Supercharged Sexism: The Triple Threat of Workplace Monitoring for Women

Elizabeth Brown
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引用次数: 3

Abstract

As biometric monitoring becomes increasingly common in workplace wellness programs, there are three reasons to believe that women will suffer disproportionately from the data collection associated with it. First, many forms of biometric monitoring are subject to gender bias, among other potential biases, because of assumptions inherent in the design and algorithms interpreting the collected data. Second, the expansion of femtech in particular creates a gender-imbalanced data source that may feed into existing workplace biases against women unless more effective safeguards emerge. Finally, many femtech platforms encourage the kind of information sharing that may reduce women’s reasonable expectations of privacy, especially with regard to fertility data, thus increasing the risk of health data privacy invasion. This triple threat to female workers may be offset somewhat by the benefits of health data collection at work and may be remedied at least in part by both legislative and non-legislative means. The current trend toward greater health data collection in the wake of COVID-19 should provoke a reexamination of how employers collect and analyze women’s health data in order to reduce the impact of these new gender bias drivers.
超级性别歧视:职场监控对女性的三重威胁
随着生物识别监测在工作场所健康计划中变得越来越普遍,有三个理由相信,与之相关的数据收集将给女性带来不成比例的损失。首先,由于解释收集数据的设计和算法中固有的假设,许多形式的生物识别监测存在性别偏见和其他潜在偏见。其次,femtech的扩张尤其会造成性别失衡的数据源,除非出现更有效的保障措施,否则可能助长现有的职场歧视女性的偏见。最后,许多妇女科技平台鼓励信息共享,这可能降低妇女对隐私的合理期望,特别是在生育数据方面,从而增加健康数据隐私被侵犯的风险。在工作中收集健康数据的好处可在一定程度上抵消对女工的这三重威胁,并可通过立法和非立法手段至少部分加以补救。在2019冠状病毒病(COVID-19)之后,当前的趋势是收集更多的健康数据,这应该促使人们重新审视雇主收集和分析女性健康数据的方式,以减少这些新的性别偏见驱动因素的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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