In the first four part of this series we have yet to cover robotics. There is one aspect of this basket of new multiple and variable technologies emerging where robotics stands out – as you will, almost certainly, within a few years, have a robot running around your house. The rest of the tech developments are slightly more nuanced, you will get to work with them, be changed by them, and all will be different, but robots are going to become companions, like the dogs and cats of the future. You will start to build relationships with robots.
Today, there are robot services available in some parts of the world, where you can leave them in charge of your house when you go on holiday. They can even feed the dog (or the cat) whilst you are away!
They will be assistants, homeworkers, concierges, and more. These companions will be able to answer questions, converse, make suggestions, and help with the shopping, washing, cleaning, and gardening.
You may have encountered some early versions if you have been to one of the growing number of restaurants where they greet you when you walk in.
Robotic personal assistants or companions are the physical embodiment of entities such as Siri and Alexa.
These devices, robotic or otherwise, are going to be super intelligent. And will be able to spot things and work things out which we can’t or even if we can – they will do it better and quicker.
A growing number of people have already woken up to the fact that AI assistants may be able to help them invest money for profit, and stories are appearing, almost by the day, of random people working from their bedrooms gaming the markets based on extensive (and quite new, in some cases) research models into short-term share price movements. So, one might ask a device/entity to track back through decades of data, align this with news stories, see where patterns or correlations appear, and then ask for predictions based around the news of a market or a particular share. The entity could for example spot or uncover a deep (difficult to find) pattern that when X story of a particular type appears (for example with certain key words in it), it is 85% likely this will spike a share price of Y company. It can then be asked to watch for such stories and to present recommended purchases for short-term trading profits.
Anyone can work with pretty much any model to do such research, explore such avenues and to gather news and information in such short spaces of time it is simply staggering. It’s not just the AI’