Collaborative Research: SOCIUS: Socially Responsible Smart Cities

美国每年有350万人无家可归，每30个儿童中就有一个无家可归。尽管有许多政府赞助的项目和非营利组织的努力，许多无家可归的人生活在悲惨的条件。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基本资源的人提供服务，包括食物，住所和医疗服务。拟议中的基础设施将连接公共服务，非政府组织和私人公民目前脱节的努力，并使用人口建模和规划算法，以匹配变化和不可预测的供应与那些谁需要它。在追求的总体目标，收集和提供服务，以最大限度地提高社会福利，这项研究将在人口建模科学的进步，以人为本的规划算法的分析和设计，以及包括安全和隐私感知模式和移动的技术在内的技术挑战。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，让多个利益相关者可以用来报告他们的需求和额外供应。非营利组织将使用这些收集的数据来战略性地分配资源。真实世界的利益相关者，如食品银行，食品储藏室，庇护所，街头医疗队和食品救援组织将密切参与设计和评估过程。这项研究是高风险和高回报的，适合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。成功将提高美国资源分配的效率和服务不足人口的生活质量。该项目的完成将产生1）用于优化资源分配的算法，这些算法既有效又了解人在回路中的关注点，并且可用于其他功能，包括灾害响应，以及2）用于非营利组织，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。该项目有可能产生巨大的社会影响：它将使慈善捐款对那些有供电能力的人来说既方便又便宜，增加捐款量，从而减少浪费。其结果将是更好地实现美国经济日益共享的慈善潜力。

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.