Our Pythagorean World

Crystals like the flourite, calcite, or garnet here show properties, that can easily be expressed in mathematical terms. Social behavior seams to be random, however, data science can help us detect laws and patterns, that can be expressed in mathematical functions like the shape of the crystals.
Crystals like the flourite, calcite, or garnet here show properties, that can easily be expressed in mathematical terms. This inspired the legendary Pythagoras an his students to postulate the whole world to be genuinly mathematical. Social behavior seams to be random, however data science can help us detect laws and patterns, that can be expressed in mathematical functions like the shape of the crystals.
Our senses are adapted to detect of our environment, what is necessary for our survival. In that way, evolution turns St. Augustin’s postulate of our world as being naturally conceivable to our minds from its head onto the feet. What we define as laws of nature are just the mostly linear correlations and the most regular patterns we could observe in our world.

When I had my first computer with graphical capabilities (an Atari Mega ST) in 1986, I, like everybody else, started hacking fractals. Rather simple functions produced remarkably complex and unpredictable visualizations. It was clear, that there might be many more patterns and laws to be discovered in nature, as soon as we could enhance our minds and senses with the computer – structures and patterns way to subtle to be recognised with our unarmed eye. In that way, the computer became, what the microscope or the telescope hat been to the researchers at the dawn of modernity: an enhancement of our mind and senses.

“Number is an extension and separation of our most intimate and interrelating activity, our sense of touch” (McLuhan)

The origin of the word digital stems from digitus, Latin for the finger. Counting is to separate, to cluster and summarize – as Beda the Venerable did with his fingers when he coined the term digit. With the Net, human behavior became trackable in unprecedented totality. Our lives are becoming digitized, everything we do becomes quantified that is, put in quants.

With the first graphically capable computers, we could suddenly experience the irritating complexity of the fractals. Now we can put almost anything into our calculations – and we find patterns and laws everywhere.

What is quantified, can be fed into algorithms. Algorithms extend our mind into the realm of data. We are already used to algorithms recommending us merchandise, handling many services at home or in business, like supporting our driving a car by navigating us around traffic jams. With data based design and innovation processes, algorithms take part in shaping our things. Algorithms also start making ethical judgments – drones that decide autonomously on the taking or sparing the life of people, or – less dramatic but very effectiv though – financial services granting us a better or worse credit score. We have already mentioned “Posthuman Advertising” earlier.

The world is not only recognisable, the world in every detail is quantifiable. Our datarized word is the final victory of the Pythagoreans – all and everything to be expressed in mathematics. Data science in this way leads us to a similar revolution of mind, than that of the time of Copernicus, Galileo and Kepler.

Data Humanities

Mathematics is usually not regared as a science but as part of philosophy - although it has some relation to the "real world" - as shown in this 18 century cut.
Mathematics is usually not regared as a science but as part of philosophy – although it has some relation to the “real world” – as shown in this 18 century cut.
There is a reason why we differentiate science and the humanities. And although sociology, experimental psychology and even history nowadays deploy many scientific methods, the difference is still fundamental. Humantites deal with correlations; the causalities are way further speculative than the “laws of nature” that are formulated in physics or chemistry. Also the data that supports social research is always and inherrently biased, no matter how much care we take in sampling, representativeness and other precautions we might take.

In her remarkable talk at Strataconf, Kate Crawford warned us, that we should always suspect our “Big Data” sources as highly biased, since the standard tools of dealing with samples (as mentioned above) are usualy neglected when the data is collected.

Nevertheless, also the most biased data gives us valuable information – we just have to be careful with generalizing. Of course this is only relevant for data relating to humans using some kind of technology or service (like websites collecting cookie-data or people using some app on their phone). However, I am anyway much more interested in the humanities’ side of data: Data describing human behavior, data as an aditional dimension of people’s lives.

Taken all this, I suggest to call this field of behavior data “Data Humanities” rather than “Data Science”.