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Deanthropomorphising NLP: Can a language model be conscious?
Matthew Shardlow1, Piotr Przybyła2,3
1Department of Computing and Mathematics, Manchester Metropolitan University, Manchester, United Kingdom.
Large language models (LLMs) are not sentient, despite claims about models like LaMDA and ChatGPT. Analysis using Integrated Information Theory shows Transformer architectures lack consciousness, refuting sentience claims in natural language processing.
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Area of Science:
- Artificial Intelligence
- Cognitive Science
- Philosophy of Mind
Background:
- Recent claims suggest pretrained large language models (LLMs) based on Transformer architecture, such as LaMDA and ChatGPT, may be sentient.
- Such claims carry significant implications for the Natural Language Processing (NLP) community due to the widespread adoption of these models.
Purpose of the Study:
- To critically evaluate the claims of sentience in large language models (LLMs).
- To analyze the Transformer architecture through the lens of Integrated Information Theory (IIT) of consciousness.
- To address the tendency towards anthropomorphic language in reporting on NLP advancements.
Main Methods:
- Analysis of the Transformer model architecture.
- Application of Integrated Information Theory (IIT) to assess consciousness.
- Review of claims regarding LLM sentience and NLP reporting practices.
Main Results:
- The study posits that large language models, including LaMDA, cannot be conscious.
- Analysis through IIT indicates that Transformer architectures do not exhibit properties of consciousness.
- LaMDA shows no unique advancements over similar models that would support sentience claims.
Conclusions:
- Claims of sentience in LLMs like LaMDA and ChatGPT are unfounded based on current architectural understanding and consciousness theory.
- The use of anthropomorphic language in NLP requires careful consideration.
- An examination of progress in language modeling and its ethical implications is timely.

