Los Angeles algorithmic homeless coordinated entry system

The City of Los Angeles developed a Coordinated Entry System (CES) to allocate housing to homeless populations in 2013. CES is based on the effective housing-first approach, which first aims to get a roof over the head of homeless persons, and then provide assistance in other ways. First, the homeless are asked to fill out a survey, which gathers their information and organizes it into a database. Then, an algorithm ranks the cases on a “vulnerability index” so that those who need housing the most will be helped first (Misra, 2018).

While there is an argument to be made for CES’ prioritization principle (there are 58,000 unhoused people in Los Angeles County alone, and there is not currently enough housing resources for everyone), the compulsory survey has been found to ask private and even intentionally criminalizing questions regarding sensitive behavior. For example, it asks: “if you are having sex without protection; if you’re trading sex for money or drugs; if you’re thinking of harming yourself or others; if you’re running drugs for someone else; if there’s an open warrant on you”(ibid). Persons who respond yes to any of these questions, usually receive a higher score on the vulnerability index, which then gives them a higher housing priority  (Misra, 2018).

Applicants are asked to sign an extensive informed consent document, but scholars question whether the power imbalance of the situation invalidates the voluntariness of the consent form. Moreover, upon signing the consent form, applicants agree to share their sensitive information to a database that includes a host of partner agencies (ibid). Previous applicants can ask to be expunged from the database, but the process by which they do so is really unclear—and some information stays in the database. Academic Virginia Eubanks has closely studied the CES and fears that the system acts as an ’empathy override’: obfuscating the dire reality that Los Angeles needs to supply more housing to the homeless, and outsourcing difficult decisions to machines because they are too painful to make as humans (ibid).