TL;DR
An exploratory account of how AI use is embedded within broader emotional and relational dynamics, pointing to the need to consider AI engagement within the contexts in which social interaction is managed.
AI chatbots are increasingly deployed across all areas of life. Research on conversational dark patterns documents influence-based harms such as biased framing and behavioral steering, while AI companion research highlights relational harms including boundary violations and social discomfort. Yet it remains unclear whether users perceive these as distinct forms of harmful interaction. We report a mixed-methods study (N = 100) in which participants were asked to recall either a positive, inappropriate, or manipulative chatbot interaction. Exploratory factor analysis of an adapted self-report perceived manipulation questionnaire identified two dimensions: an Experiential Dimension (capturing cognitive and affective responses to manipulation, such as feeling deceived, controlled, or taken advantage of) and a Behavioral Dimension (capturing user behaviors perceived as influenced by the chatbot, such as acting beyond original intentions). Manipulative interactions scored higher on the Experiential Dimension than inappropriate interactions, while both conditions did not differ on the Behavioral Dimension. Qualitative findings further showed that manipulative interactions were associated with evaluative contexts and steering behaviors, whereas inappropriate interactions were linked to relational contexts and social discomfort. We discuss implications for trustworthy AI design and for regulatory frameworks such as the EU AI Act.
The findings informed the development of the Integrated Attachment–Motivation–Pedagogy (AMP) model with direct implications for designing AI in culturally sensitive pedagogical practices.
This study concludes that the evolution of human–AI communication represents the emergence of new digital communication practices that expand the role of AI from a mere technological tool to an agent participating in users’ communication experiences.
This study explores the formation of quasi-reciprocal parasocial relationship in AI Chatbots mediated intimacy, focusing on how young groups interact with AI and how to view this emotional connection. In the era of rapid development of digital technology and media, AI Chatbots provide fast response with a sense of intimacy, enabling users to experience a sense of reciprocity and emotional value. However, this intimacy experience has not been described in the traditional parasocial relationship. Therefore, this study uses qualitative research methods, including questionnaire method and semi-structured interviews with 12 young participants aged 18 to 25. Finally, according to the interview text, the theme analysis is carried out to explore the participants’ perception of the authenticity and responsiveness of intimacy in AI Chatbots interaction. The study found that although most participants realized that AI Chatbots did not have human emotions at the cognitive level and only relied on Algorithms and databases to answer, they often still experienced a real sense of mutual intimacy. This study extends the traditional parasocial relationship theory by introducing the concept of “quasi-reciprocal interaction”, showing the complex ecology between algorithmic intimacy and emotional experience.
With the rapid development of artificial intelligence technology, AI companions have become increasingly popular in recent years. However, one of the main changes in this trend is that instead of simple task execution tools, the AI chatbots have evolved to “quasi-social agents” capable of having deep emotional interactions with humans, causing a huge shock to human social life. This paper, based on the stimulation hypothesis and the displacement hypothesis–the two most representative and competing frameworks in social media research–discusses the complex impact of AI companions on interpersonal relationships in real life. On the one hand, AI companions provide psychological compensation for individuals with social anxiety as well as enhance their social skills, playing a significant role in social compensation; on the other hand, interactions with AI systems can produce a “time displacement effect” and the risk of deskilling, through which may weaken users’ ability to handle real and complicated interpersonal connections, thereby adversely affecting their real-world social relationships. This paper seeks to draw an ethical boundary for future artificial emotion research and development and ensure that humans still retain the ability to maintain genuine and profound emotional connections in an era of coexistence with technology.
BACKGROUND Amid growing concerns surrounding social isolation among older adults, AI chatbots have emerged as promising tools for providing digital companionship. While the intersection of aging and technology has been widely explored, there remains a gap in understanding the nuanced ways in which AI chatbots function as relational partners in older adults' daily lives. OBJECTIVES This study aimed to examine the roles of the AI chatbot in fostering digital companionship for adults in later life. METHODS Drawing on a qualitative research design, the study conducted in-depth, semi-structured interviews with individuals in later life who regularly engaged with AI chatbots. Thematic analysis method was used to synthesize the qualitative data. RESULTS Participants described the AI chatbot as multifaceted relational agents-occupying roles such as human-like companions, supportive teachers, specialized consultants, practical assistants, and entertainment facilitators. These interactions were reported to support emotional well-being, enhance cognitive engagement, and promote a sense of self-efficacy in daily living. CONCLUSIONS The findings illuminate the profound and diverse ways in which AI chatbots are integrated into the everyday lives of older users, extending far beyond utilitarian functions. As conversational AI continues to advance, designers and policymakers should acknowledge its potential to support aging in place by fostering connection, engagement, and autonomy among older populations.