摘要
人工智能(AI)辅助决策给管理者带来决策效能的提高,但当AI出现错误,决策者如不加以验证A1建议准确性就采纳其建议,将会导致严重错误.对人类使用AI过程中的自动化偏差的概念、行为规律、作用机制、影响要素等进行系统述评发现,自动化偏差具有跨领域发展的趋势,呈现过度依赖、降低警觉性和忽视验证、个体差异.性等特点.可以从系统、环境、组织和个体等4个方面归纳影响自动化偏差的主要因素,分别涉及包括智能系统能否提供预测性信息以及系统能否即时反馈错误,决策支持系统设计、任务难度、工作量、任务复杂性、时间限制、对整体表现或决策准确性负责、信任和信心、知识水平的高低、能力等.未来应加强对企业管理者受AI自动化偏差影响的实证研究,同时要综合系统、环境、组织和个体要素揭示自动化偏差的形成机制,并制定出有效的去偏方案,帮助决策者正确利用AI辅助决策.
Abstract
Artificial intelligence(AI)-assisted decision-making significantly enhances managerial effectiveness.However,when AI makes errors,uncritical adoption of their suggestions by decision-makers can lead to severe consequences.This paper systematically reviews the concept,behavioral patterns,mechanisms,and influencing factors of automation bias in the context of AI utilization,using a comprehensive literature review approach.The findings highlight a growing trend of cross-domain development in automation bias,characterized by excessive reliance on AI,reduced vigilance,neglect of verification,and individual differences.The key factors influencing automation bias can be grouped into four dimensions:system,environment,organization,and individual.Specific elements include the systems'ability to provide predictive information and immediate error feedback,the design of decision support systems,task complexity,workload,time constraints,accountability for overall performance or decision accuracy,trust and confidence,knowledge level,and capabilities.Future research should focus on empirical studies exploring the effects of AI automation bias on corporate managers,incorporating system,environment,organization,and individual factors to uncover its underlying mechanisms.Moreover,the development of effective debiasing strategies is essential to help decision-makers utilize AI responsibly and accurately in decision-making processes.
维普
万方数据