Data mining opens new doors for discrimination, marginalization
In a post at Scientific American, Michael Fertik took a look at how Internet data collection practices are beginning to create an unequal — even discriminatory — online environment. Fertik writes:
“For most of the Internet’s short history, the primary goal of this data collection was classic product marketing: for example, advertisers might want to show me Nikes and my wife Manolo Blahniks. But increasingly, data collection is leapfrogging well beyond strict advertising and enabling insurance, medical and other companies to benefit from analyzing your personal, highly detailed ‘Big Data’ record without your knowledge. Based on this analysis, these companies then make decisions about you — including whether you are even worth marketing to at all.”
The consequences of such detailed data mining run deep. Fertik notes that advances in online data mining are enabling companies to “skirt the spirit of the law” and make discriminatory choices in who receives credit or loan offers, for example, by simply not displaying online offers to less credit-attractive users. “If you live on the wrong side of the digital tracks,” he says, “you won’t even see a credit offer from leading lending institutions, and you won’t realize that loans are available to help you with your current personal or professional priorities.”
Fertik also points to Google’s recent technology patent that enables dynamic pricing — “it can push the base price of an e-book up if it determines you are more likely to buy that particular item than an average user; conversely, it can adjust the price down as an incentive if you are judged less likely to purchase.” All with the consumer being completely unaware.
In a similar vein in a post at the PBS Idea Lab, Sean McDonald took a look at Internet data collection practices and argues they’re creating a “Data Divide”: “the marginalization of individual interests in the collection, analysis, use, and commercialization of data generated through digital interactions to the disproportionate benefit of institutions and service providers.” Basically, big companies and governments are wielding all the power over and reaping the benefits from consumer data, often with the consumer being unaware or not having a choice.
McDonald argues that conversations about personal data need to move beyond security issues to include how the value of that data is shared, and that the “Do Not Track” policies kind of miss the point, creating an all-or-nothing scenario. “What if there was a middle ground?” He asks. “What if you could share in the value that you create, simply by doing whatever it is you already do on these platforms?”
You can read Fertik’s piece at Scientific American and McDonald’s piece at PBS Idea Lab — they are this week’s recommended reads. You might also be interested in Alistair Croll’s related posts: “Thin walls and traffic cameras,” “New ethics for a new world” and “Big data is our generation’s civil rights issue, and we don’t know it.”
Big data is changing the way we fight crime
Highlighting law enforcement’s recent use of Google to apprehend art thieves in two separate cases, Felix Salmon took a look at the increasing use of big data in crime fighting and how such practices are becoming democratized. He points to the data mining team assembled by the SEC, and how a group of journalists at the Sun Sentinel in Florida were able to uncover evidence of 800 police officers driving 90 to 130 miles per hour on Florida highways — not in pursuit of offenders, but in their daily commutes.
Big data could be changing crime itself as well. Salmon points out that “as data mining techniques continue to evolve, and as databases become increasingly unified and tractable, and our lives are lived almost entirely online, it’s going to be harder and harder for criminals not to leave a discoverable data trail.” You can read Salmon’s piece at Reuters.
In related news, the TechAmerica Foundation has released a new study (PDF) reviewing the use of big data in government. Frank Konkel reports at FCW that the study surveyed 200 state and federal IT officials, 75% of whom responded that “big data could help government cut the federal budget, save lives, enhance citizens’ quality of lives and reduce crime.” Konkel notes a highlight from the study, that “[p]olice departments are currently using big data technology to develop predictive models about when and where crimes are likely to occur, helping dramatically reduce the overall crime rate in specific locations.”
Also notable in the study were the responses related to real-time data: 82% of those surveyed said “real-time big data is the way of the future,” that it could “save the government 10% or more annually,” that they felt real-time data could save “a significant number of lives each year,” and 65% said real-time queries would be “much more useful” than their current methods. The most significant barriers to adoption, according to those surveyed, are privacy concerns — explaining that big data is not “Big Brother.” You can access the study report at TechAmerica (PDF).
NBA fans get big basketball data
The NBA launched its NBA.com/Stats site this week, providing fans access to basketball big data previously only available to league personnel. Richard Lawler reports at Engadget that the platform offers up “box scores that go as far back as [the league’s] start in 1946-47, individual stats for anyone who has ever played in the league plus advanced statistical breakdowns and rankings of best lineup combinations.”
Jeff Beckham reviews many of the site’s features in a post at Wired. He notes that the platform was built on SAP’s HANA database, as it’s able to handle “even larger data sets than all NBA stats from the past 67 years” and provide “quick responses to a nearly unlimited combination of stats.”
Beckham notes that new game stats will be available about 15 minutes after the end of a game.
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