Paul Weirich

When new technologies create risks, government agencies use regulations to control the risks. This paper advances a method of evaluating a democracy’s regulation of risks. It assumes that a regulatory agency should act as the public would act in ideal conditions for negotiation if the public were rational and informed. The method relies on decision theory and game theory to ascertain whether a regulation has the public’s informed support. The Occupational Safety and Health Administration’s regulation of exposure to carcinogens in the workplace illustrates the account of regulation. The illustration draws attention to a distinction between physical and information-sensitive risks. Regulations guided by the physical sciences alone may overlook the value of reducing information-sensitive risks. These risks exist objectively, and rational people generally have an aversion to them. An information-sensitive risk and an aversion to it may persist after acquisition of all available relevant information. Democratic regulation justifiably aims to reduce such risks.

Causal decision theory produces decision instability in cases such as Death in Damascus where a decision itself provides evidence concerning the utility of options. Several authors have proposed ways of handling this instability. William Harper (1985 and 1986) advances one of the most elegant proposals. He recommends maximizing causal expected utility among the options that are causally ratifiable. Unfortunately, Harper's proposal imposes certain restrictions; for instance, the restriction that mixed strategies are freely available. To obtain a completely general method of handling decision instability, I step outside the confines of pure causal decision theory. I introduce a new kind of backtracking expected utility and propose maximizing it among the options that are causally ratifiable. In other words, I propose a hierarchical maximization of (1) conditional causal expected utility and (2) the new backtracking expected utility. I support this proposal with some intuitive considerations concerning the distinction between optimality and conditional optimality. And I prove that the proposal yields a solution in every finite decision problem

When a trustee makes a decision for a client, a standard objective is to decide as the client would if he had the trustee's information. How can this objective be attained when, given the trustee's information, there is still uncertainty about the consequences of alternative courses of action? A promising approach is to apply the rule to maximize expected utility using the client's utilities for consequences and the trustee's probabilities for states. But taking utilities and probabilities from different sources causes a problem that has to be resolved. Briefly, the problem is that the client's utilities for consequences involve assessments of risks that are uninformed because he does not have informed probabilities. And the resolution of the problem is to reconstruct his utilities for consequences using a component due to risk that the trustee supplies for the client, and a component due to other consequences that the client supplies for himself.

This book represents a major contribution to game theory. It offers this conception of equilibrium in games: strategic equilibrium. This conception arises from a study of expected utility decision principles, which must be revised to take account of the evidence a choice provides concerning its outcome. The argument for these principles distinguishes reasons for action from incentives, and draws on contemporary analyses of counterfactual conditionals. The book also includes a procedure for identifying strategic equilibria in ideal normal-form games. In synthesizing decision theory and game theory in a powerful way this book will be of particular interest to all philosophers concerned with decision theory and game theory as well as economists and other social scientists.

This book represents a major contribution to game theory. It offers this conception of equilibrium in games: strategic equilibrium. This conception arises from a study of expected utility decision principles, which must be revised to take account of the evidence a choice provides concerning its outcome. The argument for these principles distinguishes reasons for action from incentives, and draws on contemporary analyses of counterfactual conditionals. The book also includes a procedure for identifying strategic equilibria in ideal normal-form games. In synthesizing decision theory and game theory in a powerful way this book will be of particular interest to all philosophers concerned with decision theory and game theory as well as economists and other social scientists.

I will characterize the utilitarian and maximin rules of social choice game-theoretically. That is, I will introduce games whose solutions are the utilitarian and maximin distributions respectively. Then I will compare the rules by exploring similarities and differences between these games. This method of comparison has been carried out by others. But I characterize the two rules using games that involve bargaining within power structures. This new characterization better highlights the ethical differences between the rules.

Abner Shimony argues that degrees of belief satisfy the axioms of probability because their epistemic goal is to match estimates of objective probabilities. Because the estimates obey the axioms of probability, degrees of belief must also obey them to reach their epistemic goal. This calibration argument meets some objections, but with a few revisions it can surmount those objections. It offers a good alternative to the Dutch book argument for compliance with the probability axioms. The defense of Shimony's calibration argument examines rational pursuit of an epistemic goal, introduces strength of evidence and its measurement, and distinguishes epistemic goals and functions.