Foundations for Tracing Intuition

Challenges and Methods

Andreas Glöckner, Cilia Witteman, Andreas Glöckner, Cilia Witteman

• Publisher: Psychology Press
• Year: 2009
• Print ISBN: 9781848720190
• eBook ISBN: 9781135181451
• Topic: Psychology
• Subtopic: Cognitive Psychology & Cognition
• Index: Psychology

The study of intuition and its relation to thoughtful reasoning is a burgeoning research topic in psychology and beyond. While the area has the potential to radically transform our conception of the mind and decision making, the procedures used for establishing empirical conclusions have often been vaguely formulated and obscure. This book fills a gap in the field by providing a range of methods for exploring intuition experimentally and thereby enhancing the collection of new data.

The book begins by summarizing current challenges in the study of intuition and gives a new foundation for intuition research. Going beyond classical dual-process models, a new scheme is introduced to classify the different types of processes usually collected under the label of intuition. These new classifications range from learning approaches to complex cue integration models.

The book then goes on to describe the wide variety of behavioural methods available to investigate these processes, including information search tracing, think aloud protocols, maximum likelihood methods, eye-tracking, and physiological and non-physiological measures of affective responses. It also discusses paradigms to investigate implicit associations and causal intuitions, video-based approaches to expert research, methods to induce specific decision modes as well as questionnaires to assess individual preferences for intuition or deliberation.

By uniquely providing the basis for exploring intuition by introducing the different methods and their applications in a step-by-step manner, this text is an invaluable reference for individual research projects. It is also very useful as a course book for advanced decision making courses, and could inspire experimental explorations of intuition in psychology, behavioural economics, empirical legal studies and clinical decision making.

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Foundations for tracing intuition

Models, findings, categorizations

Andreas Glöckner and Cilia Witteman

Introduction

Every day people make a multitude of judgments and decisions which differ in complexity and importance. The question how people make these decisions has attracted research interest over many years. Why did some decisions which were based on long deliberation turn out to be bluntly wrong – leading to the break-down of mighty companies and organizations, to financial or political crisis and even wars? How can, on the other hand, complex decision tasks sometimes be solved in the blink of an eye? Obviously, processes that are not only based on deliberate, conscious information processing play a crucial role. We automatically record parts of the information we are confronted with, and are able to use this knowledge in later decisions. Parts of these processes concern conscious information selection, retrieval and processing, other parts operate completely automatically and unconsciously. Both kinds of processes interact. This could lead to a conscious overwriting of initial intuitive choice tendencies. The reverse could also happen: unconscious processes may modify the outcomes of seemingly completely deliberate decisions. They may lead us to act against our deliberate intentions, or they may generate feelings that one should select an option without knowing where this feeling comes from. They may produce vague feelings warning us that although all the facts speak for option A something feels wrong and another option should be selected, and they may even produce insights in complex tasks just in the moment when we stop deliberatively reflecting about them. These phenomena are as fascinating as they are complex and decision research has only just started to unravel them.

In November 2007 we conducted a workshop on Measuring Intuition and Expertise at the Max Planck Institute for Research on Collective Goods, Bonn. The aim of this workshop was to bring together decision researchers who have investigated expertise, intuition and the interplay of automatic and deliberate processes in decision making to present and discuss recent methodological approaches and to develop ideas for further methodological improvements. This volume is based on the talks presented there, and on the discussions held at and after the workshop. We aim to present different perspectives on intuition and different methodological approaches, which should enable graduate students and scientists from different fields (i.e., psychology, decision sciences, cognitive sciences, behavioural economics, and behavioural law and economics) to use them in their research. In this chapter we provide a theoretical basis for the different methodological approaches described in the rest of this volume.

What is intuition?

There are quite a few controversies surrounding the study of intuition. Controversy starts with the definition of intuition, and further concerns its properties, the scope and the homogeneity of the phenomenon, its working mechanism, its distinction from deliberation, its relatedness to affect, and its dependence on experience. To illustrate that there is partial agreement but also controversy about the definition of intuition, we cite four examples:

“The outcomes [of intuition] are typically approximate (not precise) and often experienced in the form of feelings (not words)” (p. 9). “The correlates are speed, and confidence” (p. 10). “Intuition or intuitive responses are reached with little apparent effort, and typically without conscious awareness; they involve little or no conscious deliberation” (p. 14) “[but are reached] in a largely tacit, unintentional, automatic, passive process” (p. 21). “We know, but we do not know why” (p. 29) (all in Hogarth, 2001).

Intuition is an involuntary, difficult-to-articulate, affect-laden recognition or judgment, based upon prior learning and experiences, which is arrived at rapidly, through holistic associations and without deliberative or conscious rational thought. (Sadler-Smith, 2008, p. 31)

Intuition is the way we translate our experiences into judgments and decisions. It’s the ability to make decisions using patterns to recognize what’s going on in a situation and to recognize the typical action scripts with which to react. Once experienced intuitive decision makers see a pattern, any decision they have to make is usually obvious. (Klein, 2003, p. 13)

Intuition is a process of thinking. The input to this process is mostly provided by knowledge stored in long-term memory that has been primarily acquired via associative learning. The input is processed automatically and without conscious awareness. The output of the process is a feeling that can serve as a basis for judgments and decisions. (Betsch, 2008, p. 4)

From the above definitions we derive the common ground which we will rely on in this volume: Most definitions agree that intuition is based on automatic processes which rely on knowledge structures that are acquired by different kinds of learning. They operate at least partially without people’s awareness and result in feelings, signals, or interpretations. Assumptions concerning the underlying processes and consequently also concerning further properties of these processes diverge. In this volume we refrain from trying to unify these perspectives. On the contrary, we suggest that intuition is used as a label for different kinds of automatic processes and we will aim to categorize them into four general types.

