Frontline staff of emergency shelters face challenges such as vicarious trauma, compassion fatigue, and burnout. The technology they use is often not designed for their unique needs, and can feel burdensome on top of their already cognitively and emotionally taxing work. While existing literature focuses on data-driven technologies that automate or streamline frontline decision-making about vulnerable individuals, we discuss scenarios in which staff may resist such automation. We then suggest how data-driven technologies can better align with their human-centred decision-making processes. This paper presents findings from a qualitative fieldwork study conducted from 2022 to 2024 at a large emergency shelter in Canada. The goal of this fieldwork was to co-design, develop, and deploy an interactive data-navigation interface that supports frontline staff when making collaborative, high-stakes decisions about individuals experiencing homelessness. By reflecting on this fieldwork, we contribute insight into the role that administrative shelter data play during decision-making, and unpack staff members' apparent reluctance to outsource decisions about vulnerable individuals to data systems. Our findings suggest a data-outsourcing continuum, which we discuss in terms of how designers may create technologies to support compassionate, data-driven decision-making in nonprofit domains.

翻译：紧急庇护所的一线工作人员面临着替代性创伤、同情疲劳和职业倦怠等挑战。他们所使用的技术往往并非针对其独特需求而设计，在其本已消耗大量认知与情感资源的工作之上，可能带来额外负担。现有文献主要关注自动化或简化针对弱势个体的一线决策的数据驱动技术，而本文则探讨了工作人员可能抵制此类自动化的场景。我们进而提出数据驱动技术如何能更好地契合其以人为本的决策流程。本文呈现了2022年至2024年在加拿大一家大型紧急庇护所进行的定性实地调研结果。该调研旨在共同设计、开发并部署一个交互式数据导航界面，以支持一线工作人员在针对无家可归者进行协作性高风险决策时使用。通过对该实地调研的反思，我们深入揭示了行政庇护数据在决策过程中所扮演的角色，并剖析了工作人员明显不愿将针对弱势个体的决策外包给数据系统的原因。我们的研究发现提出了一个数据外包连续谱，我们将从设计者如何创建技术支持非营利领域中富有同情心的数据驱动决策这一角度展开讨论。