Will Humans-in-the-Loop Become Borgs? Merits and Pitfalls of Working with AI

生物 人群 计算机科学 人工智能 数据科学 心理学 人机交互 知识管理 计算机安全 自然(考古学) 历史 考古
作者
Andreas Fügener,Jörn Grahl,Alok Gupta,Wolfgang Ketter
出处
期刊:Management Information Systems Quarterly [MIS Quarterly]
卷期号:45 (3): 1527-1556 被引量:106
标识
DOI:10.25300/misq/2021/16553
摘要

We analyze how advice from an AI affects complementarities between humans and AI, in particular what humans know that an AI does not know: “unique human knowledge.” In a multi-method study consisting of an analytical model, experimental studies, and a simulation study, our main finding is that human choices converge toward similar responses improving individual accuracy. However, as overall individual accuracy of the group of humans improves, the individual unique human knowledge decreases. Based on this finding, we claim that humans interacting with AI behave like “Borgs,” that is, cyborg creatures with strong individual performance but no human individuality. We argue that the loss of unique human knowledge may lead to several undesirable outcomes in a host of human–AI decision environments. We demonstrate this harmful impact on the “wisdom of crowds.” Simulation results based on our experimental data suggest that groups of humans interacting with AI are far less effective as compared to human groups without AI assistance. We suggest mitigation techniques to create environments that can provide the best of both worlds (e.g., by personalizing AI advice). We show that such interventions perform well individually as well as in wisdom of crowds settings.
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