Attitudes

Exploring the connecting potential of AI: Integrating human interpersonal listening and parasocial support into human-computer interactions

Abstract

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.
Guy Itzchakov, Netta Weinstein
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Listening
We examined how the experience of high-quality listening (attentive, empathic, and nonjudgmental) impacts speakers’ basic psychological needs and state self-esteem when discussing the difficult topic of a prejudiced attitude. Specifically, we hypothesized that when speakers discuss a prejudiced attitude with high-quality listeners, they experience higher autonomy, relatedness, and self-esteem than speakers who share their prejudiced attitudes while experiencing moderate listening. We predicted that autonomy needs satisfaction would mediate the effect of listening on speakers’ self-esteem even when relatedness, a well-documented predictor of self-esteem, is controlled for in mediation models. Two experiments that manipulated listening through in-person interactions with high-quality or moderate listeners supported these hypotheses. Theoretical and practical implications are discussed, with a focus on the role of experiencing high-quality listening for speakers’ state self-esteem during difficult conversations.
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Guy Itzchakov, Avraham N. Kluger
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Listening
An employee’s listening ability has implications for the effectiveness of the work team, the organization, and for the employee’s own success. Estimates of the frequency of listening suggest that workers spend about 30% of their communication time listening. However, the ability to listen might be even more important to managers, as empirical evidence suggest that they spent more than 60% of their time listening. Hence, the success of both the employee and the manager in communication, and thus in the organization, rests in part on possessing good listening abilities.
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