SaTC: CORE: Medium: Situation-Aware Identification and Rectification of Regrettable Privacy Decisions

如今，人们在与移动设备的日常互动中面临着许多隐私决定。在过去的十年里，研究人员研究了许多工具和机制的设计，比如隐私推动，旨在帮助个人做出更好的隐私决定。但就像其他领域的决策支持工具一样，这些工具并不能让用户成为完美的决策者。用户仍然会犯错误，之后会后悔自己的隐私决定。这个项目通过帮助用户重新审视和纠正他们可能后悔的过去的隐私决定，为重新设计隐私提供了一个新的视角。为了避免通过重复提醒惹恼用户，项目的一个重点是确定哪些过去的隐私决定最有可能引发后悔，并要求用户只重新访问这些决定。这个项目具有很高的社会重要性，因为今天超过75%的美国人拥有智能手机，需要经常做出隐私决定。通过将隐私行为的社会分析与隐私工具的技术设计联系起来，该项目还将产生更广泛的影响，包括技术开发者、政策制定者和消费者。该项目植根于整合多学科知识的实质性机构，以应对移动隐私的严峻挑战。它发展了一种理论，阐述了认知评估、情感状态和环境线索这三种因素如何削弱高努力的决策，并使人们转向低努力的信息处理，最终导致令人遗憾的隐私决定。对于隐私行为的社会分析，本项目采用了经验抽样法和因子小片段研究相结合的新方法来实证验证理论框架。在隐私工具的技术设计方面，本项目开发了一个专家增强预测模型，从移动操作系统收集的数据中推断认知评估、情感状态和环境线索的影响因素，从而预测隐私决策的质量。该项目的长期愿景是使技术设计能够帮助弥合用户隐私决定和他们的感知之间的差异，特别是在移动系统的背景下。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

People today are faced with many privacy decisions in their daily interactions with mobile devices. In the past decade, researchers have studied the design of many tools and mechanisms, such as privacy nudges, that aim to help individuals make better privacy decisions. But just like decision support tools in other domains, these tools cannot make users perfect decision-makers. Users still make mistakes and regret their privacy decisions later. This project casts a fresh perspective on Privacy-by-Redesign by helping users revisit and rectify past privacy decisions that they may regret. In order to avoid annoying users through repetitive alerts, a focus of the project is to identify which past privacy decisions most likely trigger regrets, and to ask users to revisit only those decisions. This project has high societal importance, given that more than 75% of Americans own a smartphone today and need to make frequent privacy decisions. The broader impacts of the project also reach technology developers, policy makers, and consumers by connecting the social analysis of privacy behaviors with the technical design of privacy tools.This project is rooted in integrating substantive bodies of multidisciplinary knowledge to address the acute challenges of mobile privacy. It develops a theory on how three types of factors, cognitive appraisal, affective states, and environmental cues undercut high-effort decision making and move people toward low-effort information processing, which ultimately leads to regrettable privacy decisions. For the social analysis of privacy behaviors, this project employs a novel combination of experience sampling method and factorial vignette studies to empirically validate the theoretical framework. For the technical design of privacy tools, the project develops an expert-augmented prediction model that infers from data collectible by a mobile operating system the influential factors of cognitive appraisal, affective states, and environmental cues, so as to predict the quality of a privacy decision. The long-term vision of this project is to enable technological designs that help bridge the discrepancies between users' privacy decisions and their perceptions, especially in the context of a mobile system.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.