NYC lets AI gamble with Child Welfare

<

div class=”field field–name-body field–type-text-with-summary field–label-hidden”>

<

div class=”field__items”>

<

div class=”field__item even”>

The Markup revealed in its reporting last month that New York City’s Administration for Children’s Services (ACS) has been quietly deploying an algorithmic tool to categorize families as “high risk”. Using a grab-bag of factors like neighborhood and mother’s age, this AI tool can put families under intensified scrutiny without proper justification and oversight.

ACS knocking on your door is a nightmare for any parent, with the risk that any mistakes can break up your family and have your children sent to the foster care system. Putting a family under such scrutiny shouldn’t be taken lightly and shouldn’t be a testing ground for  automated decision-making by the government.

 This “AI” tool, developed internally by ACS’s Office of Research Analytics, scores families for “risk” using 279 variables and subjects those deemed highest-risk to intensified scrutiny. The lack of transparency, accountability, or due process protections demonstrates that ACS has learned nothing from the failures of similar products in the realm of child services.

The algorithm operates in complete secrecy and the harms from this opaque “AI theater” are not theoretical. The 279 variables are derived only from cases back in 2013 and 2014 where children were seriously harmed. However, it is unclear how many cases were analyzed, what, if any, kind of auditing and testing was conducted, and whether including of data from other years would have altered the scoring.

What we do know is disturbing: Black families in NYC face ACS investigations at seven times the rate of white families and ACS staff has admitted that the agency is more punitive towards Black families, with parents and advocates calling its practices “predatory.” It is likely that the algorithm effectively automates and amplifies this discrimination.

Despite the disturbing lack of transparency and accountabi

[…]
Content was cut in order to protect the source.Please visit the source for the rest of the article.

This article has been indexed from Deeplinks

Read the original article: