Los Angeles is implementing a pilot project utilizing machine learning to better identify vulnerable individuals in need of housing assistance.
Over 75,000 people are currently unhoused in LA County, necessitating a rational approach to determine who receives housing help first.
Findings revealed that the traditional method of evaluating need had systemic biases, often underestimating the vulnerability of Black and Latino clients.
The new approach aims to create a more accurate assessment process by refining survey methods and employing predictive risk modeling.
While advocates express hope for these changes, concerns remain about the adequacy of housing resources and maintaining compassionate, human-centered decision-making.