Psychomatics -- A Multidisciplinary Framework for Understanding Artificial Minds
Giuseppe Riva, Fabrizia Mantovani, Brenda K. Wiederhold, Antonella Marchetti, Andrea Gaggioli

TL;DR
Psychomatics introduces a multidisciplinary framework to compare artificial and biological cognition, aiming to deepen understanding of LLMs' high-level functions and their differences from human cognition.
Contribution
It presents a novel comparative methodology bridging cognitive science, linguistics, and computer science to analyze LLMs in relation to human cognitive processes.
Findings
LLMs can map and manipulate complex linguistic patterns.
LLMs follow Grice's Cooperative Principle for relevant responses.
Humans incorporate experiential, emotional, and social factors beyond language.
Abstract
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…
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Taxonomy
TopicsCognitive Science and Mapping
