This article presents the results of an experiment, called the ABA experiment, designed to test a fundamental prediction of quantum probability theory when applied to human judgments and decisions. The prediction concerns the effect of one measurement on another when the measurements are incompatible (i.e., the answers to the measurements depend on the order of these measurements). After an initial measurement of an opinion on an issue, A, the answer to a second measurement on the same issue A immediately afterwards will certainly be the same as the first. However, according to the uncertainty principle, if a measurement of opinion on issue A is followed by an incompatible measurement on another issue, B, then the answer to a second measurement on issue A will become uncertain. This prediction was tested with 325 participants on a wide range of 12 different set of issues that were previously shown to be incompatible. Contrary to previous claims published in this journal, the empirical findings support the prediction of quantum probability theory applied to human judgments.
This article presents the results of an experiment, called the ABA experiment, designed to test a fundamental prediction of quantum probability theory when applied to human judgments and decisions. The prediction concerns the effect of one measurement on another when the measurements are incompatible (i.e., the answers to the measurements depend on the order of these measurements). After an initial measurement of an opinion on an issue, A, the answer to a second measurement on the same issue A immediately afterwards will certainly be the same as the first. However, according to the uncertainty principle, if a measurement of opinion on issue A is followed by an incompatible measurement on another issue, B, then the answer to a second measurement on issue A will become uncertain. This prediction was tested with 325 participants on a wide range of 12 different set of issues that were previously shown to be incompatible. Contrary to previous claims published in this journal, the empirical findings support the prediction of quantum probability theory applied to human judgments.
Recent findings show that human inferences and decisions interfere in ways analogous to incompatible quantum observables, and conceptual judgments are inseparable in ways similar to entangled quantum states.This discovery has led a group of physicists and psychologists to form a new field called "quantum cognition," which uses mathematical principles of quantum theory to explain human cognitive behavior.The power of this new theoretical approach is illustrated here by testing an a priori and precise prediction derived from quantum theory regarding question order effects commonly observed in survey research.The test of quantum theory was statistically satisfied across a set of 26 national surveys on presidential job approval and country satisfaction in past 10 years.These results suggest that quantum theory, initially invented to explain order effects on measurements in physics, provides a powerful prediction for measurement order effects in social and behavioral sciences too.
Can one really predict something new and interesting using quantum theory in the social or behavioral sciences? Consider the law of reciprocity described in Chapter 2: according to this law, the probability of transiting from one state to another is equal to the probability of making this transition in the opposite direction. Now this symmetrical property is a pretty bold prediction to make in the social and behavioral sciences. Does this really work? To answer this question, in this chapter we empirically test this law by applying the quantum principles to an important empirical problem concerning the effects of question order on attitude judgments. For example, suppose you are asked “How happy are you with life in general?” This question could be preceded or followed by the question “How happy are you with your marriage?” If the marriage question comes first, then the happiness rating for the general life question tends to be substantially depressed, producing a large order effect (Tourangeau et al ., 1991). Quantum physics was originally developed to understand how measurement affects the system under investigation, which led to Heisenberg's famous uncertainty principle. The potential reactivity to measurement by the person being measured has an even longer history in psychology (Tourangeau et al ., 2000). The effects of question order have been an important issue to survey researchers interested in studying beliefs and attitudes (Schuman & Presser, 1981). Measurement of a belief or attitude directs attention to a subset of a person's knowledge, which is then used in guiding subsequent judgments.
Uncertainty is an intrinsic part of life; most events, affairs, and questions are uncertain. A key problem in behavioral sciences is how the mind copes with uncertain information. Quantum probability theory offers a set of principles for inference, which align well with intuition about psychological processes in certain cases: cases when it appears that inference is contextual, the mental state changes as a result of previous judgments, or there is interference between different possibilities. We motivate the use of quantum theory in cognition and its key characteristics. For each of these characteristics, we review relevant quantum cognitive models and empirical support. The scope of quantum cognitive models encompasses fallacies in decision-making (such as the conjunction fallacy or the disjunction effect), question order effects, conceptual combination, evidence accumulation, perception, over-/underdistribution effects in memory, and more. Quantum models often formalize psychological ideas previously expressed in heuristic terms, allow unified explanations of previously disparate findings, and have led to several surprising, novel predictions. We also cast a critical eye on quantum models and consider some of their shortcomings and issues regarding their further development.
How can we use quantum theory to model other phenomena of interest to researchers in cognition and decision making? Quantum theory is not easy for researchers in cognition and decision making to accept. In fact, quantum mechanics was not easy for physicists to accept either, but it was forced on them by several paradoxical findings that could not be explained using classical physics. We have a similar problem in cognition and decision making – there are numerous paradoxical findings that just seem irrational according to classic probability theory. For example, under some conditions, people judge the probability of event A and B to be greater than the probability of event B , which is called the conjunction fallacy (Tversky & Kahneman, 1983). Also, under the same conditions, they judge the probability of A or B to be less than the probability of event A (Carlson & Yates, 1989), which is called the disjunction fallacy. In this chapter we examine how quantum probability theory explains these and other puzzling results from human probability judgment research. This chapter has two main parts. In the first part, we use a quantum model to derive qualitative predictions for conjunction errors, disjunction errors, and other closely related findings. The first section provides a general set of predictions that do not depend on specific assumptions about the features used to represent events, and the predictions are parameter free. In the second part, we examine the quantitative predictions of the quantum model for a Bayesian inference task, which we use to explain order effects on inference.
Question order effects are commonly observed in self-report measures of judgment and attitude. This article develops a quantum question order model (the QQ model) to account for four types of question order effects observed in literature. First, the postulates of the QQ model are presented. Second, an a priori, parameter-free, and precise prediction, called the QQ equality, is derived from these mathematical principles, and six empirical data sets are used to test the prediction. Third, a new index is derived from the model to measure similarity between questions. Fourth, we show that in contrast to the QQ model, Bayesian and Markov models do not generally satisfy the QQ equality and thus cannot account for the reported empirical data that support this equality. Finally, we describe the conditions under which order effects are predicted to occur, and we review a broader range of findings that are encompassed by these very same quantum principles. We conclude that quantum probability theory, initially invented to explain order effects on measurements in physics, appears to be a powerful natural explanation for order effects of self-report measures in social and behavioral sciences, too.
The hypothesis that human reasoning obeys the laws of quantum rather than classical probability has been used in recent years to explain a variety of seemingly "irrational" judgment and decision-making findings. This article provides independent evidence for this hypothesis based on an a priori prediction, called the quantum question (QQ) equality, concerning the effect of asking attitude questions successively in different orders. We empirically evaluated the predicted QQ equality using 70 national representative surveys and two laboratory experiments that manipulated question orders. Each national study contained 651-3,006 participants. The results provided strong support for the predicted QQ equality. These findings suggest that quantum probability theory, initially invented to explain noncommutativity of measurements in physics, provides a simple account for a surprising regularity regarding measurement order effects in social and behavioral science.