Talking of Drones, the old-school spy-stories are evolving around this topic, as well. Apparently, the plans for a French-British drone collaboration have been stolen at Gare du Nord station in Paris:

The unnamed man briefly left his case unattended after his female colleague was “hassled” by a stranger, said a Paris Judicial Police source. Documents in the case were marked “Defence – Confidential” and contained details of a “joint Franco-British drone”, a legal source close to the case told Le Parisien newspaper.

Foreign Policy magazine, in there recent “War” issue, have an amusing list of drone-related info fast food.

Could you guess, for instance, the name and scope of Iran’s main drone in development?

Iran has also touted its program, including the armed “Ambassador of Death” drone, which President Mahmoud Ahmadinejad unveiled by declaring: “Its main message is peace and friendship.”

Another interesting fact is the sheer scope of human involvement that is necessary to operate those vehicles.

Some 168 people are required to keep a Predator drone aloft — and 180 for its larger cousin, the Reaper — compared with roughly 100 people for an F-16 fighter jet.

Carlos Bueno wrote a children’s book about digital literacy. From the description it reads like the kids book version of Douglas Rushkoff’s “Program or be Programmed.”

What happens next is beyond mere irony — Amazon’s prizing bots take over:

The plot of my book is about how un­derstand­ing com­put­ers is the first step to tak­ing con­trol of your life in the 21st cen­tu­ry. Now I don’t know what to be­lieve.

It’s pos­sible that the opt­im­al price of Laur­en Ipsum is, in fact, ten dol­lars and seventy-six cents and I should just relax and trust the tat­tooed hipst­er who wrote Amazon’s pric­ing al­gorithm. After all, I have no choice.

A very amusing account of happenstance that sounds all but too much like straight out of a Kevin Slavin talk.

If you’ve ever wondered how much can be disclosed about individual circumstance¹ by analyzing aggregate user data, then this seminal piece by Charles Duhigg for the New York Times is a must read.

As Pole’s computers crawled through the data, he was able to identify about 25 products that, when analyzed together, allowed him to assign each shopper a “pregnancy prediction” score. More important, he could also estimate her due date to within a small window, so Target could send coupons timed to very specific stages of her pregnancy.

The gist: Target can offer baby related products to customers, sometimes even before the immediate family knows of the pregnancy.

“My daughter got this in the mail!” he said. “She’s still in high school, and you’re sending her coupons for baby clothes and cribs? Are you trying to encourage her to get pregnant?”

The manager didn’t have any idea what the man was talking about. He looked at the mailer. Sure enough, it was addressed to the man’s daughter and contained advertisements for maternity clothing, nursery furniture and pictures of smiling infants. The manager apologized and then called a few days later to apologize again.

On the phone, though, the father was somewhat abashed. “I had a talk with my daughter,” he said. “It turns out there’s been some activities in my house I haven’t been completely aware of. She’s due in August. I owe you an apology.”

We should keep in mind that, with all the discussions about Do-Not-Track and Address Books, data gathering and analysis is wide-spread, is being used and is not happening strictly online. Further, with more and more signals being picked up and available for analysis, the potential for finding valuable patterns increases tremendously.

But it is really the part about pattern formation that’s the most interesting. Nobody says, it should only be companies that collect this information about us. Analysing that data for our own benefit² should enable us to develop habits that we find beneficial.