[2308.08708] Consciousness in Artificial Intelligence: Insights from the Science of Consciousness
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Computer Science > Artificial Intelligence
arXiv:2308.08708 (cs)
[Submitted on 17 Aug 2023 (v1), last revised 22 Aug 2023 (this version, v3)]
Title:Consciousness in Artificial Intelligence: Insights from the Science of Consciousness
Authors:Patrick Butlin, Robert Long, Eric Elmoznino, Yoshua Bengio, Jonathan Birch, Axel Constant, George Deane, Stephen M. Fleming, Chris Frith, Xu Ji, Ryota Kanai, Colin Klein, Grace Lindsay, Matthias Michel, Liad Mudrik, Megan A. K. Peters, Eric Schwitzgebel, Jonathan Simon, Rufin VanRullen<br>View a PDF of the paper titled Consciousness in Artificial Intelligence: Insights from the Science of Consciousness, by Patrick Butlin and 18 other authors
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Abstract:Whether current or near-term AI systems could be conscious is a topic of scientific interest and increasing public concern. This report argues for, and exemplifies, a rigorous and empirically grounded approach to AI consciousness: assessing existing AI systems in detail, in light of our best-supported neuroscientific theories of consciousness. We survey several prominent scientific theories of consciousness, including recurrent processing theory, global workspace theory, higher-order theories, predictive processing, and attention schema theory. From these theories we derive "indicator properties" of consciousness, elucidated in computational terms that allow us to assess AI systems for these properties. We use these indicator properties to assess several recent AI systems, and we discuss how future systems might implement them. Our analysis suggests that no current AI systems are conscious, but also suggests that there are no obvious technical barriers to building AI systems which satisfy these indicators.
Subjects:
Artificial Intelligence (cs.AI); Computers and Society (cs.CY); Machine Learning (cs.LG); Neurons and Cognition (q-bio.NC)
Cite as:<br>arXiv:2308.08708 [cs.AI]
(or<br>arXiv:2308.08708v3 [cs.AI] for this version)
https://doi.org/10.48550/arXiv.2308.08708
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arXiv-issued DOI via DataCite
Submission history<br>From: Robert Long [view email]<br>[v1]<br>Thu, 17 Aug 2023 00:10:16 UTC (1,543 KB)
[v2]<br>Mon, 21 Aug 2023 06:18:34 UTC (1,543 KB)
[v3]<br>Tue, 22 Aug 2023 17:33:15 UTC (1,543 KB)
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