This report from Oliver Roeder of FiveThirtyEight, a site that lives on Big Data analysis, is disturbing:
For decades, the court has struggled with quantitative evidence of all kinds in a wide variety of cases. Sometimes justices ignore this evidence. Sometimes they misinterpret it. And sometimes they cast it aside in order to hold on to more traditional legal arguments. (And, yes, sometimes they also listen to the numbers.) Yet the world itself is becoming more computationally driven, and some of those computations will need to be adjudicated before long. Some major artificial intelligence case will likely come across the court’s desk in the next decade, for example. By voicing an unwillingness to engage with data-driven empiricism, justices — and thus the court — are at risk of making decisions without fully grappling with the evidence.
This problem was on full display earlier this month, when the Supreme Court heard arguments in Gill v. Whitford, a case that will determine the future of partisan gerrymandering — and the contours of American democracy along with it. As my colleague Galen Druke has reported, the case hinges on math: Is there a way to measure a map’s partisan bias and to create a standard for when a gerrymandered map infringes on voters’ rights? …
Four of the eight justices who regularly speak during oral arguments1 voiced anxiety about using calculations to answer questions about bias and partisanship. Some said the math was unwieldy, complicated, and newfangled. One justice called it “baloney” and argued that the difficulty the public would have in understanding the test would ultimately erode the legitimacy of the court.
Justice Neil Gorsuch balked at the multifaceted empirical approach that the Democratic team bringing the suit is proposing be used to calculate when partisan gerrymandering has gone too far, comparing the metric to a secret recipe: “It reminds me a little bit of my steak rub. I like some turmeric, I like a few other little ingredients, but I’m not going to tell you how much of each. And so what’s this court supposed to do? A pinch of this, a pinch of that?”
Justice Stephen Breyer said, “I think the hard issue in this case is are there standards manageable by a court, not by some group of social science political ex … you know, computer experts? I understand that, and I am quite sympathetic to that.”
I have to wonder if this has to do with the simplicity of the application of principle vs. the messiness of empirical analysis. A principle is a rule applied to situations which, if a valid principle, should ensure a positive outcome. On the other side, empirical analysis, which is the analysis of the information concerning the specific situation, should be used to affirm or invalidate the principle applied to the situation. The law often consists of discovering and applying the proper principle to the given allegedly illicit activity.
In the specific case concerning alleged gerrymandering, the efficiency gap is the measure of how many votes are wasted. This measurement correlates, according to the complaint, to the theoretical amount of gerrymandering. So, as Oliver writes, the role of the Court should be to determine what value of efficiency gap constitutes an illegal gerrymander.
To my mind, beyond the fact that this simple mathematical measurement is baffling some of the justices, they should be doing what the courts have done for centuries – employ experts to explain the evidence. The possibility “… that the difficulty the public would have in understanding the test would ultimately erode the legitimacy of the court …” is merely a hypothetical concern which could certainly be allayed through public education.
And the important fact on the ground is this: the public perception that gerrymandering is taking place in States such as Wisconsin and North Carolina is already damaging the perception that this is a fairly constituted democracy. If the democracy capsizes and goes down, SCOTUS goes down with it. Both wings of the court need to drop their ideological blinders and their allergies to math and really work on this case and try to understand how to measure gerrymandering – and how to stop it.
