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If Amazon can already study your history, predict your purchases and ship them before you even place an order – the online retailer’s “anticipatory shipping” technique – imagine what predictions other data-heavy companies could make.

For example, in a year or two, Google will be present in your car (thanks to its self-driving vehicles but also to the Android operating system that powers other models); in your bedroom (thanks to its acquisition of Nest, which manufactures smart thermostats and smoke detectors); in your pocket (through Android-powered smartphones); and in your entire visual field (via Google Glass, the wearable camera and screen).

In knowing your routes, your daily patterns and your contacts, Google has a far better picture of risk – for example, the odds that you will have an accident or default on a mortgage – than any insurance company or bank. And, in having unmediated access to you via your phone, Google can also sell you insurance or make you an offer for your personal data on the go, using a price point that you are most likely to accept.

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Retailers and banks can also reduce risk by moving away from cards that use magnetic strips, which are easily faked. Many countries in Europe, Asia and elsewhere have already replaced magnetic strips with chips, which are harder to duplicate. Chip-based cards also require customers to enter a secure code before they can be used. That’s partly why the United States accounts for nearly half of all global credit card fraud, even though it generates only about a quarter of all credit card spending. American retailers, including Target, have resisted (foolishly, as it turns out) the introduction of chip-based cards because they would have to invest in new equipment to handle them. (Target now says it supports chip-based cards.)

No security measure will ever rid the economy of theft and fraud completely. But there is evidence that companies could do a lot more to protect data.

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This online ad customization technique is known as behavioral targeting, but Pandora adds a music layer. Pandora has collected song preference and other details about more than 200 million registered users, and those people have expressed their song likes and dislikes by pressing the site’s thumbs-up and thumbs-down buttons more than 35 billion times. Because Pandora needs to understand the type of device a listener is using in order to deliver songs in a playable format, its system also knows whether people are tuning in from their cars, from iPhones or Android phones or from desktops.

So it seems only logical for the company to start seeking correlations between users’ listening habits and the kinds of ads they might be most receptive to.

http://www.nytimes.com/2014/01/05/technology/pandora-mines-users-data-to-better-target-ads.html?ref=todayspaper

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