梳理46万份模型卡片，发现开发者忽视人际交互中的欺诈风险。
The AI Model Risk Catalog: What Developers and Researchers Miss About Real-World AI Harms
- 从46万份模型卡中提取3000条风险，构建AI风险目录
- 开发者关注偏见与安全，却忽略常见的人际欺诈风险
- 呼吁早期设计中纳入人机互动与系统性风险考量
我们分析了Hugging Face上近46万份AI模型卡片，提取出约3000个独特风险条目，构建了《AI模型风险目录》。通过与MIT风险库及AI事故数据库的对比发现，开发者多关注偏见、安全等技术问题，而研究人员更关注社会影响；但两者均忽视了由人机交互引发的欺诈与操纵类风险。研究强调需建立更清晰、结构化的风险报告机制，推动开发人员在设计初期就考虑人类互动与系统性风险。目录与附录可访问：https://social-dynamics.net/ai-risks/catalog。
原文摘要 · Abstract (English)
We analyzed nearly 460,000 AI model cards from Hugging Face to examine how developers report risks. From these, we extracted around 3,000 unique risk mentions and built the \emph{AI Model Risk Catalog}. We compared these with risks identified by researchers in the MIT Risk Repository and with real-world incidents from the AI Incident Database. Developers focused on technical issues like bias and safety, while researchers emphasized broader social impacts. Both groups paid little attention to fraud and manipulation, which are common harms arising from how people interact with AI. Our findings show the need for clearer, structured risk reporting that helps developers think about human-interaction and systemic risks early in the design process. The catalog and paper appendix are available at: https://social-dynamics.net/ai-risks/catalog.
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