Paul Weirich

The rule to maximize expected utility is intended for decisions where options involve risk. In those decisions the decision maker's attitude toward risk is important, and the rule ought to take it into account. Allais's and Ellsberg's paradoxes, however, suggest that the rule ignores attitudes toward risk. This suggestion is supported by recent psychological studies of decisions. These studies present a great variety of cases where apparently rational people violate the rule because of aversion or attraction to risk. Here I attempt to resolve the issue concerning expected utility and risk. I distinguish two versions of the rule to maximize expected utility. One adopts a broad interpretation of the consequences of an option and has great intuitive appeal. The other adopts a narrow interpretation of the consequences of an option and seems to have certain technical and practical advantages. I contend that the version of the rule that interprets consequences narrowly does indeed neglect attitudes toward risk. That version of the rule excludes the risk involved in an option from the consequences of the option and, contrary to what is usually claimed, cannot make up for this exclusion through adjustments in probability and utility assignments. I construct a new, general argument that establishes this in a rigorous way. On the other hand, I contend that the version of the rule that interprets consequences broadly takes account of attitudes toward risk by counting the risk involved in an option among the consequences of the option. I rebut some objections to this version of the rules, in particular, the objection that the rule lacks practical interest. Drawing upon the literature on 'mean-risk' decision rules, I show that this version of the rule can be used to solve some realistic decision problems.

In Decision Space: Multidimensional Utility Analysis, first published in 2001, Paul Weirich increases the power and versatility of utility analysis and in the process advances decision theory. Combining traditional and novel methods of option evaluation into one systematic method of analysis, multidimensional utility analysis is a valuable tool. It provides formulations of important decision principles, such as the principle to maximize expected utility; enriches decision theory in solving recalcitrant decision problems; and provides in particular for the cases in which an expert must make a decision for a group of people. The multiple dimensions of this analysis create a decision space broad enough to accommodate all factors affecting an option's utility. The book will be of interest to advanced students and professionals working in the subject of decision theory, as well as to economists and other social scientists.

Classical bargaining theory attempts to solve a bargaining problem using only the information about the problem contained in the representation of its possible outcomes in utility space. However, this information usually underdetermines the solution. I use additional information about interpersonal comparisons of utility and bargaining power. The solution is then the outcome that maximizes the sum of power-weighted utilities. I use these results to advance a contractarian argument for a utilitarian form of social cooperation. As the original position, I propose a hypothetical situation in which the members of society are rational, fully informed, free, and equal. I argue that in this original position they would adopt a utilitarian form of social cooperation. I conclude that utilitarian cooperation constitutes a moral ideal toward which society ought to aspire.

Food products with genetically modified (GM) ingredients are common, yet many consumers are unaware of this. When polled, consumers say that they want to know whether their food contains GM ingredients, just as many want to know whether their food is natural or organic. Informing consumers is a major motivation for labeling. But labeling need not be mandatory. Consumers who want GM-free products will pay a premium to support voluntary labeling. Why do consumers want to know about GM ingredients? GM foods are tested to ensure safety and have been on the market for more than a decade. Still, many consumers, including some with food allergies, want to be cautious. Also, GM crops may affect neighboring plants through pollen drift. Despite tests for environmental impact, some consumers may worry that GM crops will adversely effect the environment. The study of risk and its management raises questions not settled by the life sciences alone. This book surveys various labeling policies and the cases for them. It is the first comprehensive, interdisciplinary treatment of the debate about labeling genetically modified food. The contributors include philosophers, bioethicists, food and agricultural scientists, attorneys/legal scholars, and economists.

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.

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.

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.

Collective rationality in its ordinary sense is rationality’s extension to groups. It does not entail efficiency by definition. Showing that it entails efficiency requires a normative argument. Game theorists treating cooperative games generally assume that collective rationality entails efficiency, but formulating the reasoning that leads individuals to efficiency, and verifying the rationality of its steps, presents challenging philosophical issues. This paper constructs a framework for addressing those issues and reaches some preliminary results about the prospects of rational agents achieving efficiency in coalitional games. It concludes that only under strong idealizations does collective rationality entail efficiency

Agents face serious obstacles to making optimal decisions. For instance, their cognitive limits stand in the way. John Pollock’s book, Thinking about Acting , suggests many ways of revising decision principles to accommodate human limits and to direct limited, artificial agents. The book’s main proposal is to replace optimization, or expected-utility maximization, with locally global planning. This essay describes optimization and locally global planning, and then argues that optimization among salient options has the virtues of locally global planning without certain drawbacks. Although it does not endorse locally global planning, it recommends that decision theory incorporate some of the book’s ideas about settling for improvements when optimization among all options is unrealistic.

This paper summarizes and rebuts the three standard objections made by social choice theorists against interpersonal utility. The first objection argues that interpersonal utility is measningless. I show that this objection either focuses on irrelevant kinds of meaning or else uses implausible criteria of meaningfulness. The second objection argues that interpersonal utility has no role to play in social choice theory. I show that on the contrary interpersonal utility is useful in formulating goals for social choice. The third objection argues that interpersonal utility in social choice theory can be replaced by clearer notions. I show that the replacements proposed are unsatisfactory in either interpersonal utility's descriptive or explanatory role. My conclusion is that interpersonal utility has a legitimate place in social choice theory.

To handle epistemic and pragmatic risks, Gärdenfors and Sahlin (1982, 1988) design a decision procedure for cases in which probabilities are indeterminate. Their procedure steps outside the traditional expected utility framework. Must it do this? Can the traditional framework handle risk? This paper argues that it can. The key is a comprehensive interpretation of an option's possible outcomes. Taking possible outcomes more broadly than Gärdenfors and Sahlin do, expected utility can give risk its due. In particular, Good's (1952) decision procedure adequately handles indeterminate probabilities and the risks they generate.

The conditional probability of h given e is commonly claimed to be equal to the probability that h would have if e were learned. Here I contend that this general claim about conditional probabilities is false. I present a counter-example that involves probabilities of probabilities, a second that involves probabilities of possible future actions, and a third that involves probabilities of indicative conditionals. In addition, I briefly defend these counter-examples against charges that the probabilities they involve are illegitimate