Research

Why do we find it easier to attribute knowledge than belief? A promising answer suggests that attributing belief requires representations with content that can come apart from reality, whereas attributing knowledge does not. However, this account fails to generalize to desire attribution. Like belief, desire can diverge from the world, yet research suggests that attributing desire is fast, easy, and early developing—much more like attributing knowledge than belief. I propose an alternative explanation, the efficient recovery account, which explains differences between knowledge, belief, and desire attribution in terms of processing efficiency rather than representational content.

On a popular and influential view, normative reasons are premises in good reasoning, where good reasoning manifests a pattern of reasoning that normally preserves fittingness. I develop two counterexamples to this view: isolated pro tanto reasons that are either weak or normally overridden.

The past 40 years has seen an explosion of research using “implicit” or indirect measures, purportedly uncovering a host of implicit attitudes (IAs) that escape the net of traditional, direct measures. Researchers are especially interested in IAs that reflect social biases. We describe two influential methodologies of indirect measurement, including the Implicit Association Test (IAT), and then summarize important features of IAs. But what are IAs? What are indirect measures measuring? In this entry, we survey prominent accounts in psychology and philosophy of the nature of IAs including views on which IAs are associations, views on which they are beliefs, and challenges to these views that hold IAs are, instead, patchy endorsements, traits, imaginings, or mental imagery. We conclude by exploring the possibility of a pluralism on which IAs are a motley collection of real mental entities.