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不同严重程度决策情况下对算法的抵触程度。

The extent of algorithm aversion in decision-making situations with varying gravity.

机构信息

Faculty of Business, Ostfalia University of Applied Sciences, Wolfsburg, Germany.

Faculty of Economic Sciences, Georg August University Göttingen, Göttingen, Germany.

出版信息

PLoS One. 2023 Feb 21;18(2):e0278751. doi: 10.1371/journal.pone.0278751. eCollection 2023.

DOI:10.1371/journal.pone.0278751
PMID:36809526
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9942970/
Abstract

Algorithms already carry out many tasks more reliably than human experts. Nevertheless, some subjects have an aversion towards algorithms. In some decision-making situations an error can have serious consequences, in others not. In the context of a framing experiment, we examine the connection between the consequences of a decision-making situation and the frequency of algorithm aversion. This shows that the more serious the consequences of a decision are, the more frequently algorithm aversion occurs. Particularly in the case of very important decisions, algorithm aversion thus leads to a reduction of the probability of success. This can be described as the tragedy of algorithm aversion.

摘要

算法已经比人类专家更可靠地执行许多任务。然而,一些人对算法有抵触情绪。在某些决策情况下,错误可能会产生严重的后果,而在其他情况下则不会。在框架实验的背景下,我们研究了决策情况的后果与算法抵触的频率之间的联系。这表明,决策的后果越严重,算法抵触的频率就越高。特别是在非常重要的决策中,算法抵触会导致成功的概率降低。这可以被描述为算法抵触的悲剧。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13f7/9942970/d3fdc5dc0672/pone.0278751.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13f7/9942970/d1a8f982c1b7/pone.0278751.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13f7/9942970/b2d76247a177/pone.0278751.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13f7/9942970/d3fdc5dc0672/pone.0278751.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13f7/9942970/d1a8f982c1b7/pone.0278751.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13f7/9942970/b2d76247a177/pone.0278751.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13f7/9942970/d3fdc5dc0672/pone.0278751.g003.jpg

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