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The belief that AI is conscious is not without risk , Is the design of artificial intelligence (AI) systems that are conscious within reach? Scientists, philosophers, and the general public are divided on this question. Some believe that consciousness is an inherently biological trait specific to brains, which seems to rule out the possibility of AI consciousness. Others argue that consciousness depends only on the manipulation of information by an algorithm, whether the system performing these computations is made up of neurons, silicon, or any other physical substrate—so-called computational functionalism. Definitive answers about AI consciousness will not be attempted here; instead, two related questions are considered. One concerns how beliefs about AI consciousness are likely to evolve in the scientific community and the general public as AI continues to improve. The other regards the risks of projecting into future AIs both the moral status and the natural goal of self-preservation that are normally associated with conscious beings.
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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.
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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.