计算机科学
变量(数学)
信息系统
决策系统
运筹学
管理科学
决策支持系统
决策分析
项目管理
信息技术
系统设计
管理信息系统
采购
决策论
调度(生产过程)
人工智能
信息和通信技术
结构化系统分析与设计方法
风险分析(工程)
决策模型
知识管理
过程管理
证据推理法
最优决策
工业工程
决策过程
系统工程
商业决策图
生产(经济)
智能决策支持系统
决策树
标识
DOI:10.1080/01605682.2026.2753681
摘要
Artificial intelligence is changing organisational decision making as capabilities increasingly move towards autonomous decisions and actions. The central challenge has moved beyond discussion of whether humans or machines make better decisions. It is now focused on designing systems that combine AI with human judgement to improve decision quality. This article argues that human judgement in AI-enabled systems should be designed, allocated and evaluated at the system level, rather than treated as a binary safeguard. Human involvement can be configured according to where judgement enters the process, when intervention occurs, how much authority humans retain, and what form of judgement is required. This perspective shifts the unit of analysis from the individual decision maker or AI model to the human–AI decision system. This article highlights emerging risks involved in the expansion of accountability for AI-enabled decisions. It also identifies the expertise paradox where AI automates the work through which humans actually develop the experience needed to supervise autonomous systems. This creates an important research agenda to help design intelligent decision systems and the role of the decision maker itself.
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