AI预测让女性误信身体数据，反而扭曲真实体验。
"It became a self-fulfilling prophecy": How Lived Experiences are Entangled with AI Predictions in Menstrual Cycle Tracking Apps
- 用户根据AI预测理解自身生理与心理状态。
- 因记录不全导致预测出错，但用户仍依赖其判断。
- 界面缺乏提醒，非主流使用者更感孤立。
月经周期追踪应用（MCTAs）中的基于AI的预测与洞察功能日益普及，帮助用户获取个性化的身体与心理状态信息。然而，目前尚缺乏研究探讨这些预测性AI功能及其解释如何影响用户的实际生活体验。本文通过14次半结构化访谈和一次群体自传式民族志，揭示了人与AI相互纠缠的过程。研究发现：(1) 用户在AI预测基础上理解自身体验，尽管这些预测可能因记录不完整而出现偏差；(2) 界面设计与AI解释未促进用户对这种纠缠关系的认知或批判性参与；(3) 非规范使用群体报告在此互动中感到孤立。基于此，我们提出面向预测性AI功能与解释的设计建议。
原文摘要 · Abstract (English)
In menstrual cycle tracking apps (MCTAs), AI-based predictions and insights have become increasingly popular. These features enable users to receive personalized information about their bodies and mental states. However, there is currently little research on how these predictive AI features and explanations affect users' lived experiences. This paper examines human-AI entanglement in MCTAs through 14 semi-structured user interviews and a group autoethnography. These methods uncover the processes leading to this phenomenon. Our results reveal that: (1) users understand their lived experiences in light of AI predictions, although these predictions can be faulty due to imperfect logging practices, (2) the user interface features and AI explanations do not support awareness or critical engagement with this entanglement and meaning-making, and (3) non-normative MCTA users report a sense of isolation in this entangled interaction. Based on our findings, we propose design implications for predictive AI features and explanations.
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