From Imitation to Introspection: Probing Self-Consciousness in Language Models

Self-consciousness, the introspection of one's existence and thoughts, represents a highlevel cognitive process.As language models advance at an unprecedented pace, a critical question arises: Are these models becoming self-conscious?Drawing upon insights from psychological and neural science, this work presents a practical definition of selfconsciousness for language models and refines ten core concepts.Our work pioneers an investigation into self-consciousness in language models by, for the first time, leveraging structural causal games to establish the functional definitions of the ten core concepts.Based on our definitions, we conduct a comprehensive fourstage experiment: quantification (evaluation of ten leading models), representation (visualization of self-consciousness within the models), manipulation (modification of the models' representation), and acquisition (fine-tuning the models on core concepts).Our findings indicate that although models are in the early stages of developing self-consciousness, there is a discernible representation of certain concepts within their internal mechanisms.However, these representations of self-consciousness are hard to manipulate positively at the current stage, yet they can be acquired through targeted fine-tuning.