This book is a collection of papers presented at a conference, “Decision Making: Descriptive, Normative, and Prescriptive Interactions,” held in Boston at the Harvard Business School during June 16–18, 1983. The conference was one of several celebrating the 75th anniversary of the Harvard Business School. It might equally have been held as a celebration of the renaissance of interest in the analysis of decision making under uncertainty that has occurred in recent years. Not since the early 1950s, in the aftermath of the pathbreaking work by von Neumann and Morgenstern, has so much intellectual enthusiasm been directed at the question of how people should, and do, behave when called upon to take action in the face of uncertainty.

When Amos Tversky visited Harvard in the spring of 1982, the three of us had long discussions about the philosophy behind the contribution made by various disciplines to research on decision making. It was clear that mathematicians (decision theorists) are interested in proposing rational procedures for decision making – how people should make decisions if they wish to obey certain fundamental laws of behavior. Psychologists are interested in how people do make decisions (whether or not rational) and in determining the extent to which their behavior is compatible with any rational model. They are also interested in learning the cognitive capacities and limitations of ordinary people to process the information required of them if they do not naturally behave rationally, but wish to.

The focus of our attention is the individual decision maker facing a choice involving uncertainty about outcomes. We will consider how people do make decisions, how “rational” people should make decisions, and how we might help less rational people, who nevertheless aspire to rationality, to do better. When we speak of nonrational people, we do not mean those with diminished capacities; we refer instead to normal people who have not given thought to the process of decision making or, even if they have, are unable, cognitively, to implement the desired process. Our decision makers are not economic automatons; they make mistakes, have remorse, suffer anxieties, and cannot make up their minds. We start with a premise, not that people have well thought out preferences, but that they may be viewed as having divided minds with different aspirations, that decision making, even for the individual, is an act of compromise among the different selves.

For our purposes we shall augment the usual dichotomy that distinguishes between the normative and descriptive sides (the “ought” and the “is”) of decision making, by adding a third component: the prescriptive side. We do this because much of our concern in this paper addresses the question: “How can real people – as opposed to imaginary, idealized, super-rational people without psyches – make better choices in a way that does not do violence to their deep cognitive concerns?” And we find that much that we have to say on these matters does not fit conveniently into the usual normative or descriptive niches.

THE PROBLEM

Imagine that you will shortly be asked to consciously select one of several urns and from this urn you will then be asked to randomly select one ball. For the moment, we assume that each urn contains exactly N balls (say, 1,000), and each ball in the selected urn is equally likely to be chosen. Each ball has a number on it which specifies the incremental monetary return to you for drawing that ball.

Suppose that you have the opportunity to examine the balls and their numbers in all the urns before deciding upon your choice of urn. How would you use that opportunity? A useful answer to this question would have to take some account of the length of time available for your examination. Here we will adopt the view that time is available for any extensive analysis that you would care to make.

We will present three different but related techniques for choosing among urns. In order to decide when and for whom these techniques are appropriate, we shall discuss various behavioral assumptions that underlie each of these techniques. In mathematical parlance, we shall discuss necessary and sufficient behavioral assumptions that justify each of these techniques.

The papers in this volume are organized according to a few guiding principles.

The first dichotomy is between theory (20 papers) and application (8 papers).

Within the domain of theory we organized the papers into the following trichotomy:

1. (a) conceptions of choice (9 papers)

2. (b) beliefs and judgments about uncertainties (4 papers)

3. (c) values and utilities (7 papers)

Within each of these categories we arranged the papers according to the following sequence:

1. (a) decisions people make and how they decide

2. (b) logically consistent decision procedures and proposals of how people should decide

3. (c) behavioral objections to normative proposals

4. (d) how to help people to make better decisions in the light of behavioral realities and normative ideals

5. (e) how to train people to make better decisions, for example, by providing heuristics and, possibly, therapy

This sequence is motivated and elaborated in the overview paper by the editors (chapter 1).

In the application section, the papers are arranged by fields: economics, management, education, and medicine.

We, the organizers of this conference and its proceedings, in discussions among ourselves about our domain of concern – individual decision making under uncertainty – have found the following taxonomy helpful:

Descriptive

1. Decisions people make

2. How people decide

Normative

1. Logically consistent decision procedures

2. How people should decide

Prescriptive

1. How to help people to make good decisions

2. How to train people to make better decisions

Observe that we have moved from the usual dichotomy (descriptive and normative) to a trichotomy by adding a “prescriptive” category.

INTRODUCTION

We examine the connection between, and distinction between, decreasing marginal value (whatever that may mean) and risk aversion (from Pratt, 1964). When a decision maker (DM henceforth) declares indifference between $1,500 for certain and a 50–50 lottery with payoffs $0 and $5,000, the DM may have two concerns: (1) a feeling that going from $0 to $2,500 is “worth far more” than going from $2,500 to $5,000, and (2) being “nervous” about the uncertainty in the gamble. We will call the first concern “strength of preference” and the second concern “intrinsic risk aversion.” How much of the $1,000 difference between the arithmetical average of the gamble payoffs and the certainty equivalent is due to each of these concerns? Apart from a natural curiosity about such things we have other motivations:

1. (a) Many utility-assessment procedures currently rely heavily on answers to questions about gambles (e.g., Keeney and Raiffa, 1976); but decision makers are often uncomfortable with making choices among risky alternatives. Can alternative procedures that do not rely heavily on gambling questions be used justifiably?

2. (b) Many value-assessment procedures rely exclusively on strength-of-preference protocols (e.g., by comparing increments of gain or loss) and never confront subjects with risky choices. But some of these studies are then used to guide risky-choice options. […]