Time for me to rant a little.
Agile software development. Artificial intelligence. SCRUM. Machine learning. Not a day goes by in our profession without the cognoscenti dropping these and similar buzzwords, hoping to dazzle their audience.
Give me a break, please. You think you are dazzling me but all I see is someone who just rediscovered the wheel.
Let me present two books from my bookshelf. Both were published in Hungary, long before the Iron Curtain came down, back when the country was still part of the technologically backward, relatively underdeveloped “second world” of the socialist bloc.
First, Systems Analysis and Operations Research, by Géza Jándy, published in 1980.
In this book, among other things, Jándy writes (emphasis mine): “Both in systems analysis and in design the […] steps are of an iterative nature […]. Several steps can be done contemporaneously, and if we recognize opportunities for improvement in implementing the plan, some steps may be retraced.”
Sounds familiar, Agile folks?
And then, here’s a 1973 (!!!) Hungarian translation of East German author Manfred Peschel’s book, Cybernetic Systems.
A small, unassuming paperback. But right there, the subtitles tell the story: “Automata, optimization, learning and thinking.”
Yes, it’s all there. Machine learning, neural networks, the whole nine yards. What wasn’t available in 1973 of course was Big Data, the vast repositories of human knowledge that is now present on the Internet, and which machine learning algorithms can rely on for training. And of course hardware is a lot faster, a lot more capable than half a century ago. Nor am I suggesting that we haven’t learned anything in the intervening decades, or that we cannot do things better today than back in the 1970s or 1980s.
But please, try not to sell these ideas as new. Iterative project management has been around long before computers. The conceptual foundations of machine learning date back to the 1950s. Just because it’s not on the Interwebs doesn’t mean the knowledge doesn’t exist. Go visit a library before you reinvent the wheel.