Challenges and Opportunities in Using Data Science for Homelessness Service Provision

Abstract

Homelessness service provision, a task of great societal relevance, requires solutions to several urgent problems facing our humanity. Data science, that has recently emerged as a potential catalyst in addressing long standing problems related to human services, offers immense potential. However, homelessness service provision presents unignorable challenges (e.g., assessment methods and data bias) that are are seldom found in other domains, requiring cross-discipline collaborations and cross-pollination of ideas. This work summarizes the challenges offered by homelessness service provision tasks, as well as the problems and the opportunities that exist for advancing both data science and human services. We begin by highlighting typical goals of homelessness service provision, and subsequently describe homelessness service data along with their properties, that make it challenging to use traditional data science methods. Along the way, we discuss some of the existing efforts and promising directions for data science, and conclude by discussing the importance of a deep collaboration between data science and domain experts for synergistic advancements in both disciplines.