Brett Karlan

We argue that the concept of practical wisdom is particularly useful for organizing, understanding, and improving human-machine interactions. We consider the relationship between philosophical analysis of wisdom and psychological research into the development of wisdom. We adopt a practical orientation that suggests a conceptual engineering approach is needed, where philosophical work involves refinement of the concept in response to contributions by engineers and behavioral scientists. The former are tasked with encoding as much wise design as possible into machines themselves, as well as providing sandboxes or workspaces to help various stakeholders build practical wisdom in systems that are sufficiently realistic to aid transferring skills learned to real-world use. The latter are needed for the design of exercises and methods of evaluation within these workspaces, as well as ways of empirically assessing the transfer of wisdom from workspace to world. Systematic interaction between these three disciplines (and others) is the best approach to engineering wisdom for the machine age.

Implicit attitudes are mental states posited by psychologists to explain behaviors including implicit racial and gender bias. In this paper I investigate the belief view of the implicit attitudes, on which implicit attitudes are a kind of implicit belief. In particular, I focus on why implicit attitudes, if they are beliefs, are often resistant to updating in light of new evidence. I argue that extant versions of the belief view do not give a satisfactory account of this phenomenon. This is because proponents of the belief view have focused on overly narrow explanations of recalcitrance in terms of belief storage. Expanding the focus of the belief view to the kinds of irrational and arational transitions between beliefs and other mental states provides compelling (if preliminary) explanations of recalcitrance.

Which rules should guide our reasoning? Human reasoners often use reasoning shortcuts, called heuristics, which function well in some contexts but lack the universality of reasoning rules like deductive implication or inference to the best explanation. Does it follow that human reasoning is hopelessly irrational? I argue: no. Heuristic reasoning often represents human reasoners reaching a local rational maximum, reasoning more accurately than if they try to implement more “ideal” rules of reasoning. I argue this is a genuine rational achievement. Our ideal rational advisors would advise us to reason with heuristic rules, not more complicated ideal rules. I argue we do not need a radical new account of epistemic norms to make sense of the success of heuristic reasoning.