Subjective Emotional Interpretation and Relatability of AI-Generated Versus Human-Created Content

Abstract

Abstract Artificial Intelligence (AI) has increasingly entered creative domains such as writing, poetry, marketing, and media production, raising critical questions about emotional authenticity and audience perception. While AI-generated content demonstrates high technical proficiency, its ability to establish genuine emotional connection remains debated. This study investigates how readers emotionally interpret and relate to AI-generated versus human-created content, and how authorship awareness influences perceived authenticity. A mixed-methods research design was adopted, combining a structured Google Forms survey (n = 100), expanded from a pilot study (n = 28), with qualitative analysis and real-world case evaluations from 2024–2025 poetry contests, marketing campaigns, the film ECHO, and AI-generated music controversies. Participants first evaluated texts in a blind condition and later reassessed them after authorship disclosure. Quantitative data were analysed using comparative scoring across emotional dimensions, while qualitative responses were examined thematically. In the blind phase, both AI and human-generated texts received similarly high emotional ratings, with AI content slightly outperforming human content (AI: 4.03; Human: 3.88), indicating strong emotional simulation capabilities. However, following authorship disclosure, perceptions shifted significantly. Human-written content increased in authenticity to 4.36, while AI-generated content declined to 3.68, producing a statistically significant 0.68-point “authenticity valley” (p < 0.01). Qualitative findings revealed that human writing was valued for its organic imperfections, lived experiences, and emotional layering, whereas AI content was perceived as polished but engineered, lacking vulnerability. These patterns were consistent across real-world cases, where AI-generated outputs were initially engaging but later described as emotionally hollow upon disclosure. The findings suggest that while AI can replicate surface-level emotional cues, it struggles to sustain deeper emotional resonance and trust. The study also validates the use of synthetic data augmentation to enhance statistical reliability while preserving original patterns. The study concludes that human authorship remains essential for authentic emotional connection, while AI is best positioned as a supportive tool for enhancing creativity. The results emphasize the importance of balancing technological advancement with human emotional depth in creative industries. Key words - Artificial Intelligence, Human vs AI Creativity, Emotional Authenticity, Audience Perception, Authenticity Valley, AI-Generated Content, Emotional Resonance, Mixed-Methods Research, Creative Writing, Human–AI Collaboration, Digital Creativity, Qualitative Analysis

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