Data Intelligence, Business Analytics
This article was also published on Smart Blogs
Eric Siegel, Ph.D.
Retirement kills more people than hard work ever did.
I'm not afraid of death; I just don't want to be there when it happens.
Who benefits by predicting your behavior? Organizations do—companies, government agencies, and political campaigns. They employ predictive analytics, technology that learns from data to render per-person predictions, one individual at a time.
The payoff for predicting extends beyond boosting sales and winning elections: everyone benefits when this technology strengthens the fight against risk, crime, and even spam.
In these efforts, each important thing a person does can be valuable to predict, namely click, buy, steal, drop out of school, quit your job, donate, crash your car, or vote.
So how about the final thing each of us do, die? In fact, there are five reasons organization predict your death. Sometimes they do it with altruistic intent, for healthcare-related purposes. In other cases, there's a financial incentive—they predict death for the money.
To begin with, there are two fairly well-known reasons to predict when an individual's death will come:
1. Healthcare: predicts death to help prevent it. For example, Riskprediction.org.uk predicts your risk of death in surgery, based on aspects of you and your condition, in order to help inform medical decisions. In other work, psychiatric research predicts which patients are at the greatest risk of suicide.
2. Life insurance: prices policies according to predicted life expectancy. A growing number of life insurance companies go beyond conventional actuarial tables and employ predictive analytics to establish mortality risk. It's not called death insurance, but their core analytical competency is to calculate when you are going to die.
Solo rockers die younger than those in bands. Although all rock stars face higher risk, solo rock stars suffer twice the risk of early death as rock band members. This may be due to the fact that band members benefit from peer support and solo artists exhibit even riskier behavior (factoid courtesy of public health offices in the UK).
Men on the Titanic faced much greater risk than women. A woman on the Titanic was almost four times as likely to survive as a man. Most men died and most women lived. This may be due to the fact that priority for access to life boats was given to women.
Retirement is bad for your health. For a certain working category of males in Austria, each additional year of early retirement was shown to decrease life expectancy by 1.8 months. This may be due to the fact that unhealthy habits such as smoking and drinking follow retirement (factoid courtesy of the University of Zurich).
3. Law enforcement and military: predict kill victims in order to protect. U.S. Armed Forces conduct research to analytically predict terrorist attacks. Researchers also assess the risk to individual soldiers, e.g., when parachuting. Law enforcement in Maryland applies predictive models to detect inmates more at risk to be perpetrators or victims of murder. Further, university and law enforcement researchers have developed predictive models that foretell murder among those previously convicted for homicide.
4. Safety institutes: predict system failure casualties. For example, researchers have identified aviation incidents that are five times more likely than average to be fatal, using data from the National Transportation Safety Board.
5. A top-five U.S. health insurance company: predicts the likelihood an elderly insurance policy holder will pass away within 18 months in order to trigger end-of-life counseling, e.g., regarding living wills and palliative care. The predictions are based on clinical markers in the insured's recent medical claims.