Tag Archives | Data Mining

The (Unintentional) Amazon Guide to Dealing Drugs

Some fantastic data mining detective work is revealed by Alexis Madrigal at The Atlantic:
One day, some drug dealer bought a particular digital scale—the AWS-100— on the retail site, Amazon.com. And then another drug dealer bought the same scale. Then another. Then another. Amazon's data-tracking software watched what else these people purchased, and now, if you buy the AWS-100 scale, Amazon serves up a quickstart kit for selling drugs. Amazon drug list Along with various scale-related paraphernalia, we find:
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Algocracy: The Threat Of Rule By Algorithm

microchip

Will democracy give way to algocracy? Via the Institute for Emerging Ethics & Technologies, John Danaher writes:

In brief, modern technology has made it possible for pretty much all of our movements, particularly those we make “online”, to be monitored, tracked, processed, and leveraged. We can do some of this leveraging ourselves, by tracking our behavior to improve our diets, increase our productivity and so forth. But, of course, governments and corporations can also take advantage of these data-tracking and processing technologies.

Data-mining [could create] a system of algorithmic regulation, one in which our decisions are “nudged” in particular directions by powerful data-processing algorithms. This is worrisome because the rational basis of these algorithms will not be transparent:

Thanks to smartphones or Google Glass, we can now be pinged whenever we are about to do something stupid, unhealthy or unsound. We wouldn’t necessarily need to know why the action would be wrong: the system’s algorithms do the moral calculus on their own.

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How Accepting A Friend Request Will Soon Alter Your Credit Score

credit scoreThe The Next Web writes that you will soon be “empowered” by having every mundane aspect of your life mined for data:

Are you only as good as the company you keep? Before you accept that next friend request, consider what that person says about you, what that association might eventually cost, or be worth – even in the financial sense.

Where you live, who you friend on Facebook, the frequency you shop at Trader Joe’s, how much you spend – all of this information will be picked up, shared, and analyzed amongst the various connected devices and services you use.

This wealth of data will also be applicable to your financial decisions. “Who you are” as a consumer will no longer be based solely on your purchases, investments or credit file, but will also consider your daily routines, such as browsing the Internet, where you shop, and more.

Technology and new services are now making it possible to incorporate entirely new, more relevant data into a credit profile — data that is mostly consumer controlled or contributed and generated by simply gathering and delivering your lifestyle data.

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Data Companies Sell Lists Of Rape Victims, HIV Sufferers, People On Various Medications For 8¢ Per Name

rape-sufferers-listHonestly, I think what will most spur members of Congress to action on this issue is that databases of Americans with erectile dysfunction are among those being sold. Forbes writes:

In a congressional hearing this week, Pam Dixon, executive director of the World Privacy Forum, revealed disturbing lists that she has found for sale from data brokers you’ve likely never heard of, including a “Rape Sufferers List” from a company called MEDbase 200, which sells lists about the medical industry.

The list, which was taken down yesterday after an inquiry from the Wall Street Journal, is still cached, as are some other disturbing lists such as “erectile dysfunction sufferers,” “alcoholism sufferers” and “ AIDS/HIV sufferers.“ All the lists promised 1,000 names for the low of $79:

“Select from families affected by over 500 different ailments, or who are consumers of over 200 different Rx medications. Lists can be further selected on the basis of lifestyle, ethnicity, geo, gender, and much more.”

 

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How to Protect Ourselves on Social Networks and from Data Collection Systems of Governments and Corporations

via chycho
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I. What’s Going On

Online, we are both a product for corporations and a person of interest to governments (2, 3).

Corporations are taking advantage of these times by changing their privacy policies so that they can track us, use us, and sell us whatever their algorithms decide that we need or want based on data they have acquired about our movements, contacts, desires, fantasies, or kinks. Governments on the other hand are using our data to make sure that we will never acquire enough power to change any policies that we deem to be a threat to our happiness, livelihood, or survival. In essence, we are at war with these organizations and we should act as such:

“…this is truly unprecedented in history. And what we’re seeing is secrecy and surveillance are completely subverting security and liberty, not just in the United States, but for many, many citizens around the world.”

