前台调解工作：弥合AI决策与用户期望之间差距的无形工作
Frontstage Mediation Work: Invisible Work Bridging Gaps Between AI Decisions and User Expectations
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中文总结 AI 辅助
本文提出“前台调解工作”概念，通过拼车案例揭示一线司机如何隐形地弥合AI决策与用户期望的差距，并承担系统决策的交互后果。
中文摘要 AI 辅助
自动化服务系统日益生成算法运营决策，这些决策塑造了服务的交付方式。然而，这些决策只有通过在一线执行的前台工作人员才能触达最终用户。在此过程中，自动化决策可能与用户期望产生偏差，在服务接触点表现为摩擦。我们提出“前台调解工作”作为初步分析视角，用于审视前台工作人员预测并管理算法决策与用户期望之间这种错位时常常隐形的劳动。基于对按需拼车服务的定性案例研究，我们识别出司机在摩擦出现时维持服务接触的四种反复出现的实践。此类劳动仍被吸收在日常运营中，在绩效指标、系统日志或正式职位描述中不留痕迹。本文通过说明自动化服务如何将管理系统级决策的交互后果的责任转移给一线工作人员，为以工人为中心的HCI学术研究做出贡献。
英文摘要
Automated service systems increasingly generate algorithmic operational decisions that shape how services are delivered. However, these decisions reach end-users only through frontline workers who carry them out in real-world settings. During this process, automated decisions can diverge from user expectations, surfacing as friction at the service encounter. We propose Frontstage Mediation Work as a preliminary analytic lens for examining the often invisible labor through which frontline workers anticipate and manage such misalignments between algorithmic decisions and user expectations. Drawing on a qualitative case study of an On-Demand Ride-Pooling service, we identify four recurring practices through which drivers sustain the service encounter when frictions arise. Such labor remains absorbed into routine operations, leaving no trace in performance metrics, system logs, or formal job descriptions. This paper contributes to worker-centered HCI scholarship by illustrating how automated services shift onto frontline workers the responsibility of managing the interactional consequences of system-level decisions.
发表机构
- KAIST（韩国科学技术院）
机构由 AI 辅助整理，请以论文原文为准。
