Proofiness - Charles Seife [78]
The bill got off to a great start. The committee on education gave it the green light and a few weeks later the bill passed the House unanimously, sixty-seven votes to zero. Next up was the Senate. The bill was handed, appropriately enough, to the committee on temperance, which gave an enthusiastic thumbs-up. It would have passed the Senate but for the intervention of the chair of Purdue University’s math department, who explained to the senators why passage of the bill would make Indiana a laughingstock. After a brief debate, in which one senator exclaimed that one “might as well try to legislate water to run up hill as to establish mathematical truth by law,” the bill was shelved indefinitely. It was a rare legislative victory for the forces of mathematical reality.
Indiana’s abortive attempt to rewrite the laws of nature is absurd, but it’s not an isolated incident. Our governments misuse mathematics in subtler ways all the time, trying to banish facts that are embarrassing and inconvenient. And the most mind-bending denials of mathematical reality come from the branch of government that’s supposed to be the guardian of truth: the judiciary.
Our courts have been infected with proofiness. Mathematical and statistical knowledge can be used to free the wrongfully convicted, to help convict the guilty, and to reduce bias and injustice by law enforcement and the courts. However, attorneys use proofiness to free the guilty; prosecutors use it to convict the innocent. All through the court system, bogus mathematical arguments are used to justify injustice. The problem goes all the way to the top; even Supreme Court justices use phony statistics to push their own political agendas. These lies go far beyond mere political tinkering, far beyond messing with votes and manipulating the census. They are used to try to distort the nature of justice—and of truth.
In the hands of the courts, proofiness is a weapon of terrifying power. The alternate realities that judges construct quite literally have determined the difference between life and death.
The justice system can’t be totally free of lies and distortions; after all, courts are chock-full of lawyers. For many of them, glibness is a virtue—for a defense attorney, a specious argument might be just the thing to get a client off. And there’s nothing that’s better for confusing a jury than proofiness.
The famed defense attorney Alan Dershowitz has a well-earned reputation for running circles around prosecutors. His finest moment came in 1995 when he and his team got O. J. Simpson acquitted of a double murder. Despite an extraordinary amount of forensic evidence that seemed to prove Simpson guilty, Dershowitz and his colleagues threw up a cloud of obfuscation that allowed his client to walk away from the charges. And proofiness was a key element of that cloud.
Simpson had been arrested a number of years earlier for battering his then wife, so when she was stabbed to death, it was natural to consider Simpson a key suspect. Dershowitz, however, turned that piece of evidence completely upside down thanks to some phony probabilities. He convinced the jury that the battery made it incredibly improbable that Simpson murdered his ex-wife; after all, only one in a thousand wife-beaters winds up murdering his spouse. One in a thousand! Such a small probability means that O. J. Simpson almost certainly isn’t the murderer, right?
It’s hard to express just how wrong this argument is. It’s tantamount to turning Simpson’s wife-beating—a powerful indication of violent tendencies toward his spouse—into exculpatory evidence. And in fact, Dershowitz’s line of reasoning is transparently fallacious; it fails to take into account that the probability of being murdered is very small. A one in a thousand chance of a woman’s being killed by an abusive spouse is huge by comparison. When you crunch the probabilities properly, it becomes clear that if an abused woman is murdered, it is highly likely that the murderer is her abuser. (Using reasonable assumptions, separate groups of statisticians calculated