If you thought technology was accelerating fast now, wait till you see the nitrous boost that AI is going to give to the world. All we have to do is survive the G-forces.
It’s never been harder to predict anything than today. Not only is the exponential trajectory of technology making us feel like we’re living in a science fiction novel, but we’re still wide-eyed and somewhat stupefied from the Trump/Brexit/ <insert authoritarian populist election winner here> revolution that’s seemingly ongoing.
All of this will seem like small fry compared to what’s coming up in the next few years as Artificial Intelligence (AI) becomes a dominant factor in our lives.
And it’s no longer a question of whether this will or will not happen. It is happening, and we’re in the foothills of the biggest revolution to hit work and leisure since time began.
In a way, it’s a privilege to be alive while this is happening. We’re going to see more progress in the next twenty years than in the whole of history, as long as we don’t end up killing each other or destroying the planet, either of which unpleasant outcomes would not entirely surprise me.
But I remain optimistic that we will at least exist in twenty years time, and that the world might be a better place because of technology - and, perhaps, because of us, too.
The world is much less stable than it used to be. Many of the old status quos have gone and where Western politics used to be based around a simple Right/Left axis, there are more dimensions now than there used to be, and the opinion pollsters - largely oblivious to this - are licking their wounds.
We are used to working within known boundaries. All of this changed in 2008 when automatic trading programs that were effective within strictly defined limits found that those familiar extremities were being exceeded by orders of magnitude. That’s happening all over the place now, both politically and in the field of technology.
I was in New York City on the night that the all the meters hit the end stop and carried on going. Pollsters were looking in the wrong direction and weren’t even measuring the factors that caused the election result. “Working Class” doesn’t mean what it used to mean.
We need to get used to this. Technology was in the background in the big financial crisis. It’s what fuelled some of the issues in the recent election (and “Brexit”). In the next few years technology will move to the forefront and we will never have seen anything like it.
What’s behind this is artificial intelligence. Look at any of the big social media, search and software companies and what you will find is that they are betting their future on AI. The hardware industry, too, heading that way too: Intel has mentioned the possibility that it will put neural networks on its CPUs.
A further accelerant
Let's be clear about this. Technology is accelerating anyway, without the help of AI. The simple fact that today’s generation of tools builds the next generation means that Technology is getting better, and if we need more computing power to design the next generation of… computing power, then that’s what’s going to happen.
Meanwhile, quite aside from Moore’s Law, algorithms are getting better. Increased bandwidth means that cloud and distributed processing are becoming useful. All of this already means that technology is changing faster than ever, and what happens when you add AI to the mix is anyone’s guess.
We’re at a curious and important stage in the development of AI. We’re certainly not on the verge of creating a general intelligence that is as powerful as a human brain. But as recently as last week we have seen evidence that some of the basic technology that you need for general human-level AI has been achieved. Machines are starting to work things out for themselves. They’re beginning to acquire complex skills without being taught.
The key to this process is a so-called Neural Net. This is an electronic version of a key functional aspect of the brain. When a neural net is exposed to stimuli, it sets weightings in its internal pathways that correspond to the frequency with which it has been exposed to certain patterns. It can then “recognise” similar patters. Most importantly, it can “learn” new ones - without being explicitly taught. This ability is now being emulated in digital electronics, and it is absolutely fundamental to “proper” artificial intelligence.