Updated: Jun 16
This article is Talk 06 of Honest Data Science Talks series. Each talk of around 500 words length, is personal thoughts and deliberations on the domain.
The claim has been that – Data Science needs social aspects. The Corona lock-down has certainly favoured to it, if not proved it. Raise your hands if you are irritated with all this work from home!? Okay, I see some hands. I see some are thinking and a few more going up slowly. I also anticipate that some more will go up in a week more or two.
Being in academics, I usually don’t engage a class using slides and presentations. I prefer chalk and talk and I believe that is the only means to connect. With more than one job at hand, I multitask by allocating times on a per week basis. You be there, you do it, you move on! Call me old school, but I cannot do it without my handwritten planner, a book and a pen. We are all sloppy creatures and we have an evaporating thought process. Sometimes (maybe I can cut this word – sometimes), the thoughts take the form only when they are written, talked and discussed.
Every human has a zone of expertise. Most have, if not all. That expertise can be best put in use, in a physical gathering (exceptions ignored) understanding and comprehending the real world problems. Not in an online call of 10 irritated people where most of them are looking for the call to end. It just does not do the job right.
There is a book written for everything for every kind of study. There is a tutorial available for everything. This has been true since the days of the Gurukul. Then why do we have the concept of schools and colleges? Apart from throwing deadlines and exams to make sure that learning has happened, they are also meant to impart experiences. A teacher has to take the lead to impart the know-hows. The examples I am taking are off course from the domain of my workplace but I am sure the principles are the same. The connection is the same.
People need to be together. They have to share a common meeting place and time to work on the ideas – to bring out the solutions and to learn with experiences. That is the only way how we can be differentiated from machines. If data science models are not capturing this aspect, they are doing the meaningless irritated job-ends.
Materialism probably only calls for a mechanistic conception of mental life.
Science is all about being social. It must be about. The process, context, environment, effects, everything plays a role in decision making. Space has a major influence on the ideas and solutions and it’s those experiences that provide meaningful solutions. If one does not step outside to know how the world works, one cannot build a science for it. Experiences are in real and not in closed walls and magnetic tapes or drives.
This is what I can conclude (conditions apply for specifics) – if you can be at home and complete the works with no hassle, no issues at all, probably, that job is going to be automated soon.Tomorrow, if not today. That probably is the job of a machine.