The Principle-at-Risk Analysis (PaRA): Operationalising Digital Ethics by Bridging Principles and Operations of a Digital Ethics Advisory Panel

IF 4.2 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Minds and Machines Pub Date : 2023-12-18 DOI:10.1007/s11023-023-09654-w
André T. Nemat, Sarah J. Becker, Simon Lucas, Sean Thomas, Isabel Gadea, Jean Enno Charton
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Abstract

Recent attempts to develop and apply digital ethics principles to address the challenges of the digital transformation leave organisations with an operationalisation gap. To successfully implement such guidance, they must find ways to translate high-level ethics frameworks into practical methods and tools that match their specific workflows and needs. Here, we describe the development of a standardised risk assessment tool, the Principle-at-Risk Analysis (PaRA), as a means to close this operationalisation gap for a key level of the ethics infrastructure at many organisations – the work of an interdisciplinary ethics panel. The PaRA tool serves to guide and harmonise the work of the Digital Ethics Advisory Panel at the multinational science and technology company Merck KGaA in alignment with the principles outlined in the company’s Code of Digital Ethics. We examine how such a tool can be used as part of a multifaceted approach to operationalise high-level principles at an organisational level and provide general requirements for its implementation. We showcase its application in an example case dealing with the comprehensibility of consent forms in a data-sharing context at Syntropy, a collaborative technology platform for clinical research.

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风险原则分析 (PaRA):通过衔接数字道德顾问小组的原则与操作,实现数字道德的可操作性
最近,人们试图制定和应用数字伦理原则,以应对数字转型带来的挑战,但这给组织留下了可操作性方面的空白。要成功实施此类指导,组织必须找到方法,将高层次的伦理框架转化为符合其具体工作流程和需求的实用方法和工具。在此,我们介绍了标准化风险评估工具--"风险原则分析"(PaRA)--的开发情况,以此来弥补许多组织伦理基础架构的关键层面--跨学科伦理小组工作--在操作性方面的差距。PaRA 工具用于指导和协调跨国科技公司默克公司数字道德顾问小组的工作,使其与公司《数字道德规范》中概述的原则保持一致。我们研究了如何将这种工具作为多层面方法的一部分,在组织层面落实高层次原则,并提供了实施该工具的一般要求。我们在 Syntropy(一个临床研究合作技术平台)的一个案例中展示了该工具的应用,该案例涉及数据共享背景下同意书的可理解性。
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来源期刊
Minds and Machines
Minds and Machines 工程技术-计算机:人工智能
CiteScore
12.60
自引率
2.70%
发文量
30
审稿时长
>12 weeks
期刊介绍: Minds and Machines, affiliated with the Society for Machines and Mentality, serves as a platform for fostering critical dialogue between the AI and philosophical communities. With a focus on problems of shared interest, the journal actively encourages discussions on the philosophical aspects of computer science. Offering a global forum, Minds and Machines provides a space to debate and explore important and contentious issues within its editorial focus. The journal presents special editions dedicated to specific topics, invites critical responses to previously published works, and features review essays addressing current problem scenarios. By facilitating a diverse range of perspectives, Minds and Machines encourages a reevaluation of the status quo and the development of new insights. Through this collaborative approach, the journal aims to bridge the gap between AI and philosophy, fostering a tradition of critique and ensuring these fields remain connected and relevant.
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