The Road Ahead

This final chapter of the book summarizes the conclusions of the preceding chapters and looks forward to how the Aggregate Utility Solution might be generalized so that it applies not only to the expected utility theory framework, but also to other frameworks for rational decision-making. In particular, it explains how we might extend the Aggregate Utility Solution to the framework of imprecise credences and utilities, and to the framework of risk-sensitive decision theories.

Subjective Probability and the Content/Attitude Distinction

On an attractive, naturalistically respectable theory of intentionality, mental contents are a form of measurement system for representing behavioral and psychological dispositions. This chapter argues that a consequence of this view is that the content/attitude distinction is measurement system relative. As a result, there is substantial arbitrariness in the content/attitude distinction. Whether some measurement of mental states counts as characterizing the content of mental states or the attitude is not a question of empirical discovery but of theoretical utility. If correct, this observation has ramifications in the theory of rationality. Some epistemologists and decision theorists have argued that imprecise credences are rationally impermissible, while others have argued that precise credences are rationally impermissible. If the measure theory of mental content is correct, however, then neither imprecise credences nor precise credences can be rationally impermissible.

Knowledge and belief

This chapter uses probabilistic knowledge to defend compelling positions in contemporary epistemological debates. The chapter starts by developing a knowledge norm for probabilistic belief and applying this norm to debates about what you should believe when you find out that you disagree with an epistemic peer. By contrast with existing views of peer disagreement, the knowledge norm defended in this chapter can yield the intuitive verdict that disagreeing epistemic peers should adopt imprecise credences, thereby suspending judgment about probabilistic contents that they disagree about. Probabilistic knowledge is also used in this chapter to give a theory of knowledge by statistical inference, as well as to defend dogmatism about perceptual knowledge from a wide range of recent objections.

Knowledge and action

This chapter develops and defends two probabilistic knowledge norms of action. The first is a knowledge norm for reasons, namely that you may treat a probabilistic content as a reason for action if and only if you know it. This norm can help explain intuitive judgments about rational action. It can also help us rethink alleged instances of pragmatic encroachment often cited as challenges for existing knowledge norms of action. The second norm defended in this chapter is a knowledge norm for decisions. According to this norm, an action is permissible for you if and only if it is considered permissible for an agent with imprecise credences whose beliefs exactly match your probabilistic knowledge. This norm provides a precise interpretation of the controversial view that standard decision theory cannot guide decisions about transformative experiences, where this interpretation succeeds in answering a wide range of recent objections to this view.