Identifying indicators of consciousness in AI systems
Identification
- Public canonical key
- radar:r-85e45ac4eb2f6dc942be90317c080f25
- Authors
- Patrick Butlin · Robert Long · Tim Bayne · Yoshua Bengio · Jonathan Birch · David J. Chalmers · Axel Constant · George Deane · Eric Elmoznino · Stephen M. Fleming · Xu Ji · Ryota Kanai · Colin Klein · Grace W. Lindsay · Matthias Michel · Liad Mudrik · Megan A. K. Peters · Eric Schwitzgebel · Jonathan Simon · Rufin VanRullen
- Reported year
- 2025
- Reported language
- en
- Source type
- review
- First detected
- 2026-11-14T02:04:22.027489+00:00
- Last metadata observation
- 2026-11-14T02:04:22.027489+00:00
- Last HTTP verification
- Not checked
Institutions reported by the source
University of Oxford · Canadian Institute for Advanced Research · Monash University · Mila - Quebec Artificial Intelligence Institute · Université de Montréal · London School of Economics and Political Science · New York University · University of Sussex · University College London · University of Westminster · Araya Inc. (Japan) · Australian National University · Massachusetts Institute of Technology · Tel Aviv University · University of California, Irvine · University of California, Riverside · Centre National de la Recherche Scientifique · Centre de recherche cerveau et cognition
Reported affiliation countries
AU · CA · FR · GB · IL · JP · US
Documentary abstract — original language
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.
Identifiers
- OPENALEX
- https://openalex.org/W4416083181
- DOI
- 10.1016/j.tics.2025.10.011
- PMID
- https://pubmed.ncbi.nlm.nih.gov/41219038
Documentary context
- Documentary family
- unknown
- Source-reported types
- review
- Publishers
- Elsevier BV
Entity mentions are not evidence of legal recognition. Jurisdiction studied is separate from author affiliation country.
Sources
OpenAlex · Record 1
Cite this reference
Patrick Butlin; Robert Long; Tim Bayne; Yoshua Bengio; Jonathan Birch; David J. Chalmers; Axel Constant; George Deane; Eric Elmoznino; Stephen M. Fleming; Xu Ji; Ryota Kanai; Colin Klein; Grace W. Lindsay; Matthias Michel; Liad Mudrik; Megan A. K. Peters; Eric Schwitzgebel; Jonathan Simon; Rufin VanRullen. Identifying indicators of consciousness in AI systems. 2025. https://doi.org/10.1016/j.tics.2025.10.011
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APA, Chicago, ISO 690: bibliographic formats using available fields. OSCOLA / Bluebook: structured data only; full legal citation compliance is not claimed without verification of required elements.
- APA
- Patrick Butlin; Robert Long; Tim Bayne; Yoshua Bengio; Jonathan Birch; David J. Chalmers; Axel Constant; George Deane; Eric Elmoznino; Stephen M. Fleming; Xu Ji; Ryota Kanai; Colin Klein; Grace W. Lindsay; Matthias Michel; Liad Mudrik; Megan A. K. Peters; Eric Schwitzgebel; Jonathan Simon; Rufin VanRullen. (2025). Identifying indicators of consciousness in AI systems. https://doi.org/10.1016/j.tics.2025.10.011
- Chicago
- Patrick Butlin; Robert Long; Tim Bayne; Yoshua Bengio; Jonathan Birch; David J. Chalmers; Axel Constant; George Deane; Eric Elmoznino; Stephen M. Fleming; Xu Ji; Ryota Kanai; Colin Klein; Grace W. Lindsay; Matthias Michel; Liad Mudrik; Megan A. K. Peters; Eric Schwitzgebel; Jonathan Simon; Rufin VanRullen. Identifying indicators of consciousness in AI systems. 2025. https://doi.org/10.1016/j.tics.2025.10.011
- ISO 690
- Patrick Butlin; Robert Long; Tim Bayne; Yoshua Bengio; Jonathan Birch; David J. Chalmers; Axel Constant; George Deane; Eric Elmoznino; Stephen M. Fleming; Xu Ji; Ryota Kanai; Colin Klein; Grace W. Lindsay; Matthias Michel; Liad Mudrik; Megan A. K. Peters; Eric Schwitzgebel; Jonathan Simon; Rufin VanRullen. Identifying indicators of consciousness in AI systems. 2025. https://doi.org/10.1016/j.tics.2025.10.011
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UDTR Global Rights of Nature Legal Library. Identifying indicators of consciousness in AI systems. Documentary record: https://www.declarationuniverselledesdroitsdelarbre.org/global-rights-of-nature-radar/reference/r-85e45ac4eb2f6dc942be90317c080f25/ · Last HTTP verification: not performed
Research dossiers and documentary relations
Source roles
Bibliographic / original publication source · https://doi.org/10.1016/j.tics.2025.10.011
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Documentary status
Relevance pending
Library
This identity is not yet included in the Legal Library.