Trends in Cognitive Sciences· 2025Q1· Review
Identifying indicators of consciousness in AI systems
- 53citations
- Q1SCImago
- 2025year
Short summary
A new method proposes assessing AI consciousness by deriving indicators from neuroscientific theories, particularly computational functionalist ones, which have empirically testable implications for AI.
AI-generated from the title and abstract; the full text is not read.
Key points
- A method is proposed to assess AI consciousness using indicators derived from neuroscientific theories.
- The method allows for the derivation of credences regarding AI consciousness.
- Computational functionalist theories of consciousness are highlighted for their empirical implications for AI.
- This approach aims to make meaningful progress in the assessment of AI consciousness.
AI-generated from the title and abstract; the full text is not read.
Abstract
Rapid progress in artificial intelligence (AI) capabilities has drawn fresh attention to the prospect of consciousness in AI. There is an urgent need for rigorous methods to assess AI systems for consciousness, but significant uncertainty about relevant issues in consciousness science. We present a method for assessing AI systems for consciousness that involves exploring what follows from existing or future neuroscientific theories of consciousness. Indicators derived from such theories can be used to inform credences about whether particular AI systems are conscious. This method allows us to make meaningful progress because some influential theories of consciousness, notably including computational functionalist theories, have implications for AI that can be investigated empirically.
The authors' abstract, as published at the source. Trends in Cognitive Sciences, 2025 · DOI ↗
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Field: Experimental and Cognitive Psychology
Experimental and Cognitive PsychologyPsychology