Peter Railton

At least since Aristotle, practical skill has been thought to be a possible model for individual ethical development and action. Jonathan Birch’s ambitious proposal is that practical skill and tool-use might also have played a central role in the historical emergence and evolution of our very capacity for normative guidance. Birch argues that human acquisition of motor skill, for example in making and using tools, involves formation of an internal standard of correct performance, which serves as a basis for normative guidance in skilled thought and action, and in the social transfer of skills. I suggest that evaluativemodeling, guidance, and learning play a more basic role in motor skill than standards of correctness as such-indeed, such standards can provide effective normative guidance thanks to being embedded within evaluative modeling and guidance. This picture better fits the evidence Birch cites of the flexibility, adaptability, and creativity of skills, and can support a generalized version of Birch’s ‘skill hypothesis’.

In Susanna Siegel’s compelling presentation of the case for the rationality of perception, a “significant part of the constructive defense” is played by the idea that there are “inferential routes to perceptual experience” (Siegel 2017, p. 94). Inferences, after all, are epistemically evaluable and bear on the rational standing of their conclusions. She argues that an obstacle to accepting this idea is a “Reckoning Model” of inference, and shows by example that we recognize as inferences various familiar kinds of responses to information that do not fit this model. She offers a more general approach to the nature of inference that fits these examples and accommodates inferential routes to perceptual experience. I argue that Siegel needs to say more about the mental processes involved in such inferrings, and how it can be more than merely associative and yet still distinct from Reckoning. Fortunately, a psychologically‐ and conceptually‐grounded distinction between model‐free vs. model‐based learning and guidance processes can provide a characterization that plays the role Siegel needs.

Cushman seeks to explain rationalization in terms of fundamental mental processes, and he hypotheses a selected-for function: information exchange between “rational” and “non-rational” processes in the brain. While this is plausible, his account overlooks the importance – and information value – of rationalizing the emotions of ourselves and others. Incorporating such rationalization would help explain the effectiveness of rationalization and its connection with valuation, as well as raise a challenge to his way of bifurcating “rational” and “non-rational” processes.

The past 15 years occasioned an extraordinary blossoming of research into the cognitive and affective mechanisms that support moral judgment and behavior. This growth in our understanding of moral mechanisms overshadowed a crucial and complementary question, however: How are they learned? As this special issue of the journal Cognition attests, a new crop of research into moral learning has now firmly taken root. This new literature draws on recent advances in formal methods developed in other domains, such as Bayesian inference, reinforcement learning and other machine learning techniques. Meanwhile, it also demonstrates how learning and deciding in a social domain—and especially in the moral domain—sometimes involves specialized cognitive systems. We review the contributions to this special issue and situate them within the broader contemporary literature. Our review focuses on how we learn moral values and moral rules, how we learn about personal moral character and relationships, and the philosophical implications of these emerging models.

Recent decades have witnessed a sea change in thinking about emotion, which has gone from being seen as a disruptive force in human thought and action to being seen as an important source of situation- and goal-relevant information and evaluation, continuous with perception and cognition. Here I argue on philosophical and empirical grounds that the role of emotion in contributing to our ability to respond to reasons for action runs deeper still: The affective system is at the core of the process of evaluatively modeling situations, actions, and outcomes, which is the foundation upon which rational deliberation and action can be built. Taking up this perspective affords new approaches to long-standing problems in the theory of reason-based action.

Value and uncertainty are the critical components of decision and action. To think of the affective system as at the core of action is to draw attention to the role of affect in representing and combining these two dimensions, and orchestrating a wide range of mental capacities—attention, perception, memory, inference, motivation, and monitoring—in light of these evaluative representations. The commentators have helpfully enriched our appreciation of the various ways in which affect can contribute to the attunement, cuing, motivation, control, and ongoing assessment of decision and action.

If practical reason is concerned with thoughtful normative regulation of action, then theoretical reason might be seen as a matter of thoughtful normative regulation of belief. The conclusion of a piece of practical reasoning, we are told, is an act or intention to act; the conclusion of a piece of theoretical reasoning, by parallel, would be a belief or a belief-tendency. Because theoretical reason is understood to be responsive specifically to epistemic – not merely pragmatic – reasons for belief, the norms involved in heoretical reason are norms pertinent to knowledge, including norms of evidence, justification, and truth. In both the practical and theoretical case we need not exactly agree with the conclusion another person reaches in order to attribute rationality to her – but it seems we do need to find something normatively appropriate about the means by which the other reaches her conclusion, given her capacities and circumstances.