People candidly discuss sensitive topics online under the perceived safety of anonymity; yet, for many, this perceived safety is tenuous, as miscalibrated risk perceptions can lead to over-disclosure. Recent advances in Natural Language Processing (NLP) afford an unprecedented opportunity to present users with quantified disclosure-based re-identification risk (i.e., "population risk estimates", PREs). How can PREs be presented to users in a way that promotes informed decision-making, mitigating risk without encouraging unnecessary self-censorship? Using design fictions and comic-boarding, we story-boarded five design concepts for presenting PREs to users and evaluated them through an online survey with N = 44 Reddit users. We found participants had detailed conceptions of how PREs may impact risk awareness and motivation, but envisioned needing additional context and support to effectively interpret and act on risks. We distill our findings into four key design recommendations for how best to present users with quantified privacy risks to support informed disclosure decision-making.

翻译：人们在匿名性的感知安全下在线坦率讨论敏感话题；然而，对许多人而言，这种感知安全是脆弱的，因为错误校准的风险认知可能导致过度披露。自然语言处理（NLP）的最新进展提供了前所未有的机会，向用户呈现基于披露的量化重识别风险（即“群体风险估计”，PREs）。如何向用户呈现PREs，以促进知情决策，在降低风险的同时避免鼓励不必要的自我审查？通过设计虚构和漫画分镜，我们为向用户呈现PREs绘制了五种设计概念的故事板，并通过一项N = 44名Reddit用户的在线调查对其进行了评估。我们发现参与者对PREs如何影响风险意识和动机有详细的构想，但设想需要额外的上下文和支持来有效解释风险并采取行动。我们将研究结果提炼为四项关键设计建议，旨在指导如何最佳地向用户呈现量化隐私风险，以支持知情披露决策。