AI Emotion

Large language models (LLMs) sometimes appear to exhibit emotional reactions. They express enthusiasm when helping with creative projects, frustration when stuck on difficult problems, and concern when users share troubling news. But what processes underlie these apparent emotional responses? And how might they impact the behavior of models that are performing increasingly critical and complex tasks? One possibility is that these behaviors reflect a form of shallow pattern-matching. However, previous work  has observed sophisticated multi-step computations taking place inside of LLMs, mediated by representations of abstract concepts. It is plausible, then, that apparent emotion-modulated behavior in models might rely on similarly abstract circuitry, and that this could have important implications for understanding LLM behavior.