To Err Is Human, to Correct Is Algorithmic
Across three studies and nine scenarios, we observe that people believe that algorithmic errors can be corrected, however, they do not believe that human errors can be similarly corrected. More specifically, people trust a previously erring algorithm after correction but lose confidence in an erring human even after correction.
Citation:
Chengyao Sun and Cynthia Cryder (2020) ,"To Err Is Human, to Correct Is Algorithmic", in NA - Advances in Consumer Research Volume 48, eds. Jennifer Argo, Tina M. Lowrey, and Hope Jensen Schau, Duluth, MN : Association for Consumer Research, Pages: 1227-1227.
Authors
Chengyao Sun, Washington University, USA
Cynthia Cryder, Washington University, USA
Volume
NA - Advances in Consumer Research Volume 48 | 2020
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