Can AI Understand Loneliness? Socio-Emotional Affordances of AEI Chatbots, Perceived Emotional Authenticity, and Loneliness Reduction

Loneliness is among the most pressing public health challenges of the 21st century, and emotionally intelligent chatbots are increasingly promoted as a scalable, non-clinical source of socio-emotional support. Information Systems research has yet to explain how the relational capabilities of such artifacts translate into well-being outcomes. Drawing on affordance theory and the Computers Are Social Actors paradigm, we theorize two socio-emotional affordances of artificial emotional intelligence (AEI) chatbots, adaptive empathy and scripted empathy, and propose perceived emotional authenticity (PEA) as the mechanism through which these affordances reduce emotional and social loneliness, with trust in the chatbot as a boundary condition. We propose a six-week between-subjects experiment with pre- and post-interaction survey measurements. The study extends affordance theory to the emotional domain and contributes a validated PEA instrument for IS research.