专家对如何打击AI生成的虚假信息存在分歧，但一致认为健康与政治领域需采用不同解决方案
Experts Disagree on How to Fight AI Disinformation, but Agree That Health and Politics Need Different Solutions
- Frankfurt University of Applied Sciences（法兰克福应用科学大学）
- IMT Atlantique（大西洋高等矿业学院）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
54名国际专家评估AI虚假信息威胁，发现政治与健康领域的最高威胁类型不同，专家对政府监管的有效性存在分歧，但一致认为两领域需不同解决方案，为AI虚假信息格局提供初步专家视角。
AI中文摘要：
54名国际专家评估AI生成的虚假信息威胁时，呈现出令人惊讶的模式：政治领域中，视频深度伪造（deepfakes）的平均威胁评分最高（M=6.31/7）；而健康领域则不同，AI生成文本的平均评分最高（M=5.80）。专家对应对措施也存在分歧：政府监管既获得最多“最有效”投票（30%），也获得最多“最无效”投票（15%），不过评分分布存在争议而非两极分化，这表明专家是在优先事项上存在分歧，而非对措施的有效性存在分歧。这些发现为仍在快速形成的AI虚假信息格局提供了初步的专家视角图。
英文摘要：
When 54 international experts assessed AI-generated disinformation threats, they revealed a surprising pattern: while video deepfakes received the highest average threat ratings in the political domain (M = 6.31/7), the pattern differed in the health domain, where AI-generated text received the highest average rating (M = 5.80). Experts also diverge on what to do: government regulation drew both the most "most effective" (30%) and the most "least effective" (15%) votes, though rating distributions were contested rather than polarized, indicating disagreement over priorities rather than over efficacy. These findings offer an initial expert map of an AI-disinformation landscape that is still rapidly forming.
