Romantic AI platforms invite intimate emotional disclosure, yet their data governance practices remain underexamined. This preliminary study analyses the Privacy Policies and Terms of Service of six Western and Chinese romantic AI platforms. We find that intimate disclosures are often positioned as reusable data assets, with broad permissions for storage, analysis, and model training. We identify default training appropriation, ownership reconstruction, and intimate history assetization as key mechanisms structuring these practices, expanding platforms' rights while shifting risk onto users. Our findings surface key governance challenges in romantic AI and are intended to provoke discussion and inform future empirical and design research on human AI intimacy and its governance.

翻译：浪漫AI平台鼓励用户进行私密的情感披露，但其数据治理实践尚未得到充分审视。本研究初步分析了六款中西方浪漫AI平台的隐私政策与服务条款。我们发现，私密披露常被定位为可重复利用的数据资产，平台拥有广泛的存储、分析和模型训练权限。我们识别出默认训练征用、所有权重构和亲密历史资产化作为构建这些实践的关键机制，这些机制在扩大平台权利的同时将风险转移至用户。我们的研究揭示了浪漫AI领域的关键治理挑战，旨在引发讨论并为未来关于人机亲密关系及其治理的实证与设计研究提供参考。