 Learning from machines: How negative feedback from machines improves learning between humansTengjian Zou, Gokhan Ertug and Thomas Roulet Journal of Business Research, 2024, vol. 172, issue C 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. Keywords: Learning; Failure; Machine-human interaction (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:172:y:2024:i:c:s0148296323007762 DOI: 10.1016/j.jbusres.2023.114417 Access Statistics for this article Journal of Business Research is currently edited by A. G. Woodside More articles in Journal of Business Research from Elsevier |
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