The Fifth Risk(39)
One version of the future revealed itself in March 2015. The National Weather Service had failed to spot a tornado before it struck Moore, Oklahoma. It had spun up and vanished very quickly, but, still, the people in the Weather Service should have spotted it. AccuWeather quickly issued a press release bragging that it had sent a tornado alert to its paying corporate customers in Moore twelve minutes before the tornado hit. The big point is that AccuWeather never broadcast its tornado warning. The only people who received it were the people who had paid for it—and God help those who hadn’t. While the tornado was touching down in Moore, AccuWeather’s network channel was broadcasting videos of . . . hippos, swimming.
When, at the request of the Trump White House, the former Bush Commerce Department official wrote up his list of people he believed were suited to run the National Oceanic and Atmospheric Administration, and the National Weather Service inside it, it never occurred to him to put Barry Myers’s name on it. “I don’t want someone who has a bottom line, or a concern with shareholders, in charge of saving lives and protecting property,” he said. But it was more than that. To put Barry Myers in charge of NOAA was to give him control over maybe the most valuable and necessary pile of data that the U.S. government collects. “The more people have access to the weather data, the better it is for the country,” said the Bush official. “There’s so much gold in there. People just don’t know how to get to it.”
DJ Patil had gone to Washington in 2014 to help people find that gold. He was the human expression of an executive order Obama had signed the year before, insisting that all unclassified government data be made publicly available and that it be machine-readable. DJ assumed he’d need to leave when the man who hired him left office, so that gave him just two years. “We did not have time to collect new data,” he said. “We were just trying to open up what we had.”
He set out to make as many connections as possible between the information and the people who could make new sense of it—to encourage them to use the data in novel and interesting ways. “I was looking to find people like me, when I was a student,” he said. “We’re going to open all the data and go to every economics department and say,‘Hey, you want a PhD?’ In every agency there were questions to be answered. Most of the answers we have gotten have not come from government. They’ve come from the broad American public who has access to the data.”
The opioid crisis was a case in point. The data scientists in the Department of Health and Human Services had opened up the Medicaid and Medicare data, which held information about prescription drugs. Journalists at ProPublica had combed through it and discovered odd concentrations of opioid prescriptions. “We would never have figured out that there was an opioid crisis without the data,” said DJ.
The big pools of raw facts accumulated by the federal government are windows into American life. A team of researchers at Stanford University, led by an economist named Raj Chetty, used newly accessible data from the Internal Revenue Service to write a series of papers that addressed questions of opportunity in American life. One, titled “The Fading American Dream,” asked a simple question: How likely is it that an American child will be better off than his parents? The IRS data allowed Chetty to study Americans across generations, and the census data let him compare them by race, gender, or whichever trait he wished to isolate. In the data he found an answer to his question, and much more. He discovered that while just over 90 percent of children born in 1940 went on to earn more than their parents, only 50 percent of children born in the 1980s did so. Every year, the economic future of an American child was a bit less bright. And the big reason was not lower rates of economic growth but the increasingly unequal distribution of money. More and more of the gains were being captured by the very rich. Mobility had a racial dimension as well: A white child born into the upper-income quintile was five times more likely to stay there than to fall to the bottom. A black child born into the upper-income quintile was as likely to fall to the bottom as to remain rich.
More of America’s problems than even DJ had imagined could be better understood and addressed with better access to the right information. The problem of excessive police force was another example. After a white policeman shot a defenseless black man in Ferguson, Missouri, the White House convened police chiefs from ten American cities, along with their data. The policing data was local and difficult to get ahold of—and that was DJ’s point. He wanted to show what might be possible if the government collected the information. “We asked the question: What causes excessive use of police force?” Combing the data from the ten cities, a team of researchers from several American universities found a pattern that would have been hard to spot with the naked eye. Police officers who had just come from an emotionally fraught situation—a suicide, or a domestic abuse call in which a child was involved—were more likely to use excessive force. Maybe the problem wasn’t as simple as a bad cop. Maybe it was the emotional state in which the cop had found himself. “Dispatch sent them right back out without time to decompress,” said DJ. “Give them a break in between and maybe they behave differently.”
A young guy in the White House pulled up stop-and-search rates from another pile of policing data. He discovered that a black person in a car was no more likely to be pulled over by the police than a white person. The difference was what happened next. “If you’re black you’re way more likely to get searched,” said DJ. But then he noticed another pattern: not all the cops exhibited the same degree of racial bias. A few cops in one southern city were ten times more likely than others to search a black person they had pulled over. Right there in the White House, the young researcher showed the data to the city’s police chief. “He genuinely had no idea,” said DJ. “He was like,‘Can you please tell me more?’”