Rights and Wrongs in Talk of Mind-Reading Technology

This article examines the idea of mind-reading technology by focusing on an interesting case of applying a large language model (LLM) to brain data. On the face of it, experimental results appear to show that it is possible to reconstruct mental contents directly from brain data by processing via a...

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Bibliographic Details
Main Author: Rainey, Stephen (Author)
Format: Electronic Article
Language:English
Check availability: HBZ Gateway
Interlibrary Loan:Interlibrary Loan for the Fachinformationsdienste (Specialized Information Services in Germany)
Published: 2024
In: Cambridge quarterly of healthcare ethics
Year: 2024, Volume: 33, Issue: 4, Pages: 521-531
Further subjects:B fMRI
B mind reading
B brain data
B large language models
B Reasons
B chatGPT
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Summary:This article examines the idea of mind-reading technology by focusing on an interesting case of applying a large language model (LLM) to brain data. On the face of it, experimental results appear to show that it is possible to reconstruct mental contents directly from brain data by processing via a chatGPT-like LLM. However, the author argues that this apparent conclusion is not warranted. Through examining how LLMs work, it is shown that they are importantly different from natural language. The former operates on the basis of nonrational data transformations based on a large textual corpus. The latter has a rational dimension, being based on reasons. Using this as a basis, it is argued that brain data does not directly reveal mental content, but can be processed to ground predictions indirectly about mental content. The author concludes that this is impressive but different in principle from technology-mediated mind reading. The applications of LLM-based brain data processing are nevertheless promising for speech rehabilitation or novel communication methods.
ISSN:1469-2147
Contains:Enthalten in: Cambridge quarterly of healthcare ethics
Persistent identifiers:DOI: 10.1017/S0963180124000045