Understanding Data Usage when Making High-Stakes Frontline Decisions in Homelessness Services

2025-10-15

AI Summary

This study addresses frontline homelessness service workers’ struggles with data use in high-stakes decision-making—namely, systems misaligned with practice, increasing cognitive load, and provoking ethical resistance to “data outsourcing.” Conducting a two-year (2022–2024) participatory field study, we co-designed and deployed an interactive data navigation interface to examine how administrative data function—albeit limitedly yet critically—within real-world decision chains. We introduce the “data outsourcing continuum,” a theoretical framework positing that technological intervention must dynamically modulate control authority according to context. Key contributions include: (1) the first systematic deconstruction of structural and ethical drivers behind frontline resistance to automated decision support; and (2) the articulation of *compassionate* technology design—a paradigm centered on empathy and human–AI collaboration—providing empirical grounding and methodological pathways for humane, decentralized data system design in nonprofit settings.

Technology Category

• Humans and AI: Intelligent User Interfaces
• Application Domains: Humanities & Computational Social Science
• Natural Language Processing: Ethics — Bias, Fairness, Transparency & Privacy

Application Category

• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems
• Responsible Web: Data and user privacy-enhancing technologies for the Web
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization

Abstract

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.

Problem

• Addressing frontline staff resistance to automated decision-making systems
• Designing human-centered data technologies for homelessness service decisions
• Understanding reluctance to outsource high-stakes decisions to data systems

Innovation

• Co-designing interactive data-navigation interface for shelter staff
• Supporting human-centered decision-making with data systems
• Proposing data-outsourcing continuum for compassionate technology design