CHS: Small: Multidisciplinary Design Approaches for Privacy and Security

数字设备和日常用品正日益变得智能、互联和人工智能，尽管这带来了许多好处，但它也引发了新的隐私问题，并引入了新的安全漏洞。这些担忧和漏洞是广泛的，尽管它们会根据某人的背景、身份和背景而对人们产生不同的影响。例如，健身跟踪器、声控智能扬声器、面部识别智能摄像头等智能设备可以被用来监控家庭成员、与第三方共享个人健康数据、监视保姆和照顾者、骚扰和虐待亲密伴侣，以及诱骗用户分享密码或泄露秘密。该项目将开发新的原型和战略，以解决智能设备引起的隐私和安全问题，这些设备对使用它们的人和环境敏感。该项目的主要新颖性将是其多学科方法，将数字隐私和安全方面的专业知识与交互、工业、平面和建筑设计等设计学科的专业知识相结合。通过让不同的非专家和专家参与原型解决方案的设计、开发和评估，该项目将扩大对隐私和安全研究和教育的参与，以生成对每个人都具有包容性、适当、公平和有效的解决方案和战略。该项目的一个关键目标是寻找目前推动大多数面向用户的隐私和安全研究的知情同意和可用的选择方法的替代方法。这些方法经常失败：隐私政策通常被忽视或难以理解，即使写得很清楚，实际上也会降低信任，而基于选择的方法往往无法适应隐私决策和偏好，这些决策和偏好因经验、个性、身份、能力和情况而有很大差异。为了解决这些问题，研究小组将进行定性实地考察和参与性设计研究，邀请不同的非专家和专家参与。这种多学科方法旨在通过以下方式为隐私、安全和以人为中心的计算研究做出贡献：(1)生成新颖的、对社会敏感的和适合于环境的解决方案，以解决当前和未来的隐私和安全问题，特别是与连接的、人工智能的和“始终在线”的日常技术相关的问题，(2)扩大和多样化参与隐私和安全问题的框架、解决方案寻找和讨论，以及(3)为工程、计算机科学、设计、政策制定开发前瞻性的方法、战略和范例原型，这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Digital devices and everyday objects are increasingly becoming smart, connected, and artificially intelligent, and though this promises numerous benefits, it also raises new privacy concerns and introduces new security vulnerabilities. These concerns and vulnerabilities are wide-ranging, although they affect people differently depending on someone's background, identity, and context. For example, smart devices such as fitness trackers, voice controlled smart speakers, and facial recognition smart cameras can be used to monitor family members, share personal health data with third parties, surveil nannies and caregivers, harass and abuse intimate partners, and trick users into sharing passwords or divulging secrets. This project will develop novel prototypes and strategies for addressing privacy and security concerns arising from smart devices that are sensitive to the people and contexts with which they are used. The main novelty of this project will be its multidisciplinary approach that combines expertise in digital privacy and security with expertise in the design disciplines of interaction, industrial, graphic, and architectural design. By involving diverse non-expert and expert participation in the design, development, and assessment of prototype solutions, this project will broaden participation in privacy and security research and education in order to generate solutions and strategies that are inclusive, appropriate, fair, and effective for everyone. A key aim of this project is to look for alternatives to the informed consent and usable choice approaches that currently drive most user-oriented privacy and security research. These approaches often fail: privacy policies are often ignored or impenetrable, and can actually decrease trust even when clearly written, while choice-based approaches often fail to fit privacy decisions and preferences that vary widely according to experience, personality, identity, ability, and situation. To address these issues, the research team will conduct qualitative fieldwork and participatory design research that invites diverse non-expert and expert participation. This multidisciplinary approach aims to contribute to privacy, security, and human-centered computing research by (1) generating novel multiform, socially-sensitive, and contextually-appropriate solutions to address current and future privacy and security issues, particularly those associated with the proliferation of connected, artificially-intelligent, and "always-on" everyday technologies, (2) broadening and diversifying participation in privacy and security problem framing, solutions-finding, and discourse, and (3) developing forward-looking methods, strategies, and exemplar prototypes for engineering, computer science, design, policymaking, and other experts and professionals to anticipate and respond to future privacy and security concerns.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.