Phishing for (Quantum-Like) Phools—Theory and Experimental Evidence - HAL-SHS - Sciences de l'Homme et de la Société
Article Dans Une Revue Symmetry Année : 2021

Phishing for (Quantum-Like) Phools—Theory and Experimental Evidence

Résumé

Quantum-like decision theory is by now a theoretically well-developed field (see e.g., Danilov, Lambert-Mogiliansky & Vergopoulos, 2018). We provide a first test of the predictions of an application of this approach to persuasion. One remarkable result entails that, in contrast to Bayesian persuasion, distraction rather than relevant information has a powerful potential to influence decision-making. We first develop a quantum decision model of choice between two uncertain alternatives. We derive the impact of persuasion by means of distractive questions and contrast them with the predictions of the Bayesian model. Next, we provide the results from a first test of the theory. We conducted an experiment where respondents choose between supporting either one of two projects to save endangered species. We tested the impact of persuasion in the form of questions related to different aspects of the uncertain value of the two projects. The experiment involved 1253 respondents divided into three groups: a control group, a first treatment group and the distraction treatment group. Our main result is that, in accordance with the predictions of quantum persuasion but in violation with the Bayesian model, distraction significantly affects decision-making. Population variables play no role. Some significant variations between subgroups are exhibited and discussed. The results of the experiment provide support for the hypothesis that the manipulability of people’s decision-making can to some extent be explained by the quantum indeterminacy of their subjective representation of reality.

Dates et versions

halshs-03672290 , version 1 (19-05-2022)

Licence

Identifiants

Citer

Ariane Lambert-Mogiliansky, Adrian Calmettes. Phishing for (Quantum-Like) Phools—Theory and Experimental Evidence. Symmetry, 2021, 13 (2), ⟨10.3390/sym13020162⟩. ⟨halshs-03672290⟩
22 Consultations
0 Téléchargements

Altmetric

Partager

More