I work with data but I look for truth. Let me explain:
Below is an example of a datum:
42Another example is: 1947
Together we have data (a plural). Data by themselves are not very interesting.
Jackie Robinson wore number 42. By utilising the data and applying a fact we get something more closely resembling information. Sometimes Data Scientists argue about the exact point that data becomes information, some would argue that we are not at the information stage yet.
Jackie Robinson wore number 42 and made his major league debut in 1947, he was the first black to play in the major leagues. At this point the line from data to information has very much been crossed.
Now, maybe we look at that piece of information and say, hang on a minute, emancipation happened in 1863 and organised baseball started not long after; what happened to black players before that? Perhaps we posit that America was a racist country during that period. In applying context like this information turns into knowledge.
Perhaps we think of all of the other Jackie Robinsons that could have been improving the overall quality of baseball and think what a waste! Maybe we hope it will never happen again. In doing these things intelligence is applied to knowledge, judgment to intelligence. The output might be called wisdom.
How might society use this wisdom? Well, the number 42 has been retired by all Major League Baseball clubs except on April the 15th, Jackie Robinson Day. On Jackie Robinson Day every single player wears 42, lest we forget. That’s wise.
And why might Data Scientists care about this? Well, this really is the subject in microcosm, we take some data, form a hypothesis, test it, re-test it. The science is in the uncovering of truth. Only then do we judge, take action. Not one of us has ever done this to try and make the world less intelligent, less wise, more judgemental. Just smarter, faster, better.