Designing technology for sociotechnical problems is challenging due to the heterogeneity of stakeholders’ needs, the diversity among their values and perspectives, and the disparity in their technical skills. Careful considerations are needed to ensure that data collection is inclusive and representative of the target populations. It is also important to employ data analysis methods that are compatible with users’ technical skills and are capable of drawing a representative picture of people's values, priorities, and needs. However, current technical solutions often fail to meet these critical requirements. In this article, we present a set of empirically-driven design considerations for building technological interventions to address sociotechnical issues. We then discuss open challenges and tradeoffs around privacy, ethics, bias, uncertainty, and trust. We conclude with a call to action for researchers to advance the domain knowledge and improve our technological arsenal for addressing sociotechnical problems.

中文翻译：

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为社会技术问题设计技术：挑战和考虑

由于利益相关者需求的异质性、价值观和观点的多样性以及技术技能的差异，为社会技术问题设计技术具有挑战性。需要仔细考虑以确保数据收集具有包容性并能代表目标人群。采用与用户的技术技能兼容并能够描绘出人们的价值观、优先事项和需求的代表性图片的数据分析方法也很重要。然而，当前的技术解决方案往往无法满足这些关键要求。在本文中，我们提出了一组经验驱动的设计考虑因素，用于构建技术干预以解决社会技术问题。然后我们讨论围绕隐私、道德、偏见、不确定性、和信任。最后，我们呼吁研究人员采取行动，推进领域知识并改进我们的技术库，以解决社会技术问题。