Finding love in algorithms: deciphering the emotional contexts of close encounters with AI chatbots

Main People Involved:

Renwen Zhang, Department of Communications and New Media, National University of Singapore

A short summary of the project’s aims:

AI chatbots are permeating the socio-emotional realms of human life, presenting both benefits and challenges to interpersonal dynamics and well-being. Despite burgeoning interest in human–AI relationships, the conversational and emotional nuances of real-world, in situ human–AI social interactions remain underexplored. Through computational analysis of a multimodal dataset with over 35,000 screenshots and posts from r/replika, we identified seven prevalent types of human–AI social interactions: intimate behavior, mundane interaction, self-disclosure, play and fantasy, customization, transgression, and communication breakdown, and examined their associations with six basic human emotions. Our findings suggest the paradox of emotional connection with AI, indicated by the bittersweet emotion in intimate encounters with AI chatbots, and the elevated fear in uncanny valley moments when AI exhibits semblances of mind in deep self-disclosure. Customization characterizes the distinctiveness of AI companionship, positively elevating user experiences, whereas transgression and communication breakdown elicit fear or sadness.

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