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The Robotic Herd: Using Human-Bot Interactions to Explore Irrational Herding

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  • Verginer, Luca
  • Vaccario, Giacomo
  • Ronzani, Piero

Abstract

We explore human herding in a strategic setting where humans interact with automated entities (bots) and study the shift in the behavior and beliefs of humans when they are aware of interacting with bots. The strategic setting is an online minority game, where 1,997 participants are rewarded for following the minority strategy. This setting permits distinguishing between irrational herding and rational self-interest—a fundamental challenge in understanding herding in strategic contexts. Moreover, participants were divided into two groups: one informed of playing against bots (informed condition) and the other unaware (uninformed condition). Our findings revealed that while informed participants adjusted their beliefs about bots' behavior, their actual decisions remained largely unaffected. In both conditions, 30% of participants followed the majority, contrary to theoretical expectations of no herding. This study underscores the persistence of herding behavior in human decision-making, even when participants are aware of interacting with automated entities. The insights provide profound implications for understanding human behavior on digital platforms where interactions with bots are common.

Suggested Citation

  • Verginer, Luca & Vaccario, Giacomo & Ronzani, Piero, 2023. "The Robotic Herd: Using Human-Bot Interactions to Explore Irrational Herding," SocArXiv ajusq, Center for Open Science.
    • Handle: RePEc:osf:socarx:ajusq
    DOI: 10.31219/osf.io/ajusq
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    References listed on IDEAS

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    1. Jacob W. Crandall & Mayada Oudah & Tennom & Fatimah Ishowo-Oloko & Sherief Abdallah & Jean-François Bonnefon & Manuel Cebrian & Azim Shariff & Michael A. Goodrich & Iyad Rahwan, 2018. "Cooperating with machines," Nature Communications, Nature, vol. 9(1), pages 1-12, December.
      • Abdallah, Sherief & Bonnefon, Jean-François & Cebrian, Manuel & Crandall, Jacob W. & Ishowo-Oloko, Fatimah & Oudah, Mayada & Rahwan, Iyad & Shariff, Azim & Tennom,, 2017. "Cooperating with Machines," TSE Working Papers 17-806, Toulouse School of Economics (TSE).
      • Abdallah, Sherief & Bonnefon, Jean-François & Cebrian, Manuel & Crandall, Jacob W. & Ishowo-Oloko, Fatimah & Oudah, Mayada & Rahwan, Iyad & Shariff, Azim & Tennom,, 2017. "Cooperating with Machines," IAST Working Papers 17-68, Institute for Advanced Study in Toulouse (IAST).
      • Jacob Crandall & Mayada Oudah & Fatimah Ishowo-Oloko Tennom & Fatimah Ishowo-Oloko & Sherief Abdallah & Jean-François Bonnefon & Manuel Cebrian & Azim Shariff & Michael Goodrich & Iyad Rahwan, 2018. "Cooperating with machines," Post-Print hal-01897802, HAL.
    2. Thomas Lux & Michele Marchesi, 1999. "Scaling and criticality in a stochastic multi-agent model of a financial market," Nature, Nature, vol. 397(6719), pages 498-500, February.
    3. Anderson, Lisa R & Holt, Charles A, 1997. "Information Cascades in the Laboratory," American Economic Review, American Economic Association, vol. 87(5), pages 847-862, December.
    4. Iain D. Couzin & Jens Krause & Nigel R. Franks & Simon A. Levin, 2005. "Effective leadership and decision-making in animal groups on the move," Nature, Nature, vol. 433(7025), pages 513-516, February.
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