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Using an algorithmic approach to shape human decision-making through attraction to patterns

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  • Haran Shani-Narkiss

    (UCL Sainsbury Wellcome Centre for Neural Circuits and Behaviour)

  • Baruch Eitam

    (University of Haifa, Mount Carmel)

  • Oren Amsalem

    (Harvard Medical School)

Abstract

Evidence suggests that people are attracted to patterns and regularity. We hypothesized that decision-makers, intending to maximize profit, may be lured by the existence of regularity, even when it does not confer any additional value. An algorithm based on this premise outperformed all other contenders in an international challenge to bias individuals’ preferences. To create the bias, the algorithm allocates rewards in an evolving, yet easily trackable, pattern to one option but not the other. This leads decision-makers to prefer the regular option over the other 2:1, even though this preference proves to be relatively disadvantageous. The results support the idea that humans assign value to regularity and more generally, for the utility of qualitative approaches to human decision-making. They also suggest that models of decision making that are based solely on reward learning may be incomplete.

Suggested Citation

  • Haran Shani-Narkiss & Baruch Eitam & Oren Amsalem, 2025. "Using an algorithmic approach to shape human decision-making through attraction to patterns," Nature Communications, Nature, vol. 16(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-59131-4
    DOI: 10.1038/s41467-025-59131-4
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    References listed on IDEAS

    as
    1. Sebastian Bobadilla-Suarez & Cass R. Sunstein & Tali Sharot, 2017. "The intrinsic value of choice: The propensity to under-delegate in the face of potential gains and losses," Journal of Risk and Uncertainty, Springer, vol. 54(3), pages 187-202, June.
    2. repec:cup:judgdm:v:17:y:2022:i:4:p:768-796 is not listed on IDEAS
    3. repec:jdm:journl:v:17:y:2022:i:4:p:768-796 is not listed on IDEAS
    4. Ohad Dan & Ori Plonsky & Yonatan Loewenstein, 2025. "Behavior engineering using quantitative reinforcement learning models," Nature Communications, Nature, vol. 16(1), pages 1-10, December.
    5. Shoval, Roy & Karsh, Noam & Eitam, Baruch, 2022. "Choosing to choose or not," Judgment and Decision Making, Cambridge University Press, vol. 17(4), pages 768-796, July.
    6. Ohad Dan & Yonatan Loewenstein, 2019. "From choice architecture to choice engineering," Nature Communications, Nature, vol. 10(1), pages 1-4, December.
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