E. Raybourn, Nathan Fabian, Warren Davis, R. C. Parks, J. T. McClain, D. Trumbo, Damon Regan, P. Durlach
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引用次数: 9
Abstract
A hypothetical scenario is utilized to explore privacy and security considerations for intelligent systems, such as a Personal Assistant for Learning (PAL). Two categories of potential concerns are addressed: factors facilitated by user models, and factors facilitated by systems. Among the strategies presented for risk mitigation is a call for ongoing, iterative dialog among privacy, security, and personalization researchers during all stages of development, testing, and deployment.
我们使用一个假设的场景来探索智能系统(如Personal Assistant for Learning (PAL))的隐私和安全考虑。处理了两类潜在的关注点:由用户模型促进的因素和由系统促进的因素。在提出的降低风险的策略中，有一项是呼吁在开发、测试和部署的所有阶段，在隐私、安全和个性化研究人员之间进行持续、迭代的对话。
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