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While applications abound for the modern surge of artificial-intelligence (AI)-based technologies, we owe special care to those in which human lives are at stake . Perilously, AI advances faster than the regulations that protect us from it. As such, in this review, we explore the impact of AI on high-stakes decision-making. Though reviews have attempted adjacent analyses before, none have effectively targeted safety-critical industries or considered the relation between AI developers, users, and regulators. To address these gaps, we conduct a systematic literature review. We cast a wide net in our search of two databases, Web of Science and Scopus, then filter with a series of criteria that qualify a system’s sensitivity, decision-making framework, and risk. After distilling our initial pool of 1135 papers retrieved on December 15, 2025 into a final subset of 72 reports, we identify critical features of AI systems and industry implementation practices that demonstrate: (1) the safety risks of using AI in high-stakes decision-making, (2) how we can mitigate these risks, and (3) how we can assign responsibility for AI-based decisions. We perform a quality assessment, including risk of bias, on each study in our final corpus to ensure adequate rigor of retrieved material. We extract categorical and binary data from the articles reviewed to provide quantitative trends towards the types of AI used across the industries considered and the expertise of the end-user of these applications, as well as the decision-making time those users are allotted. We also perform a qualitative analysis of the trends described in these studies, on a per-industry basis.
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Panczyk et al. (2026) studied this question.
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