Critics say employing the algorithm gives a program powered by data mostly collected about poor people an outsized role in deciding families’ fates.
“Workers, whoever they are, shouldn’t be asked to make, in a given year, 14, 15, 16,000 of these kinds of decisions with incredibly imperfect information,” said Erin Dalton, director of the county’s Department of Human Services and a pioneer in implementing the predictive child welfare algorithm.
If the tool had acted on its own to screen in a comparable rate of calls, it would have recommended that two-thirds of Black children be investigated, compared with about half of all other children reported, according to another study published last month and co-authored by a researcher who has audited the county’s algorithm.
Because family court hearings are closed to the public and the records are sealed, AP wasn’t able to identify first-hand any families who the algorithm recommended be mandatorily investigated for child neglect, nor any cases that resulted in a child being sent to foster care. Families and their attorneys can never be sure of the algorithm’s role in their lives either because they aren’t allowed to know the scores.
“It’s their life and their history,” said Thad Paul, a manager with the county’s Children Youth & Family Services. “We want to minimize the power differential that comes with being involved in child welfare … we just really think it is unethical not to share the score with families.” For years, California explored data-driven approaches to the statewide child welfare system before abandoning a proposal to use a predictive risk modeling tool in 2019.
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