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The feasibility of artificial consciousness through the lens of neuroscience.

Jaan Aru, Matthew E Larkum, James M Shine

Trends in Neurosciences December 1, 2023 DOI: 10.1016/j.tins.2023.09.009 (opens in new tab)

Study at a glance

AI-extracted from the abstract
Characteristics Theoretical or philosophical paper Peer reviewed
Keywords Agency Artificial intelligence Generative ai Large language models Machine learning Thalamus
Key points Argues that claims of LLMs becoming conscious are unsupported because they lack embodied sensory input, key neural features, and evolutionary-developmental trajectories linked to consciousness in living organisms.

Abstract

Interactions with large language models (LLMs) 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 LLMs lack the embodied, embedded information content characteristic of our sensory contact with the world around us. Secondly, the architectures of present-day artificial intelligence algorithms are 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.

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