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当任务变得更加困难时,人类更多地依赖算法而不是社会影响。

Humans rely more on algorithms than social influence as a task becomes more difficult.

机构信息

Management Information Systems Department, University of Georgia, Athens, GA, 30602, USA.

出版信息

Sci Rep. 2021 Apr 13;11(1):8028. doi: 10.1038/s41598-021-87480-9.

Abstract

Algorithms have begun to encroach on tasks traditionally reserved for human judgment and are increasingly capable of performing well in novel, difficult tasks. At the same time, social influence, through social media, online reviews, or personal networks, is one of the most potent forces affecting individual decision-making. In three preregistered online experiments, we found that people rely more on algorithmic advice relative to social influence as tasks become more difficult. All three experiments focused on an intellective task with a correct answer and found that subjects relied more on algorithmic advice as difficulty increased. This effect persisted even after controlling for the quality of the advice, the numeracy and accuracy of the subjects, and whether subjects were exposed to only one source of advice, or both sources. Subjects also tended to more strongly disregard inaccurate advice labeled as algorithmic compared to equally inaccurate advice labeled as coming from a crowd of peers.

摘要

算法已经开始涉足传统上由人类判断来完成的任务,并且在新颖、困难的任务中越来越能够出色地完成。与此同时,社会影响(通过社交媒体、在线评论或个人网络)是影响个人决策的最有力因素之一。在三个预先注册的在线实验中,我们发现随着任务变得更加困难,人们相对于社会影响更依赖算法建议。这三个实验都集中在一个有正确答案的智力任务上,发现随着难度的增加,被试者更依赖算法建议。即使控制了建议的质量、被试者的计算能力和准确性,以及被试者是否只接触到一种来源的建议,或者两种来源的建议,这种效果仍然存在。与被标记为来自人群的同等不准确的建议相比,被试者也更倾向于强烈忽视被标记为算法的不准确建议。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d36/8044128/09b9a7757361/41598_2021_87480_Fig1_HTML.jpg

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