Big Data and Big Backsides

by Stuart Ridgway, Original Music for Film and Television

Quoted with permission are my favorite parts of this May/June 2013 article by Kenneth Neil Cukier and Viktor Mayer-Schoenberger in Foreign Affairs magazine.

Big Data continues to give us more and more opportunities to link trends to correlations.  We may not know why a trend is occurring, but we can often anticipate how an event might unfold by correlating it to other, predictive events.  Other times we just learn by putting sensors beneath someone’s butt.

The possession of knowledge, which once meant an understanding of the past, is coming to mean an ability to predict the future…

…Appreciating people’s posteriors is the art and science of Shigeomi Koshimizu, a professor at the Advanced Institute of Industrial Technology in Tokyo. Few would think that the way a person sits constitutes information, but it can. When a person is seated, the contours of the body, its posture, and its weight distribution can all be quantified and tabulated. Koshimizu and his team of engineers convert backsides into data by measuring the pressure they exert at 360 different points with sensors placed in a car seat and by indexing each point on a scale of zero to 256. The result is a digital code that is unique to each individual. In a trial, the system was able to distinguish among a handful of people with 98 percent accuracy.

The research is not asinine. Koshimizu’s plan is to adapt the technology as an antitheft system for cars. A vehicle equipped with it could recognize when someone other than an approved driver sat down behind the wheel and could demand a password to allow the car to function. Transforming sitting positions into data creates a viable service and a potentially lucrative business. And its usefulness may go far beyond deterring auto theft. For instance, the aggregated data might reveal clues about a relationship between drivers’ posture and road safety, such as telltale shifts in position prior to accidents. The system might also be able to sense when a driver slumps slightly from fatigue and send an alert or automatically apply the brakes.

Read more of the original article by Kenneth Neil Cukier and Viktor Mayer-Schoenberger.

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