A 2017 District of Columbia court case is illustrative of this fact. In that case, an anonymous defendant who was being represented by Public Defender Service attorney Rachel Cicurel nearly experienced the fallout from faulty programming that was presented as evidence in court.
The worry that emerges borders on the dystopian — that flawed or biased systems are being dressed up in the unassailable robes of mathematics, machine-learning capabilities, and data and wrongfully taking away people’s freedoms.It’s just this facet of human behavior — that the products of human minds are bound to the same subjective bias' as their designers — that has people like US House Representative Mark Takano worried.
“You see courts all over the map with inconsistent conclusions,” he says. “We need some way in which to provide some national guidance to the justice system about what standards these programs need to meet. This is something that defendants and prosecutors can’t do on their own, and the software companies can’t do on their own.
“This is what we do in my bill, we charge NIST with, not deciding whether the software works or not, but establishing standards, establishing the guidance to courts and prosecutors and defenders what the software needs to be able to do in order to be valid and reliable.”Machine-learning algorithms are excellent at finding patterns in data. Give an algorithm enough statistics on crime and it will find interesting constellations in the dataset.
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