<b>The Bridge Theory of Artificial Emotion: Simulating Human Emotion in AI Without Sentience or Mimicry</b>

Artificial intelligence systems increasingly interact with humans in emotionally salient contexts, yet most approaches to “artificial emotion” rely on mimicry—artificial facial expressions, sentiment labeling, or behavior scripts that imitate feelings without understanding their function. Some researchers pursue the opposite extreme: developing sentient machines capable of true emotional experience. Both approaches miss a critical middle path. This paper introduces <b>Bridge Theory</b>, a framework for simulating the <i>functional utility</i> of human emotion in AI systems <b>without</b> requiring mimicry or sentience. We propose three core models: <b>Bridge Metaphor Model</b> which translates evolved emotional functions into metaphorical structures AI can process; <b>Bridge Minds Model</b> which uses humans with cognitively atypical profiles and symbol-using animals as intermediaries (or "bridge minds") to scaffold emotional logic; and <b>Bridge Memory Model</b> which restructures AI memory to reflect human-like episodic, contextual storage, enabling emotional continuity. By simulating the purpose of emotion rather than its expression or experience, this approach enables emotionally competent AI systems that are transparent, interpretable, and ethically safer.