When I first started out, the majority of those who worked in the IT industry were clever people. By clever, I mean people of a scientific background, who were not afraid of mathematics. It was the generation where the image of the geek was born. As the industry has grown and has penetrated all areas of society, so the number of workers has increased and the proportion of scientists has diminished. And that is a good thing
You can argue until you are blue in the face about what cleverness means. But for me it has to mean that you can deal with maths, the fundamental underpinning of all understanding about everything. And if you are good at maths, it is more than likely that you will have a keen appreciation of the arts. This is something that is intensely annoying to many people who work in the arts. It seems grossly unfair that someone can have a hobby which makes their appreciation of Mahler greater than someone who has made a career from studying it and trying to play it. But surely this has to be the correct definition of cleverness – someone who is able to understand all types of stuff.
The dismissal of people who enjoy science and maths as boring and socially inept is pretty widespread. A great book from a few years ago “Innumeracy,” was an angry response to the near-delight people had in their mathematical ignorance. (The author mused on the reaction there would be if one declared at a dinner party a profound ignorance of reading and no desire to learn anything about it.) My Facebook feed is filled with posts about funding the NHS or immigration from people who appear to have not the remotest ability to apply the most basic logic or mathematics to a problem.
I am OK at maths (or I used to be) and I am reasonably clever. I apply fact based logic to problems and come up with sets of clear actionable steps to get to the correct answer. Unfortunately, they frequently don’t work and the conclusion is often the wrong one.
And this is why the dilution of scientists in IT is a good thing. Because the correct solution to a problem is often not the answer to a problem. I worked at an insurer some years ago that reduced inefficiencies in their claims handling department. The result was much shorter claims processing times and much happier customers. But the company nearly went out of business. Unfortunately, payouts on claims more than doubled and massive losses ensued. The problem they were trying to solve was more complex than inefficient claim handling. Although the previous process frustrated customers, it also minimised payouts through slow, repeated checks of claims.
With the insurer above, the problem was not understood. Customers complained, people handling claims complained, managers complained; the answer to stop those complaints was clear and it worked. It just wasn’t the correct solution. The consultants who defined and implemented the efficiencies were some of the most clear sighted and confident that I had encountered. They were certain that their proposals would work and the results would speak for themselves. Which they did, causing a 30% drop in the share price
And ultimately, this is why too much cleverness can be a bad thing. It leads to confidence and hubris and above all else it leads to certainty. And when someone is certain that they are right, it is almost always the case that they are not. In the end, we have to find ways to let the correct solution emerge gradually by letting the problem emerge in the same way. Because you can never get the right solution, if you are correctly answering the wrong question.