首页|Exploring the risks of automation bias in healthcare artificial intelligence applications:A Bowtie analysis
Exploring the risks of automation bias in healthcare artificial intelligence applications:A Bowtie analysis
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This study conducts an in-depth review and Bowtie analysis of automation bias in AI-driven Clinical Decision Support Systems(CDSSs)within healthcare settings.Automation bias,the tendency of human operators to over-rely on automated systems,poses a critical challenge in implementing AI-driven technologies.To address this challenge,Bowtie analysis is employed to examine the causes and consequences of automation bias affected by over-reliance on AI-driven systems in healthcare.Furthermore,this study proposes preventive measures to address automation bias during the design phase of AI model development for CDSSs,along with effective mitigation strategies post-deployment.The findings highlight the imperative role of a systems approach,integrating technological advancements,regulatory frameworks,and collaborative endeavors between AI developers and healthcare practitioners to diminish automation bias in AI-driven CDSSs.We further identify future research directions,proposing quantitative evaluations of the mitigation and preventative measures.
Artificial intelligenceAutomation biasDecision support systemsMedical errorsPatient safetyBowtie analysis
Moustafa Abdelwanis、Hamdan Khalaf Alarafati、Maram Muhanad Saleh Tammam、Mecit Can Emre Simsekler
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Department of Management Science and Engineering,Khalifa University of Science and Technology,Abu Dhabi,United Arab Emirates
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