Paul Weirich

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.

Decision theory aims at a general account of rationality covering humans but to begin makes idealizations about decision problems and agents' resources and circumstances. It treats inerrant agents with unlimited cognitive power facing tractable decision problems. This book systematically rolls back idealizations and without loss of precision treats errant agents with limited cognitive abilities facing decision problems without a stable top option. It recommends choices that maximize utility using quantizations of beliefs and desires in cases where probabilities and utilities are indeterminate and using higher-order utility analysis in cases of limited access to probabilities and utilities. For agents burdened with mistakes, it advocates reasonable attempts to correct unacceptable mistakes before deciding. In decision problems without a stable top option, a topic of game theory, it proposes maximizing self-conditional utility among self-supporting options. In games of strategy, the new principles lead to solutions that are Pareto optimal among equilibria composed of jointly self-supporting strategies. Offering an account of bounded rationality, the bookmakes large strides toward realism in decision theory.

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.

Food products with genetically modified 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.

How do rational agents coordinate in a single-stage, noncooperative game? Common knowledge of the payoff matrix and of each player's utility maximization among his strategies does not suffice. This paper argues that utility maximization among intentions and then acts generates coordination yielding a payoff-dominant Nash equilibrium. ‡I thank the audience at my paper's presentation at the 2006 PSA meeting for many insightful points. †To contact the author, please write to: Philosophy Department, University of Missouri, Columbia, MO 65211; e-mail: [email protected].

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.

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 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.