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Learning from machines: How negative feedback from machines improves learning between humans

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  • Zou, Tengjian
  • Ertug, Gokhan
  • Roulet, Thomas

Abstract

Prior studies on learning from failure primarily focus on how individuals learn from failure feedback given by other individuals. It is unclear whether and how the advent of machine feedback may influence individuals’ learning from failures. We suggest that failure feedback provided by machines facilitates learning in two ways. First, it focuses individuals’ attention on their failures, leading them to learn from these failures. Second, it serves as a catalyzer, motivating individuals to learn more from failure feedback given to them by other individuals as well. In addition, this catalyzing effect is stronger if the failure feedback from machines and by other individuals pertain to related tasks. Using a dataset of 1.5 million observations from an online programming contest community, we find support for our predictions. We contribute to the learning literature by demonstrating both the direct effect and the catalyzing effect of machine failure feedback on individuals’ learning.

Suggested Citation

  • Zou, Tengjian & Ertug, Gokhan & Roulet, Thomas, 2024. "Learning from machines: How negative feedback from machines improves learning between humans," Journal of Business Research, Elsevier, vol. 172(C).
    • Handle: RePEc:eee:jbrese:v:172:y:2024:i:c:s0148296323007762
    DOI: 10.1016/j.jbusres.2023.114417
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    References listed on IDEAS

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    1. Iyad Rahwan & Jacob W. Crandall & Jean-François Bonnefon, 2020. "Intelligent machines as social catalysts," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 117(14), pages 7555-7557, April.
    2. Boris Groysberg & Linda-Eling Lee & Ashish Nanda, 2008. "Can They Take It With Them? The Portability of Star Knowledge Workers' Performance," Management Science, INFORMS, vol. 54(7), pages 1213-1230, July.
    3. Hendrik Wilhelm & Andreas W. Richter & Thorsten Semrau, 2019. "Employee Learning from Failure: A Team-as-Resource Perspective," Organization Science, INFORMS, vol. 30(4), pages 694-714, July.
    4. Hirokazu Shirado & Nicholas A. Christakis, 2017. "Locally noisy autonomous agents improve global human coordination in network experiments," Nature, Nature, vol. 545(7654), pages 370-374, May.
    5. Joel A. C. Baum & Kristina B. Dahlin, 2007. "Aspiration Performance and Railroads’ Patterns of Learning from Train Wrecks and Crashes," Organization Science, INFORMS, vol. 18(3), pages 368-385, June.
    6. Sudip Bhattacharjee & Ram D. Gopal & Kaveepan Lertwachara & James R. Marsden & Rahul Telang, 2007. "The Effect of Digital Sharing Technologies on Music Markets: A Survival Analysis of Albums on Ranking Charts," Management Science, INFORMS, vol. 53(9), pages 1359-1374, September.
    7. Dahlin, Kristina & Chuang, You-Ta & Roulet, Thomas J, 2018. "Opportunity, Motivation, and Ability to Learn from Failures and Errors: Review, Synthesis, and Ways to Move Forward," SocArXiv 4qwzh, Center for Open Science.
    8. Linsu Kim, 1998. "Crisis Construction and Organizational Learning: Capability Building in Catching-up at Hyundai Motor," Organization Science, INFORMS, vol. 9(4), pages 506-521, August.
    9. Melissa A. Schilling & Patricia Vidal & Robert E. Ployhart & Alexandre Marangoni, 2003. "Learning by Doing Something Else: Variation, Relatedness, and the Learning Curve," Management Science, INFORMS, vol. 49(1), pages 39-56, January.
    10. Camelia M. Kuhnen & Agnieszka Tymula, 2012. "Feedback, Self-Esteem, and Performance in Organizations," Management Science, INFORMS, vol. 58(1), pages 94-113, January.
    11. Merle, Aurélie & St-Onge, Anik & Sénécal, Sylvain, 2022. "Does it pay to be honest? The effect of retailer-provided negative feedback on consumers’ product choice and shopping experience," Journal of Business Research, Elsevier, vol. 147(C), pages 532-543.
    12. Diwas KC & Bradley R. Staats & Francesca Gino, 2013. "Learning from My Success and from Others' Failure: Evidence from Minimally Invasive Cardiac Surgery," Management Science, INFORMS, vol. 59(11), pages 2435-2449, November.
    13. Victor Manuel Bennett & Jason Snyder, 2017. "The Empirics of Learning from Failure," Strategy Science, INFORMS, vol. 2(1), pages 1-12, March.
    14. Amankwah-Amoah, Joseph & Adomako, Samuel & Berko, Damoah Obi, 2022. "Once bitten, twice shy? The relationship between business failure experience and entrepreneurial collaboration," Journal of Business Research, Elsevier, vol. 139(C), pages 983-992.
    15. Margaret L. Traeger & Sarah Strohkorb Sebo & Malte Jung & Brian Scassellati & Nicholas A. Christakis, 2020. "Vulnerable robots positively shape human conversational dynamics in a human–robot team," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 117(12), pages 6370-6375, March.
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