Can AI truly understand us? New research suggests Large Language Models (LLMs) might view humans as more rational than we really are. This fascinating study reveals how LLMs, like GPT-4, struggle to predict human decisions in simple gambling scenarios. While LLMs often choose the most statistically advantageous option, humans are more influenced by emotions, biases, and gut feelings. This difference highlights a key challenge in AI development: aligning LLMs with human behavior. Although LLMs excel at logic, they sometimes miss the nuances of human decision-making. Interestingly, the study also found that humans tend to overestimate the rationality of others. This shared tendency between LLMs and humans could explain why we perceive LLM-generated text as human-like, even when it deviates from actual human behavior. This discovery has important implications for using LLMs to simulate human behavior in research, marketing, and social interactions. If LLMs assume perfect rationality, their simulated responses might not accurately reflect how real people would act. Future research could explore ways to train LLMs to better capture the emotional and psychological factors that drive human decisions, bridging the gap between artificial intelligence and human behavior.