This corporate misconduct and government surveillance is threatening the internet (2, 3), the original purpose of which was to create an “open architecture networking” system where “a globally interconnected set of computers” would allow “everyone” to “quickly access data and programs from any site”.

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The NSA Is Watching Your Online Dating Profile

unsplash1Are you a match? From an NPR piece on surveillance, corporations and the government absorbing data from dating sites in order to reveal the real you:

Examples from the series include online dating sites, like OKCupid.com. The report shows how profile questions on the site about things like drug use, religious beliefs and more were transmitted to a data tracking company, along with the user’s IP address.

When you log in with a username and password to sites like Gmail, Amazon or OKCupid, your behavior can be linked to your real name or email address. Software privacy specialist Ashkan Soltani said personally identifying information also can unintentionally “leak” to third parties, even if companies say they have no need for such data; it’s not clear what happens to the information once it falls into their hands.

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The Future Of Data Mining Your Health

data mining

In a few years, will corporations, employers, insurers and others track “diseased lists” of individuals whose social media, smartphone, and purchasing activity hints that they may have health problems? Via PandoDaily, Michael Carney writes:

According to a sales rep for a midwest data co-location and analytics startup who asked to remain anonymous, regional hospitals, insurers, and grocery retailers are already investigating ways to work together to translate consumer purchase data into health risk profiling insights.

Kevin Pledge, CEO of underwriting-technology consultancy Insight Decision Solutions told the Economist last year that he has forgone the use of supermarket loyalty-cards and begun paying cash for his burgers to avoid this very type of profiling. The same article mentions a life-settlements firm declining to purchase an insurance policy based on social media activity that contradicted the supposed poor health of the policy-holder.

As we document and share more of where we go, what we do, who we spend time with, what we eat, what we buy, how hard we exert ourselves, and so on, we create more data that companies can and will use to evaluate our worthiness – or lack thereof – for their products, services, and opportunities.

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Why Hunting For Terrorism With A Data Panopticon Doesn’t Work

data miningFrom seven years ago, Bruce Schneier explains why collecting massive amounts of data won’t allow us to find terrorist patterns hidden within:

Many believe that data mining is the crystal ball that will enable us to uncover future terrorist plots. But we’re not going to find terrorist plots through systems like this. We’re not trading privacy for security; we’re giving up privacy and getting no security in return.

Data mining works best when there’s a well-defined profile you’re searching for, a reasonable number of attacks per year, and a low cost of false alarms. Credit card fraud is one of data mining’s success stories: all credit card companies data mine their transaction databases, looking for spending patterns that indicate a stolen card. Many credit card thieves share a pattern — purchase expensive luxury goods, purchase things that can be easily fenced, etc. — and data mining systems can minimize the losses in many cases by shutting down the card.

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Anomalies, Prisons, and Geophysics: How Governments Use Data and How to Stop Them

via chycho

A common definition of an anomaly is “a deviation from the common rule, type, arrangement, or form.” This definition, however, can be simplified by stating that an anomaly is a deviation from specific parameters. The defining characteristic of an anomaly is that it can only exist in a comparative setting, implying that it can only be detected within a certain data set. Once a data set is obtained then parameters can be specified to filter out so called anomalies for evaluation. Depending on the type of data collected, these parameters can be specified to be anything occurring in any combination. If there is no data set, then there are no anomalies.

A prison can be defined as “a place of seeming confinement.” It is a place to incarcerate people who have lawfully or unlawfully stepped outside the parameters set in their society. This implies that inmates are anomalies within a community.… Read the rest

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Predicting Trends Beforehand

In this age of constant advertisement and brand placement, trending topics on Twitter have become a great free way for advertisers to get their message in front of more potential customers. The only problem is that no one can predict what will be come a trending topic, at least until now.  A professor at M.I.T. in conjunction with one of his students, developed an algorithm that they claim will be 95% accurate in predicting those trending topics as much four to five hours before they are trending.

Picture: Unmadindu (CC)

Via M.I.T.

At the Interdisciplinary Workshop on Information and Decision in Social Networks at MIT in November, Associate Professor Devavrat Shah and his student, Stanislav Nikolov, will present a new algorithm that can, with 95 percent accuracy, predict which topics will trend an average of an hour and a half before Twitter’s algorithm puts them on the list — and sometimes as much as four or five hours before.

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