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Consciousness indicators, mimicry, and internal variants

Resource type
Journal Article
Authors/contributors
Title
Consciousness indicators, mimicry, and internal variants
Abstract
In a recent article on methods for assessing artificial intelligence (AI) systems for consciousness, we argued that computational properties of internal processing should be used as indicators [1]. Commenting on our proposal, Pennartz argues that this method ‘should be supplemented with behavioural-cognitive methods’ (p. 1) because there is no consensus theory of consciousness [2]. We agree that the lack of a consensus theory of consciousness makes it more important to use every available source of evidence, but in our article, we preferred internal over behavioural assessments on the grounds that the latter can be ‘gamed’ by AI systems.
Publication
Trends in Cognitive Sciences
Publisher
Elsevier
Date
2026/04/24
Volume
0
Issue
0
Journal Abbr
Trends in Cognitive Sciences
Accessed
4/26/26, 6:51 PM
ISSN
1364-6613, 1879-307X
Language
English
Library Catalog
Citation
Butlin, P., Bayne, T., Fleming, S. M., Mudrik, L., Peters, M. A. K., Schwitzgebel, E., Simon, J., & VanRullen, R. (2026). Consciousness indicators, mimicry, and internal variants. Trends in Cognitive Sciences, 0(0). https://doi.org/10.1016/j.tics.2026.04.006