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  3. Analog-era minds have a hard time processing a key product of the digital era: the staggering amount of information being create

Analog-era minds have a hard time processing a key product of the digital era: the staggering amount of information being create

admin2014-09-09  36
问题     Analog-era minds have a hard time processing a key product of the digital era: the staggering amount of information being created, collected and correlated. What’s called "big data" already identifies flu outbreaks and treatments for premature babies, and it predicts apartment overcrowding and airline delays. Explaining this is the focus of a new book, "Big Data: A Revolution That Will Transform How We Live, Work, and Think," written by Oxford scholar Viktor Mayer-Schonberger and Kenneth Cukier, data editor of the Economist. The book should spur policy makers to rethink how to protect privacy while enabling more access to data.
    Big data differs from traditional information in mind-bending ways. For one thing, the authors write, " society will need to shed some of its obsession for causality in exchange for simple correlations: not knowing why but only what. This overturns centuries of established practices and challenges our most basic understanding of how to make decisions and comprehend reality. "
    Until recently, big data made for interesting anecdotes, but now it has become a major source of new knowledge. Google is better that the Centers for Disease Control at identifying flu outbreaks. Google monitors billions of search terms("best cough medicine," for example)and adds location details to track outbreaks. When Wal-Mart analyzed correlations using its customer data and weather, it found that before storms, people buy more flashlights but also more Pop-Tarts, even though marketers can’t establish a causal relationship between weather and toaster pastries.
    Technology researchers in Canada analyzed premature births, tracking more than 1000 data points per second. They shocked doctors by showing that when vital signs are unusually stable, that correlates with a serious fever 24 hours later. Physicians now prevent fevers through treatment though causation remains a mystery.
    Data scientists working for New York City analyzed hundreds of data points to predict where owners were illegally subdividing houses and apartments, which leads to overcrowding and raises the risk of serious fires. By tracking data, including foreclosure proceedings and reports of rodents, inspectors were able to filter complaints so efficiently that they found dangerous conditions 70% of the time they inspected, an increase from 13%. Air travelers can now figure out which flights are likeliest to be on time, thanks to data scientists who tracked a decade of flight history correlated with weather patterns. Credit scores predict who needs reminders to take medicine. Publishers use data from text analysis and social networks to give readers personalized news.     Using big data to improve health care is one of the biggest opportunities, but current laws make it hard to mine even data aggregated from many patients. If we had electronic records of Americans going back generations, We’ d know more about genetic propensities, correlations among symptoms, and how to individualize treatments.
    "Instead of focusing on the problems of inadvertent disclosure or misuse, which are admittedly very real," Mr. Cukier said in an interview, "we need to balance those risks with the great potential of making health-care data available to researchers. I’m certain that in the future, we will be aghast if doctors don’t turn to big data to aid them in treating patients, just as today we’d be terrified if a pilot tried to land a jumbo jet without computer instrumentation. " Mr. Cukier’s book is a surprise best seller in China. "Big data is emerging just as China is now strong, and so it’s an area where they may be able to be a global leader, and steal a march on Silicon Valley," he says. In the U. S. , much of the privacy debate has focused on targeted online advertising. The authors identify more worrisome issues, such as "penalties based on propensities. "
    Law enforcement is using data to identify streets, groups and even individuals to track through "predictive policing". This is fine so long as it doesn’t extend, as the movie "Minority Report" imagined, to punishing people for crimes the data say they likely will commit. "If we hold people responsible for predicted future acts," the authors warn, "we also deny that humans have a capacity for moral choice. " Big data shouldn’ t become a tool to collectivize human choice and abandon free will. "
    The authors compare policy choices arising from big data to how governments responded to the printing press by censoring books and newspapers: "As centuries passed, we opted for more information flows rather that less, and to guard against its excesses not primarily through censorship but through rules that limited the misuse of information. " Wise policy on big data will follow the precedent of the printing press to allow broader access to information, while finding creative ways to limit its misuse. Big data is too big a deal to suppress.
What are the possible problems related to law enforcement in using big data?
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答案in law enforcement, with use of big data to identify + "track" criminal acts or suspects, "predictive policing"/if used over extensively, might lead to unexpected + unwanted results or consequences/wrong judgment/as the two authors suggest, big data should not be used as a tool "to collectivize human choice and abandon free will"/worrisome problems: "penalties based on propensities(tendencies)"/in other words, individual human moral choice and free will must be respected/to limit the misuse of information
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