Collaborative Research: SOCIUS: Socially Responsible Smart Cities

美国每年有350万人无家可归，每30名儿童中就有1人无家可归。尽管有许多政府资助的项目和非营利组织的努力，许多无家可归的人生活在恶劣的条件下。这项研究重新设想了智慧城市技术，以最好地为那些需要获得食物、住所和医疗服务等基本资源的人提供服务。拟议中的基础设施将把公共服务、非政府组织和普通公民目前脱节的努力联系起来，并使用人口模型和规划算法，将变化无常、不可预测的供应与需要的人相匹配。为了追求收集和提供服务以最大化社会福利的总体目标，本研究将在人口建模科学，以人为中心的规划算法的分析和设计以及包括安全和隐私感知感知模式和移动技术在内的技术挑战方面取得进展。作为以人为本的设计方法的一部分，将进行访谈和观察，以了解用户需求，并设计一个系统，多个利益相关者可以使用它来报告他们的需求和额外供应。这些收集到的数据将被非营利组织用于战略性地分配资源。现实世界的利益相关者，如食品银行、食品储藏室、收容所、街头医疗队和食品救援组织，将密切参与设计和评估过程。本研究高风险高回报，适合于EAGER。失败意味着由此产生的规划算法将做出不公平的决策并优先考虑少数组织或捐助者，或者将做出公平但低效的分配决策，这将危及社会正义和社区福祉。成功将提高资源分配的效率和美国服务不足人口的生活质量。该项目的完成将产生1)高效且意识到人在循环问题的最佳资源分配算法，并可用于其他功能，包括灾害响应；2)非营利组织、志愿者和有需要的人群的通信基础设施，以协调其他服务活动。该项目具有巨大的社会影响潜力：它将使有供电能力的人的慈善捐赠变得方便和廉价，增加捐赠量，从而减少浪费。其结果将是更好地认识到美国经济日益共享的本质所带来的慈善潜力。

Every year, 3.5 million people in the US experience homelessness, with 1 in 30 children becoming homeless. Despite numerous government-sponsored programs and efforts by nonprofit organizations, many homeless people live in abject conditions. This research re-envisions smart city technologies to best serve those in need of access to basic resources including food, shelter and medical services. The proposed infrastructure will connect the currently disjoint efforts of public services, NGOs and private citizens, and use population-modeling and planning algorithms to match the varying and unpredictable supply with those who need it. In pursuit of the overarching goal of collecting and delivering services to maximize social welfare, this research will make advances in the science of population modeling, the analysis and design of human-centered planning algorithms, and technological challenges including secure and privacy-aware sensing modalities and mobile technologies.As part of a human-centered design approach, interviews and observations will be conducted to understand user needs, and design a system that multiple stakeholders can use to report their needs and extra supply. This collected data will be used by non-profit organizations to strategically distribute resources. The real-world stakeholders such as food banks, food pantries, shelters, street medicine teams, and food rescue organizations will be closely involved in the design and evaluation process.This research is high-risk and high-reward, and appropriate for EAGER. Failure means that the resulting planning algorithms will make unfair decisions and prioritize a few organizations or donors, or will make fair, but inefficient allocation decisions, which will endanger social justice and community well-being. Success will improve both efficiency of resource distribution and the quality of life of underserved populations in the United States. The completion of the project will produce 1) algorithms for optimal resource allocation that are both efficient and aware of human-in-the-loop concerns, and which can be used for other functions including disaster-response, and 2) communication infrastructure for non-profit organizations, volunteers, and populations in need, to coordinate other service activities. The project has potential for great societal impact: it will make charitable donations convenient and inexpensive for those with supply power, increasing the volume of donations and thereby reducing wastage. The outcome will be an improved realization of the philanthropic potential of the increasingly sharing nature of the American economy.