Partner or subordinate? Sequential risky decision-making behaviors under human-machine collaboration contexts

计算机科学 群体决策 认知心理学 知识管理 社会心理学 心理学
作者
Xiong Wei,Chen Wang,Liang Ma
出处
期刊:Computers in Human Behavior [Elsevier]
卷期号:139: 107556-107556 被引量:5
标识
DOI:10.1016/j.chb.2022.107556
摘要

Human-machine teaming has shown great potential in sequential risky decision-making (SRDM), and it is promising that machines will no longer work as subordinates. Technical advances prompt people to consider the contexts of humans and machines sharing decision authority. This study aims to compare task performance, human behaviors, and subjective perception of machines in a human-dominated team (machine as a subordinate) versus a human-machine joint team (machine as a partner). We modified the Balloon Analogue Risk Task (BART) experiment to include a highly accurate machine and accommodate two types of human-machine teams (HMTs). The results showed that both HMTs yielded comparable task performance and overperformed human or machine deciding alone. In the human-machine joint team, the machine as a partner entailed human decision-makers to cede power and coordinate, and their pumping decisions became more conservative and fluctuating. Moreover, human decision-makers reacted more sensitively to the different results of the last trial. Although subjects generally favored working with a machine subordinate, they exhibited similar trust levels in both HMTs after sufficient interaction. Our preliminary findings show that allocating a partial decision authority to highly accurate machines changed human behaviors without impairing task performance or trust in collaboration.
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