When I was a little child, a book that had a big impact on me and my view on the world was “Where the Wild Things Are”. Many years later, it helped me to explain my passion and profession to my grandparents. This blog post tries to give an approach to explain software development to non-technical people.
The first encounters
My first contact with computers was when I was five or six years old in the laboratory of my father. He was a young physicist and worked virtually around the clock in his university’s laboratory. The lab itself was a magical place full of machines and dangerous things like liquid nitrogen canisters. In order to keep me from touching things, he let me play with the only machine that could do no harm: the personal computer on his desk. My interaction with it basically boiled down to moving the cursor on the screen and placing characters into pictures.
When I was eight years old, we got our own family personal computer at home. This was the start of my lifelong passion to teach the machine new tricks. Of course I played every game I could get hold on, but at same time, I wanted to create my own games. By copy-typing code listings from magazines I checked out from the local library, I taught myself to transform my ideas into source code. By trial and error, I expanded my vocabulatory until I could talk to the computer in a nearly fluent fashion.
The apprenticeship
I was sure about my career wish since these days. When my extended family (like aunts and grandparents) asked what I would do once school was finished, I could tell them that I “study something with computers”. It was sufficient as an outlook.
During my studies, it was more important to them that I was studying seriously than what exactly it was that I was studying. They asked about my grades, but not about the content.
The translation gap
Then I started my company and began to earn money with my skills. That’s when the questions about what exactly I was doing emerged. And I learned that the concept of “programming a computer” is not universally understood.
My grandparents weren’t technical people. One grandfather was a railroad worker and had mechanical skills, but couldn’t grok electronics, let alone digital systems. We tried to find a level of simplification of my work that he could imagine and landed at “rapidly pressing buttons in the right order”. In his mind, I was a silent variation of a pianist.
While this is flattering, it lacks the aspect of persistence. A piano falls silent once the button-pressing is done. My computers commence their play long after my typing. A piano player is expected to repeat his “typing”, while my code only needs to be written once and can be copied automatically. The piano player teaches one specific piano how to produce music, my code can teach lots of computers at once how to produce numbers or “data”.
The wild boxes
Data is another concept that is hard to imagine with a mechanical worldview. So I tried another communication approach: the “animal tamer”. Instead of the end result, I focused on the computation process itself. I explained that every computer has its own set of behaviour and can react on incoming information (we used the metaphor of e-mails or “electronic letters”) on its own. The problem is that computers are very dumb and need extensive training to act professional. The training comes in the form of instructional electronic letters (the program code) that the computers read and adapt to.
My job is to write the instruction letters and make the computers read them. This tames the wild box and turns them into domesticated machines that work for us, just like horses or dogs.
To my surprise, this explanation lit up my grandfather’s face: “You tame machines and teach them how to read!” He could understand this process and my role in it. And because machine taming sounds dangerous and important, I earned my wages.
Domesticated boxes
In the book from my childhood, the protagonist Max befriends a group of monsters and gets them to act according to his plan. In my life, I befriend computers and make them act according to my plan. I like the metaphor of “taming” or “domesticating” computers because it highlights the benefits of my work instead of its mechanics.
We build our modern world on billions of domesticated, well-behaved computers. They work for us in exactly the way we told them. But they won’t improve by themselves because we never told them how to learn.
Self-domesticating boxes
Right now, we change our approach of teaching them. Instead of telling them what to do, we try to let them figure it out themselves by trial and error. The beneficial potential is that the machine is not burdened with our limited understanding of the world of digital data. It may be able to expand its vocabulatory until it can interact with its world in a fluent fashion.
Maybe in the future, we need to bargain with our machines so that they work for us. Maybe the next generation of “computer kids” will explain their work to me as “machine mediators”. I’m curious!
Schneide Blog 