Introduction
Often the technical aspect of data science is in the spotlight. It always gets the glory in the new developments and in peoples’ heads of what constitutes data science. However, a very important side that has been overlooked for a number of years now is being needed more and more – the humanistic side. This is what Cecilia Aragon, a professor in the College of Engineering at the University of Washington, argues in her article in Newsweek(linked here).
Summary Of Article
First Aragon shows how prevalent data science is in our world today. It is in almost every, if not every, industry and line of work. She then says that now people are understanding the need for the ethical concern of data scientists and big corporations have started to hire ethicists and social sciences to help with this need. However, the author points out that this isn’t very sustainable because these ethicists don’t know about the technical aspect and the developers don’t have a deep foothold into the ethical aspect. These people, the article says, are T-shaped in that they have a wide breadth of knowledge but only depth in one aspect – either technical or ethical. That is not what is needed. Corporations now need people who are Π shaped because they have breadth and depth in both the technical aspect and the ethical aspect so they can blend those two together seamlessly in their work. They are so useful, in fact, that one of these Π shaped people, who was the author’s coauthor on a book, was able to identify a problem in a definition within a database and fix it leading to much more accurate insights and a great help to the stakeholder. This also shows, the author argues, that the humanistic side of data science isn’t “soft” or “imprecise”. This can also help in designing technical tools by bringing stakeholders into the process. The last point that the author shows is that human-centered data science often integrates both quantitative and qualitative data which in some instances can be combined with other domains to yield interesting results.
My Take
This article was very interesting to me as it shows how not only the technical side of data science is important but also the humanistic side. I have been trying to incorporate the humanistic side in my work but now I know that there is a whole field of study dedicated towards it. The article was formatted nicely and in an easy-to-read manner which was helpful. I would have appreciated more images to help add to the points and make the article flow better but it was overall a good one.
Conclusion
All in all, the article was a good one. It listed some very interesting points and tied a number of things together for me. It was relatively easy to read but some added images would have been nice. Overall, it was a great article and you should go read it(link here)!