"When it comes to terrorism, however, trillions of connections exist between people and events — things that the data-mining system will have to “look at” — and very few plots. This rarity makes even accurate identification systems useless. Let’s look at some numbers. We’ll be optimistic — we’ll assume the system has a one in 100 false-positive rate (99 percent accurate), and a one in 1,000 false-negative rate (99.9 percent accurate). Assume 1 trillion possible indicators to sift through: that’s about 10 events — e-mails, phone calls, purchases, web destinations, whatever — per person in the United States per day. Also assume that 10 of them are actually terrorists plotting. This unrealistically accurate system will generate 1 billion false alarms for every real terrorist plot it uncovers. Every day of every year, the police will have to investigate 27 million potential plots in order to find the one real terrorist plot per month. Raise that false-positive accuracy to an absurd 99.9999 percent and you’re still chasing 2,750 false alarms per day — but that will inevitably raise your false negatives, and you’re going to miss some of those 10 real plots. This isn’t anything new. In statistics, it’s called the “base rate fallacy,” and it applies in other domains as well. For example, even highly accurate medical tests are useless as diagnostic tools if the incidence of the disease is rare in the general population. Terrorist attacks are also rare, any “test” is going to result in an endless stream of false alarms. This is exactly the sort of thing we saw with the NSA’s eavesdropping program: the New York Times reported that the computers spat out thousands of tips per month. Every one of them turned out to be a false alarm. And the cost was enormous — not just for the FBI agents running around chasing dead-end leads instead of doing things that might actually make us safer, but also the cost in civil liberties."
Posted on: Tue, 09 Jul 2013 23:59:29 +0000
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