在算法驱动的周期和生育跟踪技术中映射伦理问题。

Maria Carmen Punzi, Tamara Thuis
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引用次数: 0

摘要

经期和生育跟踪技术中算法的激增增加了对数据和分析的依赖,以解释月经周期症状并指导与健康和生育有关的行动。虽然这些技术旨在赋予用户管理月经和生育能力的权力,但在公平、自主、透明、责任和隐私方面出现了伦理问题。算法可能对用户的月经周期和生育相关体验和行为产生(通常是看不见的)影响,因此需要更多地关注此类技术的设计、使用和影响。本文描绘了算法的六个伦理问题——不确定的证据、不可理解的证据、被误导的证据、不公平的结果、变革性影响、可追溯性——以及周期和生育跟踪的相关后果,并强调了它们的潜在影响,特别是对弱势群体的潜在影响。基于这一映射,我们确定了三个总体主题,以进一步分析和调查个人用户、组织和社会层面的相互交织,以解决这些伦理问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mapping ethical concerns in algorithm-driven period and fertility tracking technologies.

Objective: The proliferation of algorithms in period and fertility tracking technologies has increased reliance on data and analytics to interpret menstrual cycle symptoms and guide health and fertility-related action. We set out to map the ethical concerns of the (often invisible) algorithmic influence on users' experience of, and behavior related to their menstrual cycle and fertility.

Study design: Reviewing literature and media, we map six ethical concerns of algorithms in period and fertility tracking technologies - inconclusive evidence, inscrutable evidence, misguided evidence, unfair outcomes, transformative effects, traceability - and highlight their potential implications, particularly for vulnerable groups.

Results: Based on this mapping, we identify three overarching themes for further analysis: self-knowledge, power and control, representation and inclusion. We find that organizational activity, individual user activity and societal dynamics interact with each other and influence how we can prevent and address the mapped ethical concerns of algorithms.

Conclusion: Algorithm-driven period and fertility tracking technologies carry more (and more nuanced) ethical concerns than those currently discussed in the literature and in media. We call for future research to integrate the ethics of (AI) algorithms into the field of sexual and reproductive health, recognizing the complex connections between individual, organizational, and societal levels.

Implications: When taking the mapped ethical concerns seriously, we see a potential for algorithm-driven period and fertility tracking technologies to empower - and not discriminate - its users; for users to learn about their bodies and use the technologies responsibly; and for society to actively scrutinize its biases and achieve health equity.

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