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Do We Learn From Each Other: Understanding the Human-AI Co-Learning Process Embedded in Human-AI Collaboration

Author

Listed:
  • Jinwei Lu

    (Renmin University of China)

  • Yikuan Yan

    (Renmin University of China)

  • Keman Huang

    (Renmin University of China
    MIT Sloan)

  • Ming Yin

    (Purdue University)

  • Fang Zhang

    (Tsinghua University)

Abstract

Beyond collaborating in the AI-supported decision-making setting to achieve complementary performance, human and AI should learn from each other and internalize knowledge from their collaboration. This can enhance their individual performance when working independently after their collaboration. However, this expected dual-pathway co-learning process, including both “human learns from AI” and “AI learns from human”, does not occur spontaneously. Human-AI collaboration designs could have inconsistent and intertwined influences on the co-learning process. Based on the learning cycle theory, this study conducted three online, two-stage, and between-subject behavioral experiments to reveal how human and AI learn from each other. By developing a context where human and AI have comparable and moderate performance on emotion classification tasks, our study provides the first empirical evidence of an effective human-AI co-learning process within human-AI collaboration. However, the AI feedback and collaborative workflow design can lead to unequal and potentially negative impacts on both pathways of the co-learning process in groups with varying levels of cognitive reflection capability. These findings highlight three design principles to facilitate the co-learning process embedded in human-AI collaboration rather than naively deploying a complex AI system.

Suggested Citation

  • Jinwei Lu & Yikuan Yan & Keman Huang & Ming Yin & Fang Zhang, 2025. "Do We Learn From Each Other: Understanding the Human-AI Co-Learning Process Embedded in Human-AI Collaboration," Group Decision and Negotiation, Springer, vol. 34(2), pages 235-271, April.
  • Handle: RePEc:spr:grdene:v:34:y:2025:i:2:d:10.1007_s10726-024-09912-x
    DOI: 10.1007/s10726-024-09912-x
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    References listed on IDEAS

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    1. Shane Frederick, 2005. "Cognitive Reflection and Decision Making," Journal of Economic Perspectives, American Economic Association, vol. 19(4), pages 25-42, Fall.
    2. Henner Gimpel & Vanessa Graf-Seyfried & Robert Laubacher & Oliver Meindl, 2023. "Towards Artificial Intelligence Augmenting Facilitation: AI Affordances in Macro-Task Crowdsourcing," Group Decision and Negotiation, Springer, vol. 32(1), pages 75-124, February.
    3. Dominik Siemon, 2022. "Elaborating Team Roles for Artificial Intelligence-based Teammates in Human-AI Collaboration," Group Decision and Negotiation, Springer, vol. 31(5), pages 871-912, October.
    4. Reyhan Aydoğan & Tim Baarslag & Enrico Gerding, 2021. "Artificial Intelligence Techniques for Conflict Resolution," Group Decision and Negotiation, Springer, vol. 30(4), pages 879-883, August.
    Full references (including those not matched with items on IDEAS)

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