Downstream Consequences of Perceived Partner Responsiveness in Social Life

Abstract Listening and perceived responsiveness evoke a sense of interpersonal connection that benefits individuals and groups and is relevant to almost every field in Psychology, Management, Education, Communication, and Health, to name a few. In this paper, we, researchers who have devoted their careers to studying listening (first author) and perceived responsiveness (second author), address the necessity of integrating the two constructs. Moreover, we offer several questions for future research that we believe are crucial to produce a more profound and comprehensive understanding of this important process. These research questions include empirical issues, cross-cultural and inter-racial interactions, age differences, the emergence of new technologies, and opportunities to bridge political, ethnic, and social divides. By highlighting the undeniable impact of listening and perceived responsiveness on interpersonal connection across diverse domains, we emphasize the need to integrate these constructs in future research. Our proposed set of eight pivotal research questions is intended as a starting point for gaining a deeper and more holistic understanding of this critical study area while building a strong empirical foundation for interventions. By addressing these questions, we can foster meaningful advances that have the potential to bridge gaps, improve relationships, and enhance the well-being of individuals and communities alike.

Conversational artificial intelligence (AI) can be harnessed to provide supportive parasocial interactions that rival or even exceed social support from human interactions. High-quality listening in human conversations fosters social connection that heals interpersonal wounds and lessens loneliness. While AI can furnish advice, listening involves the speakers’ perceptions of positive intention, a quality that AI can only simulate. Can such deep-seated support be provided by AI? This research examined two previously siloed areas of knowledge: the healing capabilities of human interpersonal listening, and the potential for AI to produce parasocial experiences of connection. Three experiments (N = 668) addressed this question through manipulating conversational AI listening to test effects on perceived listening, psychological needs, and state loneliness. We show that when prompted, AI could provide high-quality listening, characterized by careful attention and a positive environment for self-expression. More so, AI’s high-quality listening was perceived as better than participants’ average human interaction (Studies 1–3). Receiving high-quality listening predicted greater relatedness (Study 3) and autonomy (Studies 2 and 3) need satisfaction after participants discussed rejection (Study 2–3), loneliness (Study 3), and isolating attitudes (Study 3). Despite this, we did not observe downstream lessening of loneliness typically observed in human interactions, even for those who were high in trait loneliness (Study 3). These findings clearly contrast with research on human interactions and hint at the potential power, but also the limits, of AI in replicating supportive human interactions.