Context-Based Human Influence and Causal Responsibility for Assisted Decision-Making.

IF 2.9 3区心理学 Q1 BEHAVIORAL SCIENCES

Human Factors Pub Date : 2025-02-03 DOI:10.1177/00187208251317470

Yossef Saad, Joachim Meyer

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引用次数: 0

Abstract

Objective: The impact of the context in which automation is introduced to a decision-making system was analyzed theoretically and empirically.

Background: Previous work dealt with causality and responsibility in human-automation systems without considering the effects of how the automation's role is presented to users.

Methods: An existing analytical model for predicting the human contribution to outcomes was adapted to accommodate the context of automation. An aided signal detection experiment with 400 participants was conducted to assess the correspondence of observed behavior to model predictions.

Results: The context in which the automation's role is presented affected users' tendency to follow its advice. When automation made decisions, and users only supervised it, they tended to contribute less to the outcome than in systems where the automation had an advisory capacity. The adapted theoretical model for human contribution was generally aligned with participants' behavior.

Conclusion: The specific way automation is integrated into a system affects its use and the perceptions of user involvement, possibly altering overall system performance.

Application: The research can help design systems with automation-assisted decision-making and provide information on regulatory requirements and operational processes for such systems.

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来源期刊

Human Factors 管理科学-行为科学

CiteScore

10.60

自引率

6.10%

发文量

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.