Will those insights be tested, or simply used to justify the status quo and reinforce prejudices? When I consider the sloppy and self-serving ways that companies use data, I'm often reminded of phrenology, a pseudoscience that was briefly the rage in the nineteenth century. Phrenologists would run their fingers over the patient's skull, probing for bumps and indentations. Each one, they thought, was linked to personality traits that existed in twenty-seven regions of the brain. Usually the conclusion of the phrenologist jibed with the observations he made. If the patient was morbidly anxious or suffering from alcoholism, the skull probe would usually find bumps and dips that correlated with that observation - which, in turn, bolstered faith in the science of phrenology. Phrenology was a model that relied on pseudoscientific nonsense to make authoritative pronouncements, and for decades it went untested. Big Data can fall into the same trap. Models like the ones that red-lighted Kyle Behm and black-balled foreign medical students and St. George's can lock people out, even when the "science" inside them is little more than a bundle of untested assumptions. Cathy ONeil
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For years, insurance companies have been using the same data set to determine rates for auto insurance. It includes the age of the driver, their driving history, where they live, their type of vehicle and the number of miles they drive. These variables all come together in a database that is updated periodically as people's driving habits change. This database has been used as the basis for insurance rates since the early twentieth century.

This data set has been used as an attempt to determine how much an individual will pay for car insurance. The results of this database were used as a basis for insurance companies to charge drivers based on their age and driving records and not on actual accident and traffic violations and crime statistics. However, there was no real backing or support behind the assumptions that these data sets were based on and no real objective way to test their validity.

Now that insurers can look at historical accident data and compare it with historical driving records to determine insurance rates, people are wondering if these rates will be adjusted over time to reflect new information about accidents or driving patterns?

Source: Weapons Of Math Destruction: How Big Data Increases Inequality And Threatens Democracy

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