In 1840, at the age of thirty-nine, the German physicist and psychologist Gustav
Fechner is struck with a strange disease – the onset of extreme depression and
blindness, partly as a result of directly staring into the sun while conducting
experiments in post sensorial vision perception. Alone, isolated in a dark room and wearing a mask over his eyes for three long years, Fechner suddenly emerges. He throws off the yoke of physics and transitions into philosophy – attempting to unite the material and spiritual aspects of the body in a strange new discipline called psychophysics.

Fechner invented a whole battery of concepts to help cement this new human but one stands out: The JND, the Just Noticeable Difference, expressing the logarithmic relationship between the physical and the psychic coupling of stimuli, sensation and perception. Fechner thus became the inventor of a discipline that aimed not only at “counting sensation” but “fractionating qualitative continua” through this measuring of limits, thresholds and sensory quanta. How ironic that such a noble philosophical cause, attempting to unify the classic split between mind and body, the material and the spiritual, would become the basis for the development of psychological techniques that treat the senses as machinic producers of numbers.

Ironically, Fechner’s legacy lives on. In the NY Times magazine in May 2010, an
article by ex-Wired writer Gary Wolf appears entitled “the data driven life.” In it, Wolf reveals increasingly that people are using sensors and numbers to “interrogate their inner worlds.” But stand-alone sensors are not enough. As Wolf says, the phone envelops us in infrastructure – “in a cloud of computing.” – what he calls “a poetic term.” Unlike the complex sensory organs of animals or humans that are tied to large physical-cognitive structures, these sensors have only the ability to transduce signals – not to interpret them. They have to be connected to larger infrastructures which receive the signals: routers, servers, databases, and most importantly, algorithms which after all “turn messy data from these cheap sensors” into meaningful information.