A common objection to artificial consciousness—that a simulated brain is no more conscious than simulated water is wet—is addressed from the perspective of Intrinsic Computational Functionalism. Consciousness depends not on external descriptions but on computational structures a system physically realizes through its own causal-dynamical organization. Previous work defined functional states by input-output roles under a fixed interface, but this is incomplete because it makes lookup tables and unfolded systems canonically equivalent.
Consciousness is a defining feature of the human mind, and as large language models (LLMs) advance, questions about their potential for consciousness become pressing. This paper clarifies commonly confused terms like LLM consciousness and awareness, then systematically reviews existing theoretical and empirical research on the topic. It also highlights potential frontier risks that conscious LLMs might pose, discusses current challenges, and outlines future directions for this emerging field.