When I studied Mass Communication at the university of Nijmegen in the early nineties my special interest was the up and coming computer networks (the web was still to be invented). I considered those networks to be the most promising media ever devised and was very intrigued by the possibilities it opened up. At least, in my opinion, many of my fellow students or professors were not that much interested in technology. Their focus was on the societal aspects of media. I was stubborn enough to push through so my thesis was about the question whether the broadband television network would be suitable for what were called 'electronic services'. This was a valid question since these networks were broadcast networks meaning there was route for a return signal. Making it usable for electronic services meant the network company had to invest a lot to make it two-way. For my research question I had to interview a lot of different kinds of respondents: users, network operators, content creators, marketeers, networking engineers, software developers, etc. What struck me most when I finished the interviews was the difference in depth of knowledge between the technologists and the non-technologists. The formers had a deep understanding of both the technological basis and were able to translate that into a set of possibilities and impossibilities. The latter were basically starry-eyed dreamers with very little understanding of the ongoing trend and, thus, the possible future. That was when I realised that when I wanted to make a living out of exploring this new digital frontier I'd better re-educate myself. After receiving my master's in Mass Communication and shifted to studying AI. So I shifted from an alpha to a beta study and basically never looked back. Looking back now, I can safely say that it has been one of the best choices in my life. Having the digital revolution from both sides I can say with confidence that a good grasp of underlying technologies gives me an incredibly better insight into technology related trends. And let's be honest, most innovations are (and have been) technology driven.
There are two recent trends where this became obvious. First of all the rise of bitcoin and blockchains. As I've written extensively before I spent a lot of time a couple of years ago into a technical deep dive into bitcoin and blockchains. Being intrigued by the idea of an immutable legder I became curious both about the underlying technology and the possibilities of a blockchain. So I took the dive and it was a lot deeper than I expected. A blockchain is a genuinely complex technology. But having a deep understanding made me in the end realise that almost all use cases proposed were either impossible or easier and cheaper using existing technologies. Many of the technologists from the early days have come to this conclusion by now. Still there is a very large group that don't know the technical ins and outs of blockchains and thus reside to some sort of belief in the ones that sing the gospel. The latter often lack the technical expertise as well. Without this technological understanding it is very hard to really grasp bitcoin, blockchain and their (im)possibilities.
The second trend you see this happening is with AI. There is currently a lot going on in the area of AI, but while it certainly has many, many applications, there is also a lot of non-sense and ignorance. While many AI enthusiasts have drunk the kool-aid spread by the marketing departments of the tech giants, who coincidently have a stake in keeping the hype going, they often are unaware of the limitations and dangers of AI. Because to recognise those you need a proper understanding of the underlying technology. How is it possible that a neural network can have a bias? Is an advanced general AI really possible? On what time scale? Is an AI's domain expertise transferable to another domein? Why not? It is these kinds of questions that will give you a clear understanding of where a trend is coming from and where it is going.
As David Deutsch says, progress is the never ending search for better explanations. And in our day and age this means we often have to explain technological aspects of an explanation. So if you want to contribute to finding better explanations through creativity, conjecturing and critical thinking, you will have to take the technological deep dive so you KNOW YOUR STUFF.