Although LLMs and other artificial intelligence systems demonstrate cognitive skills similar to humans, like concept learning and language acquisition, the way they process information fundamentally differs from biological cognition. To better understand these differences this paper introduces Psychomatics, a multidisciplinary framework bridging cognitive science, linguistics, and computer science. It aims to better understand the high-level functioning of LLMs, focusing specifically on how LLMs acquire, learn, remember, and use information to produce their outputs. To achieve this goal, Psychomatics will rely on a comparative methodology, starting from a theory-driven research question - is the process of language development and use different in humans and LLMs? - drawing parallels between LLMs and biological systems. Our analysis shows how LLMs can map and manipulate complex linguistic patterns in their training data. Moreover, LLMs can follow Grice's Cooperative Principle to provide relevant and informative responses. However, human cognition draws from multiple sources of meaning, including experiential, emotional, and imaginative facets, which transcend mere language processing and are rooted in our social and developmental trajectories. Moreover, current LLMs lack physical embodiment, reducing their ability to make sense of the intricate interplay between perception, action, and cognition that shapes human understanding and expression. Ultimately, Psychomatics holds the potential to yield transformative insights into the nature of language, cognition, and intelligence, both artificial and biological. Moreover, by drawing parallels between LLMs and human cognitive processes, Psychomatics can inform the development of more robust and human-like AI systems.

本文探讨了大型语言模型（LLMs）与人类认知之间的根本差异，提出心理体学这一多学科框架，以深入理解LLMs如何获取、学习和利用信息。研究发现，虽然LLMs能够遵循语言的复杂模式，但它们缺乏人类在感知、行动和认知中的身体体验，从而影响其对语言的全面理解和表达能力。此研究为人工智慧的发展提供了重要的启示，指向构建更具人性化特征的AI系统的可能性。

心理体学——理解人工心智的多学科框架