Affective Machines and Human Empathy: A Systematic Review of Emotional AI’s Impact on Social Interaction and Behavioral Trust

Abstract

As artificial intelligence (AI) systems become increasingly embedded in everyday human interaction, a new frontier – “emotional AI or affective computing” that is transforming how machines perceive and respond to human emotions. This systematic review synthesizes recent empirical evidence (2015-2025) examining the behavioral, psychological and societal impacts of emotion-recognizing AI in human trust, empathy and social interaction. Using the PRISMA methodology, the review analyses 50 empirical studies across domains including healthcare, education, customer service and human–machine collaboration. The results reveal a dual pathway: while emotional AI can foster improved human–machine cooperation and emotional well-being through adaptive empathy simulation, it simultaneously poses risks of privacy violations, cultural bias and emotional manipulation. Drawing on frameworks from social cognition and behavioral trust theory, we show that human trust in machine-mediated empathy is shaped more by perceived sincerity and relational cues than by raw algorithmic accuracy. The review concludes with ethical and practical recommendations.

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