[...] Companies were gathering millions of records from pharmacies. They then sold them on to insurers eager to gain a competitive advantage by avoiding people likely to incur high medical fees. Since 1 percent of patients account for over one-fifth of health care costs, and 5 percent account for nearly half of costs, insurers who can “cherry-pick” the healthy and “lemon-drop” the sick will see far more profit than those who take all comers. Prescription data gave insurers the information they needed to tailor policies to exclude preexisting conditions and to impose higher charges for some members.
in other news, for-profit healthcare is a giant scam=
[...] Companies were gathering millions of records from pharmacies. They then sold them on to insurers eager to gain a competitive advantage by avoiding people likely to incur high medical fees. Since 1 percent of patients account for over one-fifth of health care costs, and 5 percent account for nearly half of costs, insurers who can “cherry-pick” the healthy and “lemon-drop” the sick will see far more profit than those who take all comers. Prescription data gave insurers the information they needed to tailor policies to exclude preexisting conditions and to impose higher charges for some members.
in other news, for-profit healthcare is a giant scam=
[...] Marketers plot to tout beauty products at moments of the day that women feel least attractive. There’s little to stop them from compiling digital dossiers of the vulnerabilities of each of us. In the hall of mirrors of online marketing, discrimination can easily masquerade as innovation.
using data to overcome more of our natural defenses against advertising
[...] Marketers plot to tout beauty products at moments of the day that women feel least attractive. There’s little to stop them from compiling digital dossiers of the vulnerabilities of each of us. In the hall of mirrors of online marketing, discrimination can easily masquerade as innovation.
using data to overcome more of our natural defenses against advertising
[...] Runaway data can lead to cascading disadvantages as digital alchemy creates new analog realities. Once one piece of software has inferred that a person is a bad credit risk, a shirking worker, or a marginal consumer, that attribute may appear with decision-making clout in other systems all over the economy. [...]
[...] Runaway data can lead to cascading disadvantages as digital alchemy creates new analog realities. Once one piece of software has inferred that a person is a bad credit risk, a shirking worker, or a marginal consumer, that attribute may appear with decision-making clout in other systems all over the economy. [...]
[...] software engineers construct the datasets mined by scoring systems; they define the parameters of data-mining analyses; they create the clusters, links, and decision trees applied; they generate the predictive models applied. Human biases and values are embedded into each and every step of development. Computerization may simply drive discrimination upstream.
[...] software engineers construct the datasets mined by scoring systems; they define the parameters of data-mining analyses; they create the clusters, links, and decision trees applied; they generate the predictive models applied. Human biases and values are embedded into each and every step of development. Computerization may simply drive discrimination upstream.
[...] Laws prevent the government from collecting certain kinds of information on citizens, but data brokers are not so constrained. And once someone else has collected that information, little stops the government from buying it, demanding it, or even hacking into it.
Our off- and online actions are logged in hundreds of private-sector databases. Aptly called “big brother’s little helpers” by privacy expert Chris Hoofnagle, private-sector data brokers gather files that police would never be able to gather on their own, and then sell them to the police. This is not a “bug” in our surveillance system, but a “feature.” Note that the very definition of fusion centers includes their willingness to receive information from private parties. The Snowden leaks make the shared infrastructure of state and private data collection incontrovertible. Never again can data deregulationists claim that corporate data collection is entirely distinct and far less threatening than government surveillance. They are irreversibly intertwined.
[...] Laws prevent the government from collecting certain kinds of information on citizens, but data brokers are not so constrained. And once someone else has collected that information, little stops the government from buying it, demanding it, or even hacking into it.
Our off- and online actions are logged in hundreds of private-sector databases. Aptly called “big brother’s little helpers” by privacy expert Chris Hoofnagle, private-sector data brokers gather files that police would never be able to gather on their own, and then sell them to the police. This is not a “bug” in our surveillance system, but a “feature.” Note that the very definition of fusion centers includes their willingness to receive information from private parties. The Snowden leaks make the shared infrastructure of state and private data collection incontrovertible. Never again can data deregulationists claim that corporate data collection is entirely distinct and far less threatening than government surveillance. They are irreversibly intertwined.