Evidence From the Past: AI Decision Aids to Improve Housing Systems for Homeless Youth
Evidence From the Past: AI Decision Aids to Improve Housing Systems for Homeless Youth
复制标题
过去的证据：人工智能决策有助于改善无家可归青少年的住房系统
DOI：
--
复制
发表时间：
2017
期刊：
影响因子：
--
通讯作者：
M. Morton
中科院分区：
文献类型：
--
作者：
Hau;E. Rice;P. Vayanos;Milind Tambe;M. Morton
人工智能决策援助能否改善帮助无家可归青年的住房系统？美国每年有近200万无家可归的青年。协调进入系统正在被用来为全国无家可归的青年提供住房援助。尽管作出了这些努力，但仍然无家可归和流落街头的无家可归青年人数仍然很高。基于这一事实，我们发起了第一项研究，以创建人工智能决策辅助工具，以改善无家可归青年的现有住房系统。首先，我们确定是否可以用来预测青年的无家可归状态接受住房援助后，优先考虑青年的住房援助目前的标题。然后，我们考虑使用规则的其他组件构建更好的AI决策辅助工具和预测模型。我们相信，在住房分配方面，有效的人机协作有很大的潜力。我们计划与HUD和当地社区合作，在未来开发此类系统。
Could an AI decision aid improve housing systems that assist homeless youth? There are nearly 2 million homeless youth in the United States each year. Coordinated entry systems are being used to provide homeless youth with housing assistance across the nation. Despite these efforts, the number of homeless youth still homeless and unstably housed on the street remains very high. Motivated by this fact, we initiate a first study to create AI decision aids for improving the current housing systems for homeless youth. First, we determine whether the current rubric for prioritizing youth for housing assistance can be used to predict youth’s homelessness status after receiving housing assistance. We then consider building better AI decision aids and predictive models using other components of the rubric. We believe there is much potential for effective human-machine collaboration in the context of housing allocation. We plan to work with HUD and local communities to develop such systems in the future.