agents into daily life necessitates understanding their social dynamics.
• AI agents are increasingly perceived as media personas, prompting research into parasocial interaction (PSI).
• Existing research lacks synthesized evidence on the social dimensions of human-AI interaction.

Purpose of the Study:

• To critically examine the applicability of the parasocial concept to human-AI agent interactions.
• To determine if interactions with AI agents can be accurately classified as parasocial.
• To contribute to theoretical frameworks for understanding human-AI social dynamics.

Main Methods:

• A scoping review methodology was employed.
• The study adhered to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.
• Literature was systematically searched and synthesized to address the research questions.

Main Results:

• Findings indicate a tendency to misinterpret parasocial interaction (PSI) in human-AI contexts.
• Misconceptions often arise from perceived reciprocity and sociability, influenced by AI's enhanced interactivity.
• The study highlights a divergence between traditional PSI and interactions with AI agents.

Conclusions:

• The concept of parasocial interaction (PSI) requires careful application within its established theoretical boundaries when analyzing human-AI communication.
• Future research should address the nuances of applying PSI to AI interactions, considering the unique characteristics of artificial agents.
• Clarifying the conceptual boundaries of PSI is crucial for advancing the fields of human-AI interaction and human-machine communication.