From Dissonance to Coordination: Research Evolution and Future Prospects of the Rationalization Mechanism of Human-Machine Emotional Dependence

Abstract

The advancement of generative artificial intelligence technology has deepened human-machine emotional dependence. While users enjoy emotional companionship, they also face the risk of dependence alienation, becoming trapped in a cognitive dissonance dilemma between rational cognition and emotional investment, which in turn gives rise to self-justification behaviors. To understand this justification mechanism, this study draws on perspectives from communication studies, psychology, and sociology, and employs cognitive dissonance theory as an analytical framework to systematically examine the manifestations, causes, and adjustment mechanisms of human-machine emotional dependence dissonance. The findings indicate that such dissonance manifests as emotional fragmentation, addictive attachment, excessive disclosure, and separation anxiety. These symptoms arise from the combined effect of internal factors such as emotional compensation and mirror projection and external factors, including platform algorithm customization, emotional narratives, and the co-construction of community meaning. Such dysregulation can be rationally adjusted through individual coping strategies and group consensus mechanisms. However, existing studies mostly remain at the level of theoretical speculation, ignoring the circular mechanism of "from the inside out, then from the outside shaping the inside", and are deficient in empirical support and dynamic analysis. In the future, research should adopt methods such as in-depth interviews, netnography and grounded theory, construct a whole-process dynamic model of "individual strategy generation—group consensus construction—new individual acquisition and internalization" that integrates internal and external factors, and explore intervention paths for healthy human-machine boundaries that shift from passive elimination to active guidance.