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Perhaps the greatest strength of the randomized controlled trial is in combating what’s known as selection bias. That occurs when groups being studied (intervention and control) are already significantly different after they are “selected” to be in the intervention or not. One of the most elegant examples of why we need such trials came recently in an examination of employer-sponsored wellness programs.

It Might Soon Be Legal for Employers to Force You Into a Genetic Test

Say your employer wants you to get a genetic test. You politely decline because you consider it a gross infringement of privacy. Well, too bad—your monthly health insurance payments just spiked 30%.

In December, 2015, the Migration Board rejected their final appeal, and, in a letter, told the family, “You must leave Sweden.” Their deportation to Russia was scheduled for April. Soslan said that to his children Russia “might as well be the moon.” Georgi read the letter silently, dropped it on the floor, went upstairs to his room, and lay down on the bed. He said that his body began to feel as if it were entirely liquid. His limbs felt soft and porous. All he wanted to do was close his eyes. Even swallowing required an effort that he didn’t feel he could muster. He felt a deep pressure in his brain and in his ears. He turned toward the wall and pounded his fist against it. In the morning, he refused to get out of bed or to eat. Savl poured Coca-Cola into a teaspoon and fed Georgi small sips. The soda dribbled down his chin.

As the doctor Mark Tonelli has argued, distinct forms of knowledge can’t be judged by the same standards: what a patient prefers on the basis of personal experience; what a doctor thinks on the basis of clinical experience; and what clinical research has discovered — each of these is valuable in its own way. While scientists concur that randomized trials are ideal for evaluating the average effects of treatments, such precision isn’t necessary when the benefits are obvious or clear from other data.

Distrusting expertise makes it easy to confuse an absence of randomized evaluations with an absence of knowledge. And this leads to the false belief that knowledge of what works in social policy, education or fighting terrorism can come only from randomized evaluations. But by that logic (as a spoof scientific article claimed), we don’t know if parachutes really work because we have no randomized controlled trials of them.

Experiments, of course, are invaluable and have, in the past, shown the consensus opinion of experts to be wrong. But those who fetishize this methodology, as the flossing example shows, can also impair progress toward the truth. A strong demand for evidence is a good thing. But nurturing a more nuanced view of expertise should be part of that demand.

“It’s a parallel to what the tobacco industry did,” Mike Moore told me. “They got caught in America, they saw their market share decline, so they export it to places with even fewer regulations than we have.” He added, “You know what’s going to happen. You’re going to see lots and lots of death.” In May, several members of Congress wrote to the World Health Organization, urging it to help stop the spread of OxyContin, and mentioning the Sackler family by name. “The international health community has a rare opportunity to see the future,” they wrote. “Do not allow Purdue to walk away from the tragedy they have inflicted on countless American families simply to find new markets and new victims elsewhere.”

A former journalist, equipped with an algorithm and the largest collection of murder records in the country, finds patterns in crime.

So what, exactly, did the algorithm “learn” about the process of dying? And what, in turn, can it teach oncologists? Here is the strange rub of such a deep learning system: It learns, but it cannot tell us why it has learned; it assigns probabilities, but it cannot easily express the reasoning behind the assignment. Like a child who learns to ride a bicycle by trial and error and, asked to articulate the rules that enable bicycle riding, simply shrugs her shoulders and sails away, the algorithm looks vacantly at us when we ask, “Why?”

How Is ‘Dune’ So Prescient About Climate Change? Thank This Native American Tribe.