This chapter discusses the philosophical relevance of empirical research on moral cognition. It distinguishes three central aims of normative ethical theory: understanding the nature of moral agency, identifying morally right actions, and determining the justification of moral beliefs. For each of these aims, the chapter considers and rejects arguments against employing cognitive scientific research in normative inquiry. It concludes by suggesting that, whichever of the central aims one begins from, normative ethics is improved by engaging with the science of moral (...) cognition. (shrink)

When making moral judgments, people are typically guided by a plurality of moral rules. These rules owe their existence to human emotions but are not simply equivalent to those emotions. And people’s moral judgments ought to be guided by a plurality of emotion-based rules. The view just stated combines three positions on moral judgment: [1] moral sentimentalism, which holds that sentiments play an essential role in moral judgment,1 [2] descriptive moral pluralism, which holds that commonsense moral judgment is guided by (...) a plurality of moral rules2, and [3] prescriptive moral pluralism, which holds that moral judgment ought to be guided by a plurality of moral rules. In what follows, we will argue for all three positions. We will not present a comprehensive case for these positions nor address many of the arguments philosophers have developed against them. What we will try to show is that recent psychological work supports sentimentalist pluralism in both its descriptive and prescriptive forms. (shrink)

‘Particularism’ and ‘generalism’ refer to families of positions in the philosophy of moral reasoning, with the former playing down the importance of principles, rules or standards, and the latter stressing their importance. Part of the debate has taken an empirical turn, and this turn has implications for AI research and the philosophy of cognitive modeling. In this paper, Jonathan Dancy’s approach to particularism (arguably one of the best known and most radical approaches) is questioned both on logical and empirical grounds. (...) Doubts are raised over whether Dancy’s brand of particularism can adequately explain the graded nature of similarity assessments in analogical arguments. Also, simple recurrent neural network models of moral case classification are presented and discussed. This is done to raise concerns about Dancy’s suggestion that neural networks can help us to understand how we could classify situations in a way that is compatible with his particularism. Throughout, the idea of a surveyable standard—one with restricted length and complexity—plays a key role. Analogical arguments are taken to involve multidimensional similarity assessments, and surveyable contributory standards are taken to be attempts to articulate the dimensions of similarity that may exist between cases. This work will be of relevance both to those who have interests in computationally modeling human moral cognition and to those who are interested in how such models may or may not improve our philosophical understanding of such cognition. (shrink)

In this paper, I defend the view that we can literally perceive the morally right and wrong, or something near enough. In defending this claim, I will try to meet three primary objectives: to clarify how an investigation into moral phenomenology should proceed, to respond to a number of misconceptions and objections that are most frequently raised against the very idea of moral perception, and to provide a model for how some moral perception can be seen as literal perception. Because (...) I take “moral perception” to pick out a family of different experiences, I will limit myself to a discussion of the moral relevance of the emotions. (shrink)

I raise skeptical doubts about the prospects of Bayesian formal epistemology for providing an adequate general normative model of epistemic rationality. The notion of credence, I argue, embodies a very dubious psychological myth, viz., that for virtually any proposition p that one can entertain and understand, one has some quantitatively precise, 0-to-1 ratio-scale, doxastic attitude toward p. The concept of credence faces further serious problems as well—different ones depending on whether credence 1 is construed as full belief or instead is (...) construed as absolute certainty. I argue that the notion of an “ideal Bayesian reasoner” cannot serve as a normative ideal that actual human agents should seek to emulate as closely as they can, because different such reasoners who all have the same evidence as oneself—no single one them being uniquely psychologically most similar to oneself—will differ from one another in their credences. I argue that epistemic probability, properly understood, is quantitative degree of evidential support relative to one’s evidence, and that principled epistemic probabilities arise only under quite special evidential circumstances—which means that epistemic probability is ill suited to figure centrally within general norms of human epistemic rationality. (shrink)