I review three problems that have historically motivated pessimism about artificial intelligence: (1) the Problem of Consciousness, according to which artificial systems function without the right sort of conscious oversight; (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 the 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. (shrink)

This paper disputes the widespread assumption that beliefs and desires may be attributed as theoretical entities in the service of the explanation and predic- tion of human behavior. The literature contains no clear account of how beliefs and desires might generate actions, and there is good reason to deny that principles of rationality generate a choice on the basis of an agent’s beliefs and desires. An alter- native conception of beliefs and desires is here introduced, according to which an attribution (...) of belief is, in a certain sense, an assertion on the believer’s behalf and an attribution of desire is, in a certain sense, a command on the desirer’s behalf. In terms of this conception of the attribution of beliefs and desires, we can begin to understand how attributions of beliefs and desires can be explanatory, although we still cannot expect the attribution of beliefs and desires to generate predictions based on an assumption of rationality. Finally, the reality of beliefs and desires is likened to the reality of money; it is the reality of things governed by objective norms. (shrink)

Over the last decade, Hugo Mercier and Dan Sperber have elaborated an influential naturalistic account of human reasoning. Their distinctive hypothesis is that its adaptive rationale – and primary function – is to produce and assess reasons in interpersonal justification and argumentation. In this paper I argue, first, that their characterisation of reasoning as based on metarepresentations threatens to oversophisticate reasoning and faces the problem of vicious regress. Second, I argue that they owe us a coherent account of the cognitive (...) role of reasons in reasoning. (shrink)

Science is a collaborative effort to produce knowledge. Scientists thus must assess what information is trustworthy and who is a competent and honest source and partner. Facing the problem of trust, we can expect scientists to be vigilant. In response to their peers’ vigilance scientists will provide reasons, not only to convince their colleagues to adopt their practices or beliefs, but also to demonstrate that their beliefs and practices are justified. By justifying their beliefs and practices, scientists also justify themselves. (...) Reasons in science thus do not only function as tools of persuasion but also to manage reputation. This analysis strongly suggests that science constitutes a moral system, which has implications for the study and philosophy of science. (shrink)