Full bibliography
Identifying indicators of consciousness in AI systems
Resource type
Journal Article
Authors/contributors
- Butlin, Patrick (Author)
- Long, Robert (Author)
- Bayne, Tim (Author)
- Bengio, Yoshua (Author)
- Birch, Jonathan (Author)
- Chalmers, David (Author)
- Constant, Axel (Author)
- Deane, George (Author)
- Elmoznino, Eric (Author)
- Fleming, Stephen M. (Author)
- Ji, Xu (Author)
- Kanai, Ryota (Author)
- Klein, Colin (Author)
- Lindsay, Grace (Author)
- Michel, Matthias (Author)
- Mudrik, Liad (Author)
- Peters, Megan A. K. (Author)
- Schwitzgebel, Eric (Author)
- Simon, Jonathan (Author)
- VanRullen, Rufin (Author)
Title
Identifying indicators of consciousness in AI systems
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.
Publication
Trends in Cognitive Sciences
Date
2025-11-10
Journal Abbr
Trends in Cognitive Sciences
Accessed
11/11/25, 8:04 PM
ISSN
1364-6613
Library Catalog
ScienceDirect
Citation
Butlin, P., Long, R., Bayne, T., Bengio, Y., Birch, J., Chalmers, D., Constant, A., Deane, G., Elmoznino, E., Fleming, S. M., Ji, X., Kanai, R., Klein, C., Lindsay, G., Michel, M., Mudrik, L., Peters, M. A. K., Schwitzgebel, E., Simon, J., & VanRullen, R. (2025). Identifying indicators of consciousness in AI systems. Trends in Cognitive Sciences. https://doi.org/10.1016/j.tics.2025.10.011
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