Big data makes it possible to predict which children will grow up to be the greatest economic burden on the community, according to an article in a new journal, Nature Human Behaviour. Researchers who analysed the lives of nearly a thousand people from birth to age 38 in the New Zealand city of Dunedin found that 20% of the population accounts for 80% of social costs such as crime, welfare dependence and health-care needs when they are adults.
Big Data is essential to identify candidates. “We know every location they’ve lived, every name they’ve used. We’re able to match them with pretty much 100% accuracy back for many years,” said Terrie Moffitt, a Duke researcher.
The research group was also testing the Pareto principle: or the “80-20 rule.” Italian engineer and social scientist Vilfredo Pareto observed a century ago that 80% of wealth is controlled by 20% of the population. This is also a rule of thumb in computer science, biology, physics, economics and many other fields.
“Most expenses from social problems are concentrated in a small segment of the population,” said Avshalom Caspi, of Duke University, the lead author. “So whatever segment of the health, social or judicial system that you look at, we find a concentration. And that concentration approximates what Pareto anticipated over 100 years ago. We called the group 'high-needs/high-costs’.”
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