Social-based learning and leadership in school: conflict management training for holistic, relational conflict resolution

Although gratitude is typically conceptualized as a positive emotion, it may also induce socially oriented negative feelings, such as indebtedness and guilt. Given its mixed emotional experience, we argue that gratitude motivates people to improve themselves in important life domains. Two single-timepoint studies tested the immediate emotional and motivational effects of expressing gratitude. We recruited employees (n = 224) from French companies in Study 1 and students (n = 1026) from U.S. high schools in Study 2. Participants in both studies were randomly assigned to either write gratitude letters to benefactors or outline their weekly activities (control condition). Expressing gratitude led to mixed emotional experiences (e.g., greater elevation and indebtedness) for employees and students as compared with the control group. Students also felt more motivated and capable of improving themselves, as well as conveyed stronger intentions to muster effort towards self-improvement endeavors.

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.