Medical Ethics With Focus on Digitization, Joint Faculty of Health Sciences Brandenburg, University of Potsdam, Potsdam, Germany.
Faculty of Educational Sciences, University of Duisburg-Essen, Essen, Germany.
J Med Internet Res. 2023 Jun 28;25:e45112. doi: 10.2196/45112.
Digital contact tracing algorithms (DCTAs) have emerged as a means of supporting pandemic containment strategies and protecting populations from the adverse effects of COVID-19. However, the impact of DCTAs on users' privacy and autonomy has been heavily debated. Although privacy is often viewed as the ability to control access to information, recent approaches consider it as a norm that structures social life. In this regard, cultural factors are crucial in evaluating the appropriateness of information flows in DCTAs. Hence, an important part of ethical evaluations of DCTAs is to develop an understanding of their information flow and their contextual situatedness to be able to adequately evaluate questions about privacy. However, only limited studies and conceptual approaches are currently available in this regard.
This study aimed to develop a case study methodology to include contextual cultural factors in ethical analysis and present exemplary results of a subsequent analysis of 2 different DCTAs following this approach.
We conducted a comparative qualitative case study of the algorithm of the Google Apple Exposure Notification Framework as exemplified in the German Corona Warn App and the Japanese approach of Computation of Infection Risk via Confidential Locational Entries (CIRCLE) method. The methodology was based on a postphenomenological perspective, combined with empirical investigations of the technological artifacts within their context of use. An ethics of disclosure approach was used to focus on the social ontologies created by the algorithms and highlight their connection to the question about privacy.
Both algorithms use the idea of representing a social encounter of 2 subjects. These subjects gain significance in terms of risk against the background of a representation of their temporal and spatial properties. However, the comparative analysis reveals 2 major differences. Google Apple Exposure Notification Framework prioritizes temporality over spatiality. In contrast, the representation of spatiality is reduced to distance without any direction or orientation. However, the CIRCLE framework prioritizes spatiality over temporality. These different concepts and prioritizations can be seen to align with important cultural differences in considering basic concepts such as subject, time, and space in Eastern and Western thought.
The differences noted in this study essentially lead to 2 different ethical questions about privacy that are raised against the respective backgrounds. These findings have important implications for the ethical evaluation of DCTAs, suggesting that a culture-sensitive assessment is required to ensure that technologies fit into their context and create less concern regarding their ethical acceptability. Methodologically, our study provides a basis for an intercultural approach to the ethics of disclosure, allowing for cross-cultural dialogue that can overcome mutual implicit biases and blind spots based on cultural differences.
数字接触追踪算法（DCTAs）已成为支持大流行防控策略和保护人群免受 COVID-19 不利影响的一种手段。然而，DCTAs 对用户隐私和自主权的影响引发了激烈的争论。尽管隐私通常被视为控制信息访问的能力，但最近的方法将其视为构建社会生活的规范。在这方面，文化因素对于评估 DCTAs 中的信息流至关重要。因此，DCTAs 伦理评估的一个重要部分是了解其信息流及其上下文情境，以便能够充分评估隐私问题。然而，在这方面，目前只有有限的研究和概念方法可用。
本研究旨在开发一种案例研究方法，将上下文文化因素纳入伦理分析，并展示随后按照这种方法对两种不同 DCTAs 进行分析的示例结果。
我们对谷歌苹果接触暴露通知框架的算法进行了比较定性案例研究，该算法在德国 Corona Warn App 中得到了体现，并对日本的计算感染风险方法（CIRCLE）进行了分析。该方法基于后现象学的观点，结合了对技术人工制品在其使用情境中的实证研究。披露伦理方法被用于关注算法创建的社会本体论，并强调它们与隐私问题的联系。
这两种算法都使用了代表两个主体社交接触的想法。这些主体在代表其时间和空间属性的背景下，在风险方面具有重要意义。然而，比较分析揭示了两个主要差异。谷歌苹果接触暴露通知框架优先考虑时间性而不是空间性。相比之下，空间性的表示简化为距离，而没有任何方向或方位。然而，CIRCLE 框架优先考虑空间性而不是时间性。这些不同的概念和优先级可以被视为与东方和西方思想中主体、时间和空间等基本概念的重要文化差异相一致。
本研究中注意到的差异实质上导致了在各自背景下提出的关于隐私的两个不同的伦理问题。这些发现对 DCTAs 的伦理评估具有重要意义，表明需要进行文化敏感评估，以确保技术适应其背景，减少对其伦理可接受性的关注。从方法论的角度来看，我们的研究为披露伦理的跨文化方法提供了基础，允许进行基于文化差异的跨文化对话，克服相互隐含的偏见和盲点。
