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SCC-PG: Trust, transparency and technology: Building digital equity through a civic digital commons

SCC-PG: Trust, transparency and technology: Building digital equity through a civic digital commons
SCC-PG:信任、透明度和技术:通过公民数字共享建立数字公平
批准号:
2234081
负责人:
Gwen Shaffer
金额:
$14.74万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2023
资助国家:
美国
项目状态:
已结题
起止时间:
2023-05-01 至 2024-09-30

项目摘要

项目成果

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中文摘要
翻译
智能城市平台——包括移动应用程序、摄像头、传感器、算法和预测分析——生成了大量关于居民的数据。研究表明,过度监控强化了一种不安全感,导致居民担心公民自由受到侵犯,尤其是在有色人种社区。我们的数字版权平台将赋予社区成员权力,让他们有权决定伦敦金融城如何收集、使用和存储他们的个人数据。该平台将与数百名长滩居民合作设计,参与公民用户测试平台和其他定性数据收集。该平台将以文本和开源图像为特色,直观地传达长滩市如何使用特定技术,这些技术收集了哪些数据以及该市如何利用这些数据。我们计划战略性地在长滩部署标牌,在物理上毗邻或数字嵌入公民技术,例如传感器,摄像头,移动支付亭,311应用程序。该平台将包括二维码或超链接,将用户带到在线仪表板,在那里他们可以了解更多细节,更新数据收集偏好,并与当地官员分享评论和关注-让居民清楚地了解当地政府如何收集,分析,分享,并保留他们的个人数据。这个数字版权平台将以文本和开源图像为特色,直观地传达长滩市如何使用特定的智能技术,这些技术收集了哪些数据以及该市如何利用这些数据。该平台考虑了智能技术的技术、法律、伦理和空间方面。该项目以信任和背景完整性框架为基础,重点关注伦敦金融城的愿景,即以合乎道德的方式使用数据,避免强化现有的种族偏见和歧视性决策。具体来说,我们计划战略性地在长滩部署标牌,在物理上毗邻或数字嵌入公民技术,例如传感器,摄像头,移动支付亭,311应用程序。该平台将包括QR码或超链接,将用户带到在线仪表盘,在那里他们可以了解更多细节,更新数据收集偏好,并与当地官员分享意见和关注。我们计划与智慧城市技术开发人员合作,开发一种软件解决方案,最终使居民能够选择退出数据收集。该项目将为新的问责策略提供信息,旨在确保截然不同的智慧城市技术——每种技术都有不同的用途——尊重居民的数据隐私,避免歧视性影响。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。
英文摘要
Smart city platforms–encompassing mobile apps, cameras, sensors, algorithms, and predictive analytics—generate troves of data on residents. Research suggests that excessive surveillance reinforces a sense of insecurity and leads residents to fear civil liberties violations, particularly among communities of color. Our digital rights platform will empower community members by granting them agency over how the City collects, uses and stores their personal data. The platform will be designed collaboratively with hundreds of Long Beach residents participating in a civic user testbed and other qualitative data collection. The platform will feature text and open-source iconography that visually conveys how the City of Long Beach uses specific technologies, what data these technologies collect and how the City utilizes that data. We plan to strategically deploy signage across Long Beach, physically adjacent to or digitally embedded within civic technologies, e.g., sensors, cameras, mobile payment kiosks, a 311 app. The platform will include a QR code or hyperlink that take users to an online dashboard where they may learn additional details, update data collection preferences, and share comments and concerns with local officials—giving residents a clear understanding of how local government collects, analyzes, shares, and retains their personal data. This digital rights platform will feature text and the open-source iconography that visually conveys how the City of Long Beach uses specific smart technologies, what data these technologies collect and how the City utilizes that data. The platform considers the technical, legal, ethical, and spatial aspects of smart technologies. Grounded in frameworks of trust and contextual integrity, the project is focused on the City’s vision to use data in ethical ways that avoid reinforcing existing racial biases and discriminatory decision-making. Specifically, we plan to strategically deploy signage across Long Beach, physically adjacent to or digitally embedded within civic technologies, e.g., sensors, cameras, mobile payment kiosks, a 311 app. The platform will include a QR code or hyperlink that take users to an online dashboard where they may learn additional details, update data collection preferences, and share comments and concerns with local officials. We plan to work with smart city technology developers to create a software solution that will, ultimately, enable residents to opt out of data collection. The project will inform novel accountability strategies meant to ensure that wildly disparate smart city technologies—each employed for a distinct purpose—respect residents’ data privacy and avoid discriminatory impacts.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.
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