Humanoid artificial consciousness designed with Large Language Model based on psychoanalysis and personality theory

Integrating psychoanalysis and the Myers-Briggs Type Indicator (MBTI) into artificial intelligence can produce models that simulate human-like consciousness, though differences between simulated personalities and consciousness types remain small. The authors developed three artificial consciousness modules (self-awareness, unconsciousness, preconsciousness) and sixteen personality characters based on MBTI types, each with attributes such as needs, status, and memories. They evaluated decision-making across ten situations using survey, ChatGPT classification, and qualitative review. Both quantitative and qualitative analyses indicated a high likelihood of well-simulated consciousness, but the response differences between characters and consciousnesses were not very significant. The work proposes that incorporating psychoanalysis and personality theory may lead to more intuitive and adaptable AI systems.

Study at a glance

Abstract

Human consciousness is still a concept hard to define with current scientific understanding. Although Large Language Models (LLMs) have recently demonstrated significant advancements across various domains including translation and summarization, human consciousness is not something to imitate with current upfront technology owing to so-called hallucination. This study, therefore, proposes a novel approach to address these challenges by integrating psychoanalysis and the Myers-Briggs Type Indicator (MBTI) into constructing consciousness and personality modules. We developed three artificial consciousnesses (self-awareness, unconsciousness, and preconsciousness) based on the principles of psychoanalysis. Additionally, we designed 16 characters with different personalities representing the sixteen MBTI types, with several attributes such as needs, status, and memories. To determine if our model's artificial consciousness exhibits human-like cognition, we created ten distinct situations considering seven attributes such as emotional understanding and logical thinking. The decision-making process of artificial consciousness and the final action were evaluated in three ways: survey evaluation, three-tier classification via ChatGPT, and qualitative review. Both quantitative and qualitative analyses indicated a high likelihood of well-simulated consciousness, although the difference in response between different characters and consciousnesses was not very significant. This implies that the developed models incorporating elements of psychoanalysis and personality theory can lead to building a more intuitive and adaptable AI system with humanoid consciousness. Therefore, this study contributes to opening up new avenues for improving AI interactions in complex cognitive contexts.