In this chapter, we will first discuss why tracing intuition is challenging, and we summarize some historical background to the investigation of intuition. Next the distinction between intuition and deliberation as well as assumptions concerning the interplay of both will be described. Then we turn to a discussion of the processes underlying intuition. We suggest a classification of types of intuition according to four rather different underlying learning and retrieval or information integration processes, and we sort existing models accordingly (see also Glöckner and Witteman, in press). Neuroscientific results are outlined that support the hypothesis that the processes exist and seem to operate at least partially independently. Turning back to the distinction between intuition and deliberation, different factors are described that are supposed to influence the activation of one or the other process. Also, the relation between intuition and expertise, as based on extensive learning, is briefly discussed. We show that the suggested types of intuition allow for rather similar predictions concerning when it will lead to good or bad decisions. Finally, the structure of the book is outlined.

The challenge of tracing intuition

The importance of improving our scientific understanding of intuitive processes in judgment and decision making has been prominently highlighted in several influential publications (e.g., Kahneman & Frederick, 2002; Plessner, Betsch, & Betsch, 2008). Automatic, intuitive processes seem to be particularly important for professional decision makers such as clinicians, managers, and judges (Agor, 1986; Beach, 1996; Glöckner, 2008b; Glöckner & Engel, 2008; Guthrie, Rachlinski, & Wistrich, 2007; Klein, 2003; Klein, Orasanu, Calderwood, & Zsambok, 1993), but these processes also enable lay persons to come to good decisions quickly (Glöckner & Betsch, 2008a, 2008b, 2008c; Glöckner & Dickert, under review; Glöckner & Herbold, in press). The theoretical and the practical importance of intuition have attracted many decision researchers to start investigating the topic empirically. However, there are at least four major challenges that “intuition” researchers face: ambiguity of the concept intuition and a multitude of models, under-specification of models, methodological challenges to trace unconscious processes, and interactions of the research method with cognitive processes.

Concerning the first point: intuition is used as a common label for a set of phenomena that are likely to be based on completely different cognitive mechanisms (cf. definitions above). Hence, it is probably a waste of time to ask the question what “intuition really is”. It is more fruitful to concentrate on one class of mechanisms and to investigate them first separately and later on in their interaction with other ones. We provide a simple classification of mechanisms below that reduces the multitude of models to a few basic processes that could be specifically explored.

Second, some models of intuition are still in the process of being elaborated and hence they are sometimes underspecified in that they do not allow the derivation of clear behavioural predictions. We advise researchers to focus on models that are well specified or to use (and explicate) additional specifying assumptions that make them testable (if not done so by the authors themselves) (see Glöckner, chapter 5, this volume; Glöckner & Herbold, in press). Note, however, that intuition is a phenomenon for complex information integration processes. That means that better specified models for intuition are usually mathematically somewhat complex (but see Gigerenzer, 2007). Researchers should take the time to understand the underlying concepts as well as the math and not focus on the simplest models only. Increasingly, computer tools are available to derive predictions from mathematically complex intuition models (see Glöckner, chapter 5, this volume; for materials and links see www.intuitive-experts.de – Resources).

Third, one of the major challenges for exploring automatic-intuitive processes is that some of the traditional methods used in behavioural decision research are simply not suitable for capturing implicit, unconscious processes or have to be modified to do so. In this volume we describe methods ranging from “technical” approaches such as information-search tracing via eye-tracking (Norman & Schulte-Mecklenbeck, chapter 2, this volume) or physiological measures (Hochman, Glöckner, & Yechiam, chapter 8, this volume) to applying classical behavioural approaches such as the analysis of choices (Bröder, chapter 4, this volume), decision times and confidence (Glöckner, chapter 5, this volume), the usage of verbal protocols (Witteman & van Geenen, chapter 3, this volume), and many more.

The final issue is closely related to the previous one. It has been shown that research methods such as computer-based information search paradigms (see Norman & Schulte-Mecklenbeck, chapter 2, this volume) influence whether persons rely on automatic-intuitive processes or whether they apply simple deliberate short-cut strategies (Glöckner & Betsch, 2008c). Hence, researchers should be very sensitive concerning the influence of context factors which are induced by the research method. Otherwise the results might not generalize to real world settings. This is particula...

Table of contents

• Contents
• Contributors
• 1 Foundations for tracing intuition
• 2 Take a quick click at that!
• 3 Cognitive process analysis
• 4 Outcome-based strategy classification
• 5 Multiple measure strategy classification
• 6 Studying experts’ intuitive decision making online using video stimuli
• 7 Implicit evaluation as a basis for intuition
• 8 Physiological measures in identifying decision strategies
• 9 Investigating causal intuitions
• 10 Measuring affect and emotions in decision making
• 11 Tracking memory search for cue information
• 12 Methods for inducing intuitive and deliberate processing modes
• 13 The internal validity of self-report measures for intuitive and rational decision making
• 14 Measuring individual differences in intuitive and deliberate decision-making styles
• 15 Tracing intuition
• Author index
• Subject index