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.
The effects of listening on speaker and listener while talking about character strengths: an open science school-wide collaboration
Tia Moin, Netta Weinstein, Guy Itzchakov, Amanda Branson, Beth Law, Lydia Yee, Emma Pape, Rebecca Y. M. Cheung, Anthony Haffey, Bhismadev Chakrabarti and Philip Beaman
Listening
Listening is understood to be a foundational element in
practices that rely on effective conversations, but there is
a gap in our understanding of what the effects of highquality
listening are on both the speaker and listener.
This registered report addressed this gap by training one
group of participants to listen well as speakers discuss
their character strengths, allowing us to isolate the role
relational listening plays in strengths-based conversations.
Participants were paired and randomly assigned to a highquality
listening (experimental) or moderate-quality listening
(comparison) condition manipulated through a validated
video-based training. High-quality listening predicted a
more constructive relational experience; specifically, positivity
resonance. Intrapersonal experiences (perceived authenticity
and state anxiety) were not affected. Those who engaged
in high-quality listening expressed a behavioural intention
to continue listening, but condition did not predict a
behavioural intention for speakers to continue applying
character strengths. This is the first evidence of positivity
resonance as a shared outcome between both a speaker and listener when the listener conveys high-quality (as opposed to ‘everyday’) listening. These early
findings merit further study with stronger listening manipulations to explore the potential role
of listening within interpersonal communication, and inform the applied psychological sciences
(counselling, psychotherapy, coaching, organizational, education).
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An Examination of the Moderating Effect of Core Self-Evaluations and the Mediating Effect of Self-Set Goals on the Primed Goal-Task Performance Relationship
Guy Itzchakov, Gary P. Latham
Goal Setting
An understudied issue in the goal priming literature is why the same prime can provoke different responses in different people. The current research sheds light on this issue by investigating whether an individual difference variable, core self-evaluations (CSE), accounts for different responses from the same prime. Based on the findings of experiments showing that individuals with high CSE have higher performance after consciously setting a task-related goal than individuals with lower CSE, two hypotheses were tested: (1) Individuals who score high on CSE perform better following a subconsciously primed goal for achievement than do individuals who score low on CSE, and (2) this effect is mediated by a self-set goal. Two laboratory experiments (n = 207, 191) and one field experiment (n = 62) provided support for the hypotheses. These findings suggest that personality variables such as the CSE can provide an explanation for the “many effects of the one prime problem”.
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