Downstream Consequences of Perceived Partner Responsiveness in Social Life

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.

Disagreements can polarize attitudes when they evoke defensiveness from the conversation partners. When a speaker talks, listeners often think about ways to counterargue. This process often fails to depolarize attitudes and might even backfire (i.e., the Boomerang effect). However, what happens in disagreements if one conversation partner genuinely listens to the other’s perspective? We hypothesized that when conversation partners convey high-quality listening—characterized by attention, understanding, and positive intentions—speakers will feel more socially comfortable and connected to them (i.e., positivity resonance) and reflect on their attitudes in a less defensive manner (i.e., have self-insight). We further hypothesized that this process reduces perceived polarization (perceived attitude change, perceived attitude similarity with the listener) and actual polarization (reduced attitude extremity). Four experiments manipulated poor, moderate, and high-quality listening using a video vignette (Study 1) and live interactions (Studies 2–4). The results consistently supported the research hypotheses and a serial mediation model in which listening influences depolarization through positivity resonance and nondefensive self-reflection. Most of the effects of the listening manipulation on perceived and actual depolarization generalized across indicators of attitude strength, specifically attitude certainty and attitude morality. These findings suggest that high-quality listening can be a valuable tool for bridging attitudinal and ideological divides.