A Call for the End of Technological Buzz Words

These last years were marked by buzzwords that had to be seized. What if 2019 was the last year we would see a technical buzzword emerge and dominate briefly, only to give way to other types of buzzwords?

How We Got Here

In recent years we have seen the Big Data years, the IOT years, and the AI years. With this kind of buzz, it's the same every time. Analysts get excited, consulting firms come out with a speech on the subject, business owners want to be part of it, and solutions publishers claim to have the miracle solution. It is no coincidence that Gartner's Hype Cycle is called a "cycle." At first there's euphoria and everyone claims to be a self-proclaimed specialist on the subject. Then comes the disillusionment because no one was really an expert on the subject at all, and then everyone moves to the next wave, leaving the previous one to be forgotton and not necessarily well-implemented.

Why All These Buzzwords?

Of course, the need stems from technology companies' desire to generate growth! In fact, the latest buzzwords are all from technology that are actually more than ten years old. IoT has already existed for a long time in factories, and the AI has known one of its variations in the OCR. Of course, cost reductions and CPU power increases have allowed all this, but it is clear that these no longer have the capacity to fuel growth and innovation as quickly as they once did. CPU power growth is now flat, and we find ourselves with an innovation engine that suffocates.

So What Else Is There?

I could be told that the AI will gradually improve and will change a lot of things, that it is a financial gold mine. This may be true, but are we sure that the technological revolution will be as broad as promised? And as for quantum computing, for example, I'm willing to wait until we get beyond the stage of laboratory work, but for the moment there's no promise that we'll get a really functional quantum computer. The growth accelerator is another example of technology that has been hyped up without any real promise of positive social implications.

The social sciences are considered non-productive sciences, and therefore useless. However, understanding human beings before technology means improving the productivity of their employees, their creativity, and customer satisfaction. This could obviously be seen as a utilitarian vision of things, but perhaps we should turn to ourselves before we run towards technological innovation. Perhaps it is time to deal with what really matters: ensuring that human beings will not be misled by an overexcitement of technological innovation. And this is where all texts and studies on agility take on their meaning, because being liberating from a creative force, it generates value for all. After all, we will live just fine without a quantum smartphone, I promise you!