<![CDATA[The development of artificial intelligence (AI), particularly ChatGPT, demonstrates the ability to generate responses that resemble human emotional understanding and raises questions about the integration of consciousness, emotions, and algorithms in the context of singularity. This study aims to analyze how AI builds the illusion of consciousness and emotional closeness through computational mechanisms and its impact on human-AI interactions across various sectors. The method used is a structured literature review, examining academic journals, official reports, and the latest technical documentation classified by technical domain, including model architecture, emotion simulation, ethical implications, and publication year to assess its developmental dynamics. The results show that ChatGPT is capable of simulating empathy through affective computing and language prediction patterns, but it does not possess subjective emotional experiences like humans. This illusion of emotional closeness has proven beneficial in enhancing the effectiveness of interactions in education, public services, and healthcare, although it also poses risks such as emotional manipulation, data bias, and unrealistic empathy standards. The discussion emphasizes that the term “empathy” in AI should be understood technically as a data-driven adaptive response, not authentic emotional experience, and thus must be distinguished from human empathy. Critical analysis also reveals contradictions between AI's effectiveness in mimicking human behavior and its limitations in achieving genuine emotional connection. The discussion emphasizes that the term “empathy” in AI should be understood technically as a data-driven adaptive response, not an authentic emotional experience, and therefore needs to be distinguished from human empathy. Critical analysis also reveals a contradiction between AI's effectiveness in mimicking emotional behavior and its limitations in understanding meaning and consciousness at a deeper level. Therefore, this research contributes to the field of Computer Science by presenting a conceptual synthesis that clarifies both the limitations and potential of AI, while offering a foundation for designing more ethical interaction systems and developing risk assessment models in vulnerable sectors.]]>
