可解释性
计算机科学
人工智能
决策工程
商业决策图
决策质量
意外事故
人类智力
决策分析
集合(抽象数据类型)
授权
管理科学
知识管理
决策支持系统
管理
数学
工程类
哲学
经济
统计
程序设计语言
团队效能
语言学
作者
Yash Raj Shrestha,Shiko M. Ben-Menahem,Georg von Krogh
标识
DOI:10.1177/0008125619862257
摘要
How does organizational decision-making change with the advent of artificial intelligence (AI)-based decision-making algorithms? This article identifies the idiosyncrasies of human and AI-based decision making along five key contingency factors: specificity of the decision search space, interpretability of the decision-making process and outcome, size of the alternative set, decision-making speed, and replicability. Based on a comparison of human and AI-based decision making along these dimensions, the article builds a novel framework outlining how both modes of decision making may be combined to optimally benefit the quality of organizational decision making. The framework presents three structural categories in which decisions of organizational members can be combined with AI-based decisions: full human to AI delegation; hybrid—human-to-AI and AI-to-human—sequential decision making; and aggregated human–AI decision making.
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