Collaborative Research: SOCIUS: Socially Responsible Smart Cities
合作研究:SOCIUS:具有社会责任感的智慧城市
基本信息
- 批准号:1651566
- 负责人:
- 金额:$ 10万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2016
- 资助国家:美国
- 起止时间:2016-09-01 至 2018-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
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.
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。这些收集的数据将被非营利组织用于战略性地分配资源。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。
项目成果
期刊论文数量(3)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
A Human-Centered Approach to Algorithmic Services: Considerations for Fair and Motivating Smart Community Service Management that Allocates Donations to Non-Profit Organizations
以人为本的算法服务:向非营利组织分配捐款的公平和激励智能社区服务管理的考虑
- DOI:10.1145/3025453.3025884
- 发表时间:2017
- 期刊:
- 影响因子:0
- 作者:Lee, Min Kyung;Kim, Ji Tae;Lizarondo, Leah
- 通讯作者:Lizarondo, Leah
Towards a socially responsible smart city: dynamic resource allocation for smarter community service
迈向对社会负责的智慧城市:动态资源配置,实现智慧社区服务
- DOI:10.1145/3137133.3137163
- 发表时间:2017
- 期刊:
- 影响因子:0
- 作者:Tsai, Huey-Ru;Shoukry, Yasser;Lee, Min Kyung;Raman, Vasumathi
- 通讯作者:Raman, Vasumathi
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Min Kyung Lee其他文献
WeBuildAI: Participatory Framework for Fair and Efficient Algorithmic Governance
WeBuildAI:公平高效算法治理的参与框架
- DOI:
- 发表时间:
2018 - 期刊:
- 影响因子:0
- 作者:
Min Kyung Lee;Daniel Kusbit;Anson Kahng;J. Tae;Xinran Yuan;Allissa Chan;Ritesh Noothigattu;Daniel See;Siheon Lee;Alexandros Psomas;Ariel D. Procaccia - 通讯作者:
Ariel D. Procaccia
Hunting paleoceanographic archives of ice sheet-ocean interaction in the northwestern Ross Sea, Antarctica
在南极洲罗斯海西北部寻找冰盖与海洋相互作用的古海洋档案
- DOI:
10.3389/feart.2023.1234347 - 发表时间:
2023 - 期刊:
- 影响因子:2.9
- 作者:
Sookwan Kim;L. De Santis;J. Hong;E. Colizza;Sunghan Kim;A. Bergamasco;Sang;Seung‐Goo Kang;Min Kyung Lee;Hyoungjun Kim;Y. Choi;Andrea Geniram;Hyoung Gyu Choi;Jae Il Lee;K. Yoo;Yongcheol Park - 通讯作者:
Yongcheol Park
Human-Centered Approaches to Fair and Responsible AI
以人为本的公平和负责任的人工智能方法
- DOI:
- 发表时间:
2020 - 期刊:
- 影响因子:0
- 作者:
Min Kyung Lee;Nina Grgic;Michael Carl Tschantz;Reuben Binns;Adrian Weller;Michelle Carney;K. Inkpen - 通讯作者:
K. Inkpen
Algorithms at Work: Empirical Diversity, Analytic Vocabularies, Design Implications
工作中的算法:经验多样性、分析词汇、设计含义
- DOI:
10.1145/2818052.2855519 - 发表时间:
2016 - 期刊:
- 影响因子:0
- 作者:
Susann Wagenknecht;Min Kyung Lee;Caitlin Lustig;J. O'Neill;Himanshu Zade - 通讯作者:
Himanshu Zade
Particle-size dependent magnetic properties of Scotia Sea sediments since the Last Glacial Maximum: Glacial ice-sheet discharge controlling magnetic proxies
自末次盛冰期以来斯科舍海沉积物的颗粒尺寸相关磁性:冰川冰盖排放控制磁性代理
- DOI:
10.1016/j.palaeo.2020.109906 - 发表时间:
2020 - 期刊:
- 影响因子:0
- 作者:
J. Shin;Sunghan Kim;Xiang Zhao;K. Yoo;Yongjae Yu;Jae Il Lee;Min Kyung Lee;H. Yoon - 通讯作者:
H. Yoon
Min Kyung Lee的其他文献
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{{ truncateString('Min Kyung Lee', 18)}}的其他基金
Collaborative Research: DASS: Enabling Standards- and Disclosure-Based Regulations in and through Software Systems: Making Algorithmic Work Management Software Accountable to Law
合作研究:DASS:在软件系统中并通过软件系统实现基于标准和披露的法规:使算法工作管理软件对法律负责
- 批准号:
2217721 - 财政年份:2022
- 资助金额:
$ 10万 - 项目类别:
Standard Grant
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Cell Research
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- 批准号:10774081
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