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Targeting in quantum persuasion problem

Author

Listed:
  • Vladimir I. Danilov

    (RAS - the Russian Academy of Sciences [Moscow, Russia])

  • Ariane Lambert-Mogiliansky

    (PJSE - Paris Jourdan Sciences Economiques - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris sciences et lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris sciences et lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

Abstract

In this paper we investigate the potential for persuasion arising from the quantum indeterminacy of a decision-maker's beliefs, a feature that has been proposed as a formal expression of well-known cognitive limitations. We focus on a situation where an agent called Sender only has few opportunities to influence the decision-maker called Receiver. We do not address the full persuasion problem but restrict attention to a simpler one that we call targeting, i.e. inducing a specific belief state. The analysis is developed within the frame of a -dimensional Hilbert space model. We find that when the prior is known, Sender can induce a targeted belief with a probability of at least when using two sequential measurements. This figure climbs to 1/2 when both the target and the belief are known pure states. A main insight from the analysis is that a well-designed strategy of distraction can be used as a first step to confuse Receiver. We thus find that distraction rather than the provision of relevant arguments is an effective means to achieve persuasion. We provide an example from political decision-making.

Suggested Citation

  • Vladimir I. Danilov & Ariane Lambert-Mogiliansky, 2018. "Targeting in quantum persuasion problem," Post-Print halshs-02088061, HAL.
  • Handle: RePEc:hal:journl:halshs-02088061
    DOI: 10.1016/j.jmateco.2018.04.005
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    References listed on IDEAS

    as
    1. Emir Kamenica & Matthew Gentzkow, 2011. "Bayesian Persuasion," American Economic Review, American Economic Association, vol. 101(6), pages 2590-2615, October.
    2. Vladimir Ivanovitch Danilov & Ariane Lambert-Mogiliansky, 2017. "Preparing a (quantum) belief system," Working Papers halshs-01542068, HAL.
    3. V. Danilov & A. Lambert-Mogiliansky, 2010. "Expected utility theory under non-classical uncertainty," Theory and Decision, Springer, vol. 68(1), pages 25-47, February.
    4. V. I. Danilov & A. Lambert-Mogiliansky & V. Vergopoulos, 2018. "Dynamic consistency of expected utility under non-classical (quantum) uncertainty," Theory and Decision, Springer, vol. 84(4), pages 645-670, June.
    5. Erev, Ido & Bornstein, Gary & Wallsten, Thomas S., 1993. "The Negative Effect of Probability Assessments on Decision Quality," Organizational Behavior and Human Decision Processes, Elsevier, vol. 55(1), pages 78-94, June.
    6. Ricardo Alonso & Odilon Câmara, 2016. "Persuading Voters," American Economic Review, American Economic Association, vol. 106(11), pages 3590-3605, November.
    7. George A. Akerlof & Robert J. Shiller, 2015. "Phishing for Phools: The Economics of Manipulation and Deception," Economics Books, Princeton University Press, edition 1, number 10534.
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