Paul Weirich

Weirich examines three competing views entertained by economic theory about the instrumental rationality of decisions: the first says to maximize self-interest, the second to maximize utility, and the third to satisfice, that is, to adopt a satisfactory option. Critics argue that the first view is too narrow, that the second overlooks the benefits of teamwork and planning, and that the third, when carefully formulated, reduces to the second. Weirich defends a refined version of the principle to maximize utility. A broad conception of utility makes it responsive to the motives and benefits critics allege it overlooks. He discusses generalizations of utility theory to extend it to nonquantitative cases and other cases with nonstandard features.

In a decision problem with a dynamic setting there is at least one option whose realization would change the expected utilities of options by changing the probability or utility function with respect to which the expected utilities of options are computed. A familiar example is Newcomb's problem. William Harper proposes a generalization of causal decision theory intended to cover all decision problems with dynamic settings, not just Newcomb's problem. His generalization uses Richard Jeffrey's ideas on ratifiability, and material from game theory on mixed strategies. Harper's proposal has two drawbacks, however. One concerns the mechanism for choosing among ratifiable options. The other concerns the proposal's reliance upon mixed strategies. Here I make another proposal that eliminates these two drawbacks.

Groups of people perform acts. For example, a committee passes a resolution, a team wins a game, and an orchestra performs a symphony. These collective acts may be evaluated for rationality. Take a committee’s passing a resolution. This act may be evaluated not only for fairness but also for rationality. Did it take account of all available information? Is the resolution consistent with the committee’s past resolutions? Standards of collective rationality apply to collective acts, that is, acts that groups of people perform. What makes a collective act evaluable for rationality? What methods of evaluation apply to collective acts? This paper addresses these two questions. Collective rationality is rationality’s extension from individuals to groups. The paper’s first few sections review key points about rationality. They identify the features of an individual’s act that make it evaluable for rationality and distinguish rationality’s methods of evaluating acts directly and indirectly controlled. This preliminary work yields general principles of rationality for all agents, both individuals and groups. Applying the general principles to groups answers the paper’s two main questions about collective rationality.

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

J. Howard Sobel has long been recognized as an important figure in philosophical discussions of rational decision. He has done much to help formulate the concept of causal decision theory. In this volume of essays Sobel explores the Bayesian idea that rational actions maximize expected values, where an action's expected value is a weighted average of its agent's values for its possible total outcomes. Newcomb's Problem and The Prisoner's Dilemma are discussed, and Allais-type puzzles are viewed from the perspective of causal world Bayesianism. The author establishes principles for distinguishing options in decision problems, and studies ways in which perfectly rational causal maximizers can be capable of resolute choices. Sobel also views critically Gauthier's revisionist ideas about maximizing rationality. This collection will be a desideratum for anyone working in the field of rational choice theory, whether in philosophy, economics, political science, psychology or statistics. Howard Sobel's work in decision theory is certainly among the most important, interesting and challenging that is being done by philosophers.

Theories of rationality advance principles that differ in topic, scope, and assumptions. A typical version of the principle of utility maximization formulates a standard rather than a procedure for decisions, evaluates decisions comprehensively, and relies on idealizations. I generalize the principle by removing some idealizations and making adjustments for their absence. The generalizations accommodate agents who have incomplete probability and utility assignments and are imperfectly rational. They also accommodate decision problems with unstable comparisons of options.

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.

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.

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.

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.