Casey Landers

Educators are increasingly concerned with the use of artificial intelligence (AI) in student writing. Much of the concern focuses on the issue of students using ChatGPT to complete their work. I introduce the CUPID model for instructors to use when thinking about how to pedagogically handle ChatGPT. The CUPID model lays out five general approaches: Catch, Utilize, Prevent, Ignore, and Disincentivize. I suggest that instructors should especially consider using certain assignments that fall under the approach “Disincentivize”. Philosophy instructors in particular should assign more low-stakes writing, such as journals and reflection pieces. The adoption of low-stakes writing assignments aims to discourage students from relying on AI while promoting clarity of thought and deeper engagement with philosophical ideas.

Through extensive training, experts acquire specialized knowledge and abilities. In this paper, I argue that experts also acquire specialized visual experiences. Specifically, I articulate and defend the account that experts enjoy visual experiences that represent gestalt properties through perceptual learning. I survey an array of empirical studies on face perception and perceptual expertise that support this account. I also look at studies on perceptual adaptation that some might argue present a problem for my account. I show how the data are subject to an interpretation that is friendly to it. Last, I address two theoretical objections to the claim that visual experiences represent gestalt properties.

Synesthesia is a neurological phenomenon in which a single stimulus typically associated with one sensory modality automatically and involuntarily produces sensations not typically associated with that modality. I argue that synesthesia elucidates how two naturalistic theories of representation and phenomenal experience conflict. Strong representationalism holds that what an experience is like is determined by the experience’s representational content. Informational semantics holds that representational content is determined by causal co-variation between a representation and an external object or property. I argue that according to informational semantics, synesthetes and normal perceivers represent the same content in different ways. However, according to strong representationalism, two experiences with the same content must be represented in the same way. Therefore, if strong representationalists want to account for synesthesia, they cannot hold onto informational semantics as a theory of mental content.

When someone says she believes that God exists, is she expressing the same kind of mental state as when she says she thinks that a lake bigger than Lake Michigan exists⎯i.e., does she refer to the same kind of cognitive attitude in both cases? Using evidence from linguistic corpora (Study 1) and behavioral experiments (Studies 2-4), the current work provides evidence that individuals typically use the word “believe” more in conjunction with statements about religious credences and “think” more in conjunction with factual statements, pointing to two different understandings of claims made with these two terms. These patterns do not appear to reflect low-level differences based on the amount of consensus surrounding a particular claim, the extent to which the truth of a particular claim is known to the participant, or linguistic differences between religious and factual statements. We discuss implications of these findings for religious cognition (e.g., as supporting the theory that religious credences are qualitatively distinct from factual beliefs) as well as cognitive processes more broadly. Finally, we relate the present findings to prior theoretical work on differences between factual belief and religious credence.