More than Merely Positive: The Immediate Affective and Motivational Consequences of Gratitude

The Listening Circle is a method for improving listening in organizations. It involves people sitting in a circle where only one talks at a time. Talking turns are signaled by a talking object. Although there are several reports regarding the effectiveness of the Listening Circle, most are based on case studies, or confounded with another intervention, and do not use theory to predict the listening-induced outcomes. We predicted that perceiving good listening decreases employees’ social anxiety, which allows them to engage in deeper introspection, as reflected by increased self-awareness. This increased self-awareness enables an acknowledgment of the pros and cons of various work-related attitudes and can lead to attitudes that are objectively more ambivalent and less extreme. Further, we hypothesized that experiencing good listening will enable speakers to accept their contradictions without the evaluative conflict usually associated with it (subjective-attitude ambivalence). In three quasi-experiments (Ns = 31, 66 and 83), we compared the effects of a Listening Circle workshop to a self-enhancement workshop (Studies 1 and 2), to a conflict management workshop (Study 2) and to employees who did not receive any training (Study 3), and found consistent support for the hypotheses. Our results suggest that the Listening Circle is an effective intervention that can benefit organizations.

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.