The Moral Foreign-Language Effect

Many have argued that moral judgment is driven by one of two types of processes. Rationalists argue that reasoned processes are the source of moral judgments, whereas sentimentalists argue that emotional processes are. We provide evidence that both positions are mistaken; there are multiple mental processes involved in moral judgment, and it is possible to manipulate which process is engaged when considering moral dilemmas by presenting them in a non-native language. The Foreign-Language Effect (FLE) is the activation of systematic reasoning processes by thinking in a foreign language. We demonstrate that the FLE extends to moral judgment. This indicates that different types of processes can lead to the formation of differing moral judgments. One implication of the FLE is that it raises the possibility that moral judgments can be made more systematic, and that the type of processing used to form them might be relevant to normative and applied ethics.     

Greatest surprise reduction semantics: an information theoretic solution to misrepresentation and disjunction

Causal theories of content, a popular family of approaches to defining the content of mental states, commonly run afoul of two related and serious problems that prevent them from providing an adequate theory of mental content—the misrepresentation problem and the disjunction problem. In this paper, I present a causal theory of content, built on information theoretic tools, that solves these problems and provides a viable model of mental content. This is the greatest surprise reduction theory of content, which identifies the content of a signal as the event the surprisal of which is most reduced by that signal. Conceptually, this amounts to the claim that the content of a signal is the event the probability of which has increased by the largest proportion, or the event that the signal makes the most less surprising to us. I develop the greatest surprise reduction theory of content in four stages. First, I introduce the general project of causal theories of content, and the challenges presented to this project by the misrepresentation and disjunction problems. Next, I review two recent and prominent causal theories of content and demonstrate the serious challenges faced by these approaches, both clarifying the need for a solution to the misrepresentation and disjunction problems and providing a conceptual background for the greatest surprise reduction theory. Then, I develop the greatest surprise reduction theory of content, demonstrate its ability to resolve the misrepresentation and disjunction problems, and explore some additional applications it may have. Finally, I conclude with a discussion of a particularly difficult challenge that remains to be addressed—the partition problem—and sketch a path to a potential solution.

     

Is belief evaluation truth sensitive? A reply to Turri

Synthese - A key question about the value of truth in epistemology is whether the truthfulness of some proposition is (or should be) a factor in our evaluation of beliefs. The traditional...