L.A.’s Vulnerable Kids Caught in the Middle as the “Elephants” of Analytics Fight

“When elephants fight,” the proverb goes, “the grass gets hurt.”

As Los Angeles deals with the aftermath of another child abuse tragedy, the death of Yonatan Aguilar, the debate over how to fix the system is devolving into a fight between two of the field’s “elephants.”

They’re fighting over which of two flawed, racially biased approaches to trying to predict which children are in danger should predominate in the biggest child welfare “market” in the country.

They’re being egged on by the Los Angeles County Board of Supervisors – or as this particular governing body should properly be known, simply “The B.S.” The B.S. is doing what it always does about child welfare issues: micromanage and grandstand.

The entire shameful spectacle only diverts attention from the problem that’s been at the root of Los Angeles’ child welfare crisis for decades: a take-the-child-and-run mentality that does enormous harm to children needlessly taken. It also so overloads caseworkers that they can’t do a thorough investigation of any case, no matter what decision-making tool they use.

Los Angeles takes away children at double the rate of New York City and triple the rate of Chicago. That didn’t save Yonatan Aguilar, Gabriel Fernandez or the many who came before. Of course, New York and Chicago also have horrifying cases involving deaths of children “known to the system.” But does anyone really believe that Los Angeles children are twice as safe from abuse as children in New York City and three times as safe as children in Chicago?

On the contrary, the take-the-child-and-run approach makes all children less safe.

The more that workers are overwhelmed with false allegations, trivial cases and children who don’t need to be in foster care, the less time they have to find children in real danger. So they make even more mistakes in all directions. That’s almost always the real reason for the tragedies that make headlines. But instead of getting to the heart of the problem, the supervisors are obsessing over whether to replace one flawed system of risk assessment with another.

Two Flawed Models of Risk Assessment

Right now, Los Angeles caseworkers use an approach called “Structured Decision Making.” They fill out questionnaires that rate families, then feed the results into a computer that supposedly tells the caseworkers how high the risk is in the families.

But a study in Michigan found that while SDM has a veneer of objectivity, many of the determinations workers make are highly subjective. The Michigan study also found that risk factors that appear to be race neutral are anything but. Simply being a young parent is deemed a risk. So is being a single parent. Black parents are more likely to be young and more likely to be single.

Other “risk factors” are self-reinforcing. A child is rated at higher risk if there have been previous reports of maltreatment. But, precisely because of poverty, which is easily confused with “neglect, ” and because of racial bias, poor black families are more likely to be subjects of such reports.

So it’s no wonder officials at the Los Angeles County Department of Children and Family Services (DCFS) suggested in 2007 that SDM contributed to a rapid increase in children taken from their parents in Los Angeles County. DCFS has acknowledged that the racial disparity in the Los Angeles system has increased since SDM began.

An evaluation by the Washington State Institute for Public Policy found that using SDM may have increased racial bias in child removals in that state.

SDM’s competitor is “predictive analytics,” which is essentially SDM on steroids. The analytics software uses demographic factors to compute alleged risk. It’s being touted by, among others, SAS, a giant software firm which points to its own analysis of its own test as evidence that it works.

But the test also found that 95 percent of the time, when the software predicted a catastrophe if the child was not taken away, the software was wrong. And, like SDM, predictive analytics has a major racial bias problem.

Both SDM and predictive analytics amount to the same thing: computerized racial profiling.

Switching from one to the other will only contribute to another spike in needless entries into foster care, doing enormous harm to the children who are needlessly taken. It will also further overwhelm caseworkers, making it even more likely that they’ll miss the next Yonatan Aguilar.

If that happens, the members of “The B.S.” will surely race to express their “shock” and “outrage” before the television cameras. And the cycle will begin all over again.

The elephants are fighting, but this time it’s not grass that’s getting hurt – it’s innocent children.