Debiasing Judgements Using a Distributed Cognition Approach: A Scoping Review of Technological Strategies.

IF 2.9 3区 心理学 Q1 BEHAVIORAL SCIENCES Human Factors Pub Date : 2024-10-26 DOI:10.1177/00187208241292897
Harini Dharanikota, Emma Howie, Lorraine Hope, Stephen J Wigmore, Richard J E Skipworth, Steven Yule
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引用次数: 0

Abstract

Objective: To review and synthesise research on technological debiasing strategies across domains, present a novel distributed cognition-based classification system, and discuss theoretical implications for the field.

Background: Distributed cognition theory is valuable for understanding and mitigating cognitive biases in high-stakes settings where sensemaking and problem-solving are contingent upon information representations and flows in the decision environment. Shifting the focus of debiasing from individuals to systems, technological debiasing strategies involve designing system components to minimise the negative impacts of cognitive bias on performance. To integrate these strategies into real-world practices effectively, it is imperative to clarify the current state of evidence and types of strategies utilised.

Methods: We conducted systematic searches across six databases. Following screening and data charting, identified strategies were classified into (i) group composition and structure, (ii) information design and (iii) procedural debiasing, based on distributed cognition principles, and cognitive biases, classified into eight categories.

Results: Eighty articles met the inclusion criteria, addressing 100 debiasing investigations and 91 cognitive biases. A majority (80%) of the identified debiasing strategies were reportedly effective, whereas fourteen were ineffective and six were partially effective. Information design strategies were studied most, followed by procedural debiasing, and group structure and composition. Gaps and directions for future work are discussed.

Conclusion: Through the lens of distributed cognition theory, technological debiasing represents a reconceptualisation of cognitive bias mitigation, showing promise for real-world application.

Application: The study results and debiasing classification presented can inform the design of high-stakes work systems to support cognition and minimise judgement errors.

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利用分布式认知方法消除判断偏差:技术策略范围综述》。
目的:回顾和总结各领域技术去蔽策略的研究,提出基于分布式认知的新型分类系统,并讨论该领域的理论意义:回顾和总结跨领域技术去伪存真策略的研究,提出一种新颖的基于分布式认知的分类系统,并讨论该领域的理论意义:分布式认知理论对于理解和减少高风险环境中的认知偏差非常有价值,在这种环境中,感知决策和问题解决取决于决策环境中的信息表征和流动。将消除偏差的重点从个人转移到系统,技术消除偏差策略涉及设计系统组件,以尽量减少认知偏差对绩效的负面影响。为了将这些策略有效地融入现实世界的实践中,必须明确当前的证据状况以及所使用策略的类型:我们对六个数据库进行了系统检索。经过筛选和绘制数据图表,确定的策略分为:(i) 小组组成和结构;(ii) 信息设计;(iii) 基于分布式认知原则的程序性去势;以及认知偏差,分为八类:符合纳入标准的文章有 80 篇,涉及 100 项除错调查和 91 项认知偏差。据报道,大多数(80%)已确定的除错策略是有效的,14 篇无效,6 篇部分有效。对信息设计策略的研究最多,其次是程序性排错以及群体结构和组成。本文讨论了差距和未来工作的方向:通过分布式认知理论的视角,技术去偏代表了对认知偏差缓解的重新认识,显示了在现实世界中应用的前景:应用:所介绍的研究结果和去偏差分类可为高风险工作系统的设计提供信息,以支持认知并最大限度地减少判断错误。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Human Factors
Human Factors 管理科学-行为科学
CiteScore
10.60
自引率
6.10%
发文量
99
审稿时长
6-12 weeks
期刊介绍: Human Factors: The Journal of the Human Factors and Ergonomics Society publishes peer-reviewed scientific studies in human factors/ergonomics that present theoretical and practical advances concerning the relationship between people and technologies, tools, environments, and systems. Papers published in Human Factors leverage fundamental knowledge of human capabilities and limitations – and the basic understanding of cognitive, physical, behavioral, physiological, social, developmental, affective, and motivational aspects of human performance – to yield design principles; enhance training, selection, and communication; and ultimately improve human-system interfaces and sociotechnical systems that lead to safer and more effective outcomes.
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