The feasibility of artificial consciousness through the lens of neuroscience

TL;DR

This paper critically examines the possibility of artificial consciousness through neuroscience, arguing that current large language models lack essential biological features linked to consciousness.

Contribution

It provides a neuroscientific perspective highlighting key differences between biological consciousness and artificial models, challenging claims of AI consciousness.

Findings

Large language models lack embodied sensory information.

Architectural differences from mammalian thalamocortical systems.

Evolutionary development of consciousness involves agency and multi-level processes.

Abstract

Interactions with large language models have led to the suggestion that these models may soon be conscious. From the perspective of neuroscience, this position is difficult to defend. For one, the inputs to large language models lack the embodied, embedded information content characteristic of our sensory contact with the world around us. Secondly, the architecture of large language models is missing key features of the thalamocortical system that have been linked to conscious awareness in mammals. Finally, the evolutionary and developmental trajectories that led to the emergence of living conscious organisms arguably have no parallels in artificial systems as envisioned today. The existence of living organisms depends on their actions, and their survival is intricately linked to multi-level cellular, inter-cellular, and organismal processes culminating in agency and consciousness.