I consider a class of argument implying that Hume's position on general representation is irredeemably circular in that it presupposes what it is meant to explain. Arguments of this sort (the most famous being Sellars' "myth of the given") threaten to undermine any empiricist account of general representation by showing how they depend on the naïve assumption that the relevant resemblances required for the sorting of experience into concepts for use in reasoning are simply given in experience itself. My aim (...) is to salvage Hume's account from this objection. To that end, I argue first for a "Goodmanesque" interpretation of Humean resemblance, and second for an alternative reading of Hume's account of general ideas offered at T 1.1.7 that avoids falling into "the given" trap. (shrink)

I offer a defense of ana-logical accounts of scientific models by meeting certain logical objections to the legitimacy of analogical reasoning. I examine an argument by Joseph Agassi that purports to show that all putative cases of analogical inference succumb to the following dilemma: either (1) the reasoning remains hopelessly vague and thus establishes no conclusion, or (2) can be analyzed into a logically preferable non-analogical form. In rebuttal, I offer a class of scientific models for which (a) there is (...) no satisfactory non-analogical analysis, and (b) we can gain sufficient clarity for the legitimacy of the inference to be assessed. This result constitutes an existence proof for a class of analogical models that escape Agassi’s dilemma. (shrink)

While the value of the extended mind hypothesis for human cognition is disputed, this paper examines the explanatory utility of the extended mind framework in the domain of AI systems, specifically the Google self-driving car. I argue that the cognitive architecture of the Google-car is best explained as an instance of extended cognition. The argument for this claim begins with a description of the Google-car’s cognitive architecture, including the indispensable role of “prior maps” in its performance. I then argue that (...) the hypothesis of extended cognition provides a better explanation of the Google-car’s performance than two rival, non-extended alternatives. Consideration of the Google-car also offers insight into whether driverless vehicles have achieved human-level competency in the cognitive skills required for driving, or instead remain “poor substitutes.”. (shrink)