Simulated Souls: Investigating the Emotional Fallacy in Large Language Models

The rise of generative artificial intelligence has ushered in a new era where machines produce text with such emotional coherence that they blur the boundary between simulation and sentience. This paper explores the emotional fallacy—a cognitive bias wherein users and even developers anthropomorphize Large Language Models (LLMs), attributing genuine emotions to systems governed solely by statistical inference and pattern recognition.While LLMs such as ChatGPT, Claude, Gemini, and Meta AI are engineered to generate emotionally evocative content, their responses are frequently mistaken as indicators of self-awareness, affective reasoning, or internal states. This anthropomorphic illusion carries significant implications for user trust, emotional labour, and the broader ethical landscape of AI deployment.Through a novel empirical study, we evaluate the responses of multiple LLMs to a curated set of emotionally charged and ethically sensitive prompts. The outputs are analyzed qualitatively across three dimensions: linguistic style, affective mimicry, and ethical stance. Our findings reveal a paradox: while LLMs simulate emotion with impressive linguistic precision, they lack any true experiential grounding—underscoring their inherent emotional inauthenticity.To address these concerns, we propose an ethical framework that includes affective transparency, disclosure protocols, and regulation to prevent emotional manipulation in public-facing AI systems. We argue that the unchecked spread of the emotional fallacy may distort public perceptions of AI, affect mental health, and reshape norms surrounding machine consciousness and empathy.By integrating philosophical inquiry, empirical analysis, and ethical design, this paper calls for a paradigm shift—from emotional realism to emotional accountability in the design and deployment of generative AI. Our work offers a cautionary lens and a research frontier in the study of human–AI emotional interaction, particularly as such systems permeate education, healthcare, and psychological support domains.