4.3 Article

Primer on an ethics of AI-based decision support systems in the clinic

期刊

JOURNAL OF MEDICAL ETHICS
卷 47, 期 12, 页码 -

出版社

BMJ PUBLISHING GROUP
DOI: 10.1136/medethics-2019-105860

关键词

decision-making; ethics

资金

  1. German Ministry for Health [ZMV/1-2517 FSB 013]
  2. German Ministry of Education and Research [01GP1903A]

向作者/读者索取更多资源

This article examines the challenges faced by clinical decision-making processes due to the emergence of artificial intelligence-driven decision support systems (AI-DSS), analyzing the impact on interactions between agents in the clinic and discussing implications for trustworthiness, transparency, normative concepts of agency, and responsibility ascriptions. Starting points for ensuring 'meaningful human control' over clinical AI-DSS are also discussed.
Making good decisions in extremely complex and difficult processes and situations has always been both a key task as well as a challenge in the clinic and has led to a large amount of clinical, legal and ethical routines, protocols and reflections in order to guarantee fair, participatory and up-to-date pathways for clinical decision-making. Nevertheless, the complexity of processes and physical phenomena, time as well as economic constraints and not least further endeavours as well as achievements in medicine and healthcare continuously raise the need to evaluate and to improve clinical decision-making. This article scrutinises if and how clinical decision-making processes are challenged by the rise of so-called artificial intelligence-driven decision support systems (AI-DSS). In a first step, this article analyses how the rise of AI-DSS will affect and transform the modes of interaction between different agents in the clinic. In a second step, we point out how these changing modes of interaction also imply shifts in the conditions of trustworthiness, epistemic challenges regarding transparency, the underlying normative concepts of agency and its embedding into concrete contexts of deployment and, finally, the consequences for (possible) ascriptions of responsibility. Third, we draw first conclusions for further steps regarding a 'meaningful human control' of clinical AI-DSS.

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