As synthetic media proliferates, AI policymakers and practitioners have increasingly turned to disclosures--signals describing how media has been created or modified by AI--to help audiences evaluate media credibility. While there is a growing body of research on user interpretations, the upstream decision-making processes that affect users remain underexplored. This study therefore examines how AI policymakers and practitioners design synthetic media disclosures under complex sociotechnical constraints. Drawing on 23 expert interviews and 13 case studies from organizations participating in the Partnership on AI's Synthetic Media Framework, analysis identifies key disclosure goals, including process transparency and harm reduction, and two central tensions that emerge when pursuing those goals: normativity versus neutrality and proactivity versus precision. Findings highlight the role of analogical reasoning, from nutrition labels to Prop 65 warnings, in managing, but not resolving tensions. Ultimately, this study emphasizes the need for scholarship focused on AI transparency decision-makers and their use of analogical reasoning to support audiences encountering media in the AI age.

翻译：随着合成媒体的激增，人工智能政策制定者和从业者越来越多地转向信息披露——即描述媒体如何被AI创建或修改的信号——以帮助受众评估媒体的可信度。尽管关于用户解读的研究日益增多，但影响用户的上游决策过程仍未被充分探索。因此，本研究探讨了人工智能政策制定者和从业者如何在复杂的社会技术约束下设计合成媒体信息披露。基于对参与人工智能合作伙伴关系合成媒体框架组织的23次专家访谈和13个案例研究，分析识别出关键的信息披露目标，包括流程透明度和减少伤害，以及在追求这些目标时出现的两个核心张力：规范性与中立性、主动性与精确性。研究结果强调了类比推理的作用——从营养标签到第65号提案警告——在于管理而非解决这些张力。最终，本研究强调了需要更多关注AI透明度决策者及其使用类比推理来支持在AI时代遇到媒体的受众的学术研究。