Snow queen is evil and beautiful: Experimental evidence for probabilistic contextuality in human choices.

Cervantes, Víctor H.; Dzhafarov, Ehtibar N.

doi:10.1037/dec0000095

Cited by 92 publications

(95 citation statements)

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“…Based on the CbD analysis of many published experiments in none of which contextuality was found, it was tempting to hypothesize that all behavioral systems were noncontextual (Dzhafarov, Kujala, Cervantes, Zhang, & Jones, 2016;Dzhafarov, Zhang, & Kujala, 2015;. This hypothesis was rejected by recent crowdsourcing experiments (Basieva et al, in press;Cervantes & Dzhafarov, 2018), but the question remained open as to whether contextuality can also be observed in individual human behavior. In the crowdsourcing experiments the stimuli were questions to be answered in one of two ways.…”

Section: Discussionmentioning

confidence: 99%

“…When direct influences are taken into account, a large body of experimental data collected in search of contextuality can be shown to exhibit no contextuality (Dzhafarov, & Kujala, 2014;Dzhafarov, Kujala, Cervantes, Zhang, & Jones, 2016;Dzhafarov, Zhang, & Kujala, 2015). Nevertheless two very recent series of experiments unequivocally demonstrate that behavioral data (simple conjoint choices made by people) can be represented by contextual systems of random variables (Basieva, Cervantes, Dzhafarov, & Khrennikov, in press;Cervantes & Dzhafarov, 2018). These experiments dealt with responses aggregated over large pools of people, with each person making choices within a single conteXt.…”

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confidence: 99%

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True contextuality in a psychophysical experiment

Cervantes

Dzhafarov

2019

Journal of Mathematical Psychology

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Recent crowdsourcing experiments have shown that true contextuality of the kind found in quantum mechanics can also be present in human behavior. In these experiments simple human choices were aggregated over large numbers of respondents, with each respondent dealing with a single context (set of questions asked). In this paper we present experimental evidence of contextuality in individual human behavior, in a psychophysical experiment with repeated presentations of visual stimuli in randomly varying conteXts (arrangements of stimuli). The analysis is based on the Contextuality-by-Default (CbD) theory whose relevant aspects are reviewed in the paper. CbD allows one to detect contextuality in the presence of direct influences, i.e., when responses to the same stimuli have different distributions in different contexts. The experiment presented is also the first one in which contextuality is demonstrated for responses that are not dichotomous, with five options to choose among. CbD requires that random variables representing such responses be dichotomized before they are subjected to contextuality analysis. A theorem says that a system consisting of all possible dichotomizations of responses has to be contextual if these responses violate a certain condition, called nominal dominance. In our experiment nominal dominance was violated in all data sets, with very high statistical reliability established by bootstrapping.

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%

True contextuality in a psychophysical experiment

Cervantes

Dzhafarov

2019

Journal of Mathematical Psychology

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“…The general definition, provided in the Supplementary Material, encompasses the definition here and is conceptually similar but more technical. Given this definition, Cervantes and Dzhafarov's no-conspiracy principle [8] can be formalized as a prohibition against models with hidden direct influences, or equivalently a restriction to aligned models.…”

Section: Direct Influence In Causal Modelsmentioning

confidence: 99%

Relating causal and probabilistic approaches to contextuality

Jones

2019

Phil. Trans. R. Soc. A.

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A primary goal in recent research on contextuality has been to extend this concept to cases of inconsistent connectedness, where observables have different distributions in different contexts. This article proposes a solution within the framework of probabi- listic causal models, which extend hidden-variables theories, and then demonstrates an equivalence to the contextuality-by-default (CbD) framework. CbD distinguishes contextuality from direct influences of context on observables, defining the latter purely in terms of probability distributions. Here, we take a causal view of direct influences, defining direct influence within any causal model as the probability of all latent states of the system in which a change of context changes the outcome of a measurement. Model-based contextuality (M-contextuality) is then defined as the necessity of stronger direct influences to model a full system than when considered individually. For consistently connected systems, M-contextuality agrees with standard contextuality. For general systems, it is proved that M-contextuality is equivalent to the property that any model of a system must contain ‘hidden influences’, meaning direct influences that go in opposite directions for different latent states, or equivalently signalling between observers that carries no information. This criterion can be taken as formalizing the ‘no-conspiracy’ principle that has been proposed in connection with CbD. M-contextuality is then proved to be equivalent to CbD-contextuality, thus providing a new interpretation of CbD-contextuality as the non-existence of a model for a system without hidden direct influences. This article is part of the theme issue ‘Contextuality and probability in quantum mechanics and beyond’.

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“…Regardless of how strictly these stimuli (properties) are controlled, stochasticity in the responses (measurements) cannot be reduced by nontrivial amounts. In addition, however, psychological experiments exhibit the property of non-selectivity in responses to several stimuli: when the task is to respond to stimulus x and to respond to stimulus y, then x almost always, if not always, influences the distribution of responses to y, and vice versa (Cervantes & Dzhafarov, 2018;Dzhafarov, Zhang, & Kujala, 2015). In this respect behavioral systems differ from some quantum physical systems, those in which quantum theory includes "no-signaling" or "no-disturbance" constraints.…”

Section: On "Mental Signaling"mentioning

confidence: 99%

On universality of classical probability with contextually labeled random variables: Response to A. Khrennikov

Dzhafarov

Kon

2019

Journal of Mathematical Psychology

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In his constructive and well-informed commentary, Andrei Khrennikov acknowledges a privileged status of classical probability theory with respect to statistical analysis. He also sees advantages offered by the Contextuality-by-Default theory, notably, that it "demystifies quantum mechanics by highlighting the role of contextuality," and that it can detect and measure contextuality in inconsistently connected systems. He argues, however, that classical probability theory may have difficulties in describing empirical phenomena if they are described entirely in terms of observable events. We disagree: contexts in which random variables are recorded are as observable as the variables' values. Khrennikov also argues that the Contextuality-by-Default theory suffers the problem of non-uniqueness of couplings. We disagree that this is a problem: couplings are all possible ways of imposing counterfactual joint distributions on random variables that de facto are not jointly distributed. The uniqueness of modeling experiments by means of quantum formalisms brought up by Khrennikov is achieved for the price of additional, substantive assumptions. This is consistent with our view of quantum theory as a special-purpose generator of classical probabilities. Khrennikov raises the issue of "mental signaling," by which he means inconsistent connectedness in behavioral systems. Our position is that it is as inherent to behavioral systems as their stochasticity.

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Snow queen is evil and beautiful: Experimental evidence for probabilistic contextuality in human choices.

Cited by 92 publications

References 37 publications

True contextuality in a psychophysical experiment

True contextuality in a psychophysical experiment

Relating causal and probabilistic approaches to contextuality

On universality of classical probability with contextually labeled random variables: Response to A. Khrennikov

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