Consciousness and Rationality: The Lesson from Artificial Intelligence

The author reviews three longstanding objections to artificial intelligence: that machines lack consciousness, cannot solve fully general problems, and operate without genuine semantic understanding. The argument connects these problems through the concept of non-syntactic inferences—inferences based on insight into rational relationships among thought-contents. Such insight, the author contends, is only possible through phenomenal consciousness, and it alone gives epistemic justification to those inferences. Until artificial systems can execute inferences guided by conscious states, they cannot be considered intelligent in a literal sense.

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Abstract

I review three problems that have historically motivated pessimism about artificial intelligence: (1) the problem of consciousness, according to which artificial systems lack the conscious oversight that characterizes intelligent agents; (2) the problem of global relevance, according to which artificial systems cannot solve fully general theoretical and practical problems; (3) the problem of semantic irrelevance, according to which artificial systems cannot be guided by semantic comprehension. I connect the dots between all three problems by drawing attention to non-syntactic inferences — inferences that are made on the basis of insight into the rational relationships among thought-contents. Consciousness alone affords such insight, I argue, and such insight alone confers positive epistemic status on the execution of these inferences. Only when artificial systems can execute inferences that are rationally guided by phenomenally conscious states will such systems count as intelligent in a literal sense.