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| Hillary Clinton |
I’ve written
before about how one of the biggest losers in the 2016 elections was “predictive
analytics.” All those algorithms kept
assuring us that Hillary Clinton was all but certain to win. The media were suckered.
It turns out the media were not alone. In her
review of a new book, Shattered: Inside Hillary
Clinton’s Doomed Campaign, Michiko Kakutani of The New York Times writes that the campaign itself made the same
disastrous error:
As described in
“Shattered,” Clinton’s campaign manager, Robby Mook — who centered the Clinton
operation on data analytics (information about voters, given to him by number
crunchers) as opposed to more old-fashioned methods of polling, knocking on
doors and trying to persuade undecideds — made one strategic mistake after
another, but was kept on by Clinton, despite her own misgivings.
Yet “predictive analytics” continues to be sold, literally
and figuratively, to child welfare systems as a way to target which parents
should have their children taken away.
In fact, as is discussed indetail here, predictive analytics magnifies the racial and class biases
that are built into the child welfare.
It will work every bit as well in child welfare as it did in
the Clinton campaign.
