Nicolas Porot

“What is the structure of thought?” is as central a question as any in cognitive science. A classic answer to this question has appealed to a Language of Thought (LoT). We point to emerging research from disparate branches of the field that supports the LoT hypothesis, but also uncovers diversity in LoTs across cognitive systems, stages of development, and species. Our letter formulates open research questions for cognitive science concerning the varieties of rules and representations that underwrite various LoT-based systems and how these variations can help researchers taxonomize cognitive systems

The language of thought hypothesis is a thesis about the structure of mental representations. It is an example of the computational–representational theory of mind, according to which much of cognition consists in formal computations over mental representations. What distinguishes the language of thought hypothesis from other such theories is the idea that mental representations share core features with formal languages. The language of thought hypothesis states that thinking is the transformation of mental representations in a language of thought, in which most of what we call “thinking” is in fact inferences performed over sentences in the language. The language of thought is not a natural language, such as Spanish or Haitian Creole. It is a formal language, comparable to the machine language of a computer or formal languages of logic. The language of thought is often claimed to be innate, universal, and pivotal in learning, and it is implicated in processes such as natural language acquisition. However, it is also compatible with learning and reasoning in nonlinguistic creatures as well as in mental processes seemingly unconnected to language such as perception and motor control.

In our paper, “The reference of proper names” (2018), we raised and rebutted the “New‐Meaning” objection to our methodology. Our rebuttal rested on theoretical considerations and experimental results. In “Do the Gödel vignettes involve a new descriptivist meaning?”, Nicolò D'Agruma provides an interesting argument against our theoretical considerations (but does not address the experimental evidence). Our present paper argues against D'Agruma. So, our original rebuttal of the objection still stands. We offer further evidence against the objection.

We aim to do two things in this article. On the positive end, our goal is to explain how some seemingly incompatible aspects of belief live together, by presenting distinct mechanistic explanations of each of them: in particular we want to show how belief can be discerning, credulous, rational, and irrational. After clarifying our positive view, we take aim at some competitor views in the second half of the paper, particularly offering critiques of epistemic vigilance and social marketplace accounts of belief. We conclude by inviting proponents to provide an architecture for belief that can be tested against existing models

Four studies explore the role of perceptual fluency in attenuating bullshit receptivity, or the tendency for individuals to rate otherwise meaningless statements as “profound”. Across four studies, we presented participants with a sample of pseudoprofound bullshit statements in either a fluent or disfluent font and found that overall, disfluency attenuated bullshit receptivity while also finding little evidence that this effect was moderated by cognitive thinking style. In all studies, we measured participants’ cognitive reflection, need for cognition, faith in intuition, and superstitious beliefs. Superstition strongly predicted bullshit receptivity regardless of fluency. Inconclusive results were found for the remaining scales. Potential links for the role of perceptual disfluency in promoting analytic thinking are discussed.

Mental representations remain the central posits of psychology after many decades of scrutiny. However, there is no consensus about the representational format(s) of biological cognition. This paper provides a survey of evidence from computational cognitive psychology, perceptual psychology, developmental psychology, comparative psychology, and social psychology, and concludes that one type of format that routinely crops up is the language-of-thought (LoT). We outline six core properties of LoTs: (i) discrete constituents; (ii) role-filler independence; (iii) predicate–argument structure; (iv) logical operators; (v) inferential promiscuity; and (vi) abstract content. These properties cluster together throughout cognitive science. Bayesian computational modeling, compositional features of object perception, complex infant and animal reasoning, and automatic, intuitive cognition in adults all implicate LoT-like structures. Instead of regarding LoT as a relic of the previous century, researchers in cognitive science and philosophy-of-mind must take seriously the explanatory breadth of LoT-based architectures. We grant that the mind may harbor many formats and architectures, including iconic and associative structures as well as deep-neural-network-like architectures. However, as computational/representational approaches to the mind continue to advance, classical compositional symbolic structures – that is, LoTs – only prove more flexible and well-supported over time.

Experiments on theories of reference have mostly tested referential intuitions. We think that experiments should rather be testing linguistic usage. Substantive Aim (I): to test classical description theories of proper names against usage by “elicited production.” Our results count decisively against those theories. Methodological Aim (I): Machery, Olivola, and de Blanc (2009) claim that truth-value judgment experiments test usage. Martí (2012) disagrees. We argue that Machery et al. are right and offer some results that are consistent with that conclusion. Substantive Aim (II): Machery et al. provide evidence that the usage of a name varies, being sometimes descriptive, sometimes not. In seven out of eight tests of usage, we did not replicate this variation. Methodological Aim (II): to test the reliability of referential intuitions by comparing them with linguistic usage. Earlier studies led us to predict that we would find those intuitions unreliable, but we did not. Our results add to evidence that tests of referential intuition are susceptible to unpredictable wording effects.

The empirical study of belief is emerging at a rapid clip, uniting work from all corners of cognitive science. Reliance on belief in understanding and predicting behavior is widespread. Examples can be found, inter alia, in the placebo, attribution theory, theory of mind, and comparative psychological literatures. Research on belief also provides evidence for robust generalizations, including about how we fix, store, and change our beliefs. Evidence supports the existence of a Spinozan system of belief fixation: one that is automatic and independent of belief rejection. Independent research supports the existence of a system of fragmented belief storage: one that relies on large numbers of causally isolated, context-sensitive stores of belief in memory. Finally, empirical and observational data support at least two systems of belief change. One system adheres, mostly, to epistemological norms of updating; the other, the psychological immune system, functions to guard our most centrally held beliefs from potential inconsistency with newly formed beliefs. Refining our under- standing of these systems can shed light on pressing real-world issues, such as how fake news, propaganda, and brainwashing exploit our psychology of belief, and how best to construct our modern informational world.