欧洲开发者访谈揭示AI隐私风险认知分歧与防护策略落地难。
"We are not Future-ready": Understanding AI Privacy Risks and Existing Mitigation Strategies from the Perspective of AI Developers in Europe
- 25位欧洲开发者访谈，分析隐私风险认知差异
- 技术之外的人为因素影响风险判断，共识度低
- 虽知防护策略但实际应用极少，存在落地鸿沟
人工智能的普及引发了关于训练数据、模型接口、下游应用等环节的隐私担忧。我们对25位欧洲人工智能开发者进行了访谈，了解他们认为对用户、开发者及企业构成最大威胁的隐私风险，以及可缓解这些风险的保护策略。研究发现，开发者之间对隐私风险的优先级排序缺乏共识，这种分歧源于显著的人类而非纯技术性推理模式。此外，尽管开发者了解多种风险缓解策略，但在现实中采纳程度极低。研究揭示了在应对人工智能隐私风险方面存在的差距与机遇。
原文摘要 · Abstract (English)
The proliferation of AI has sparked privacy concerns related to training data, model interfaces, downstream applications, and more. We interviewed 25 AI developers based in Europe to understand which privacy threats they believe pose the greatest risk to users, developers, and businesses and what protective strategies, if any, would help to mitigate them. We find that there is little consensus among AI developers on the relative ranking of privacy risks. These differences stem from salient reasoning patterns that often relate to human rather than purely technical factors. Furthermore, while AI developers are aware of proposed mitigation strategies for addressing these risks, they reported minimal real-world adoption. Our findings highlight both gaps and opportunities for empowering AI developers to better address privacy risks in AI.
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