Collaborative Research: SOCIUS: Socially Responsible Smart Cities

每年，美国有350万人无家可归，每30名儿童中就有一人无家可归。尽管有许多政府赞助的项目和非营利组织的努力，许多无家可归的人仍然生活在恶劣的条件下。这项研究重新设想了智能城市技术，以最好地为那些需要获得包括食物、住所和医疗服务在内的基本资源的人提供服务。拟议的基础设施将连接公共服务、非政府组织和普通公民目前分散的努力，并使用人口建模和规划算法，将变化和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，这项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的传感模式和移动技术在内的技术挑战方面取得进展。作为以人为中心的设计方法的一部分，将进行访谈和观察以了解用户需求，并设计一个多个利益相关者可以用来报告他们的需求和额外供应的系统。这些收集的数据将被非营利组织用于战略性地分配资源。现实世界中的利益相关者，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。本研究具有高风险和高回报，适合渴望。失败意味着由此产生的规划算法将做出不公平的决定并优先考虑少数组织或捐赠者，或者将做出公平但效率低下的分配决定，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未得到充分服务的人口的生活质量。该项目的完成将产生1)优化资源分配的算法，这些算法既高效又了解人在环路中的关切，并可用于其他职能，包括灾害应对，以及2)非营利组织、志愿者和有需要的人口的通信基础设施，以协调其他服务活动。该项目有可能产生巨大的社会影响：它将使慈善捐赠对有电力供应的人来说既方便又便宜，增加了捐赠量，从而减少了浪费。其结果将是更好地实现日益分享的美国经济的慈善潜力。

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.