Los Angeles is using AI to predict who might become homeless and help before they do

Los Angeles is pioneering a program that uses artificial intelligence (AI) to predict who might become homeless and intervenes to provide support before this happens.

The initiative: The AI-driven project, run by the Los Angeles County Department of Health Services, tracks information from seven county agencies, including ER visits, mental health crises, substance abuse disorders, arrests, and requests for public benefits.
* Using machine learning, it identifies the individuals most at risk of losing their homes, who aren’t covered by other prevention programs, and offers assistance.
* The help includes a case manager to work with people for four to six months, and between $4,000 and $6,000 of aid, which is used to cover bills such as rent, utilities, groceries and other monthly expenses.

Practical challenges: Despite the program’s potential, it battles with the realities of reaching out to people with unstable lives, changing addresses, and trust issues.
* Half of the targeted individuals are unreachable, and those who are contacted sometimes decline the help, or are already homeless, and hence no longer qualify.

Case studies: The program has successfully helped individuals like Dulce Volantin and Ricky Brown stabilize their lives.
* Volantin and her partner managed to get a subsidized apartment with on-site case management for Volantin’s mental health needs.
* Brown, following the sudden death of his ex-wife, took custody of his three grandsons. The financial aid has helped him navigate the subsequent financial challenges.

Outcomes and prospects: The project, which has worked with 560 people over two years, is yet to establish if it can help people maintain their living situation in the long term.
* A randomized control trial is currently tracking similar individuals who haven’t received assistance, and initial results will be published in 2026.
* Despite this, San Diego County is already planning to run a similar program.

View original article on NPR

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