It’s an uncertain world when even the constants aren’t constant…
After more than a century, the international prototype kilogram – a cylindrical chunk of metal stored in a French vault – doesn’t weigh the same as its 40 replicas, distributed worldwide and used to standardize mass measurements. Suspecting that gunk accumulating on the metallic surfaces is to blame, scientists at Newcastle University have developed a high-tech way to clean the standards.
… in the late 1980s, scientists noticed that the original kilogram was about 50 micrograms lighter than its brethren. Because mass measurements are relative, it’s tough to determine whether the replicas are getting heavier or the original is getting lighter.
Read the full story at Wired
The e-book concept, turned inside out. A timelapse of an amazing senior project at the Academy of Fine Arts in Katowice.
Elektrobiblioteka / Electrolibrary from waldek wegrzyn on Vimeo.
A team of British researchers has produced an algorithm that can analyze a cell phone’s location data and predict where you’ll be in 24 hours. To an accuracy of 20 meters. That may not tell them which chair you’ll sit in, but it’s enough for them to know that you’ll be at your favorite locally-sourced burger joint before you even know you’re going there. From the article on Slate:
That’s far more accurate than past studies that have tried to predict people’s movements. Studies have shown that most people follow fairly consistent patterns over time, but traditional prediction algorithms have no way of accounting for breaks in the routine.
The researchers solved that problem by combining tracking data from individual participants’ phones with tracking data from their friends—i.e., other people in their mobile phonebooks. By looking at how an individual’s movements correlate with those of people they know, the team’s algorithm is able to guess when she might be headed, say, downtown for a show on a Sunday afternoon rather than staying uptown for lunch as usual.
There are of course the usual privacy concerns, and the easily-imagined potential interest that law enforcement would have in employing such an algorithm as a tool. Yet there are significant practical limits involved; having to pull data not just from your phone but from those of your friends in order to provide accurate results. And as the article points out, justifying tracking specific individuals and their friends to find out where someone will be has significant ethical and legal challenges. To go down that road gives us a real-life Minority Report, and turns our justice system on its head.
What is more interesting, to both myself and the researchers, is that this is even possible. Despite the fact that humans, in mathematical terms, are walking irrational numbers, we are apparently more predictable than we realize.
But this is not that surprising if I stop and think about my own activities. It doesn’t take a genius to figure out my routine- work, home, and the smattering of places that Lynn and I like to go for dinner or other entertainment. You could assemble a very accurate pool of guesses from Facebook updates and her Foursquare posts. We pretty much put it all out there anyway.
Online privacy continues to be a hot topic, legally and technologically. And that’s one way that humans continue to be quite unpredictable. We are fine with sharing information online… except when we’re not. Google guessed at where the line is drawn with their first social networking experiment (Google Buzz) and got it quite wrong. Walt Whitman had no idea how right he would be- “Do I contradict myself? Very well, then I contradict myself, I am large, I contain multitudes.”
In the meantime, I’m wishing my phone would tell me if I’m going somewhere unexpected 24 hours in advance, so I could dress for it…