Smart voice assistants (SVAs) are embedded in the daily lives of youth, yet their privacy controls often remain opaque and difficult to manage. Through five semi-structured focus groups (N=26) with young Canadians (ages 16-24), we investigate how perceived privacy risks (PPR) and benefits (PPBf) intersect with algorithmic transparency and trust (ATT) and privacy self-efficacy (PSE) to shape privacy-protective behaviors (PPB). Our analysis reveals that policy overload, fragmented settings, and unclear data retention undermine self-efficacy and discourage protective actions. Conversely, simple transparency cues were associated with greater confidence without diminishing the utility of hands-free tasks and entertainment. We synthesize these findings into a qualitative model in which transparency friction erodes PSE, which in turn weakens PPB. From this model, we derive actionable design guidance for SVAs, including a unified privacy hub, plain-language "data nutrition" labels, clear retention defaults, and device-conditional micro-tutorials. This work foregrounds youth perspectives and offers a path for SVA governance and design that empowers young digital citizens while preserving convenience.

翻译：智能语音助手（SVAs）已融入青少年的日常生活，但其隐私控制机制往往不透明且难以管理。通过对加拿大青少年（16-24岁，N=26）开展的五场半结构化焦点小组访谈，我们探究了感知隐私风险（PPR）与感知隐私收益（PPBf）如何与算法透明度及信任（ATT）、隐私自我效能（PSE）相互作用，进而影响隐私保护行为（PPB）。分析表明，策略过载、设置分散及数据保留规则不明确会削弱自我效能感，阻碍保护性行为。相反，简洁的透明度提示能在不影响免提任务与娱乐功能实用性的前提下，增强用户信心。我们将这些发现整合为一个定性模型：透明度摩擦会侵蚀PSE，继而弱化PPB。基于该模型，我们提出可行的SVA设计指南，包括统一隐私管理中心、通俗易懂的“数据营养”标签、清晰的数据保留默认设置，以及设备情境化微教程。本研究凸显青少年视角，为智能语音助手的治理与设计提供了一条路径，在保障便捷性的同时赋能年轻数字公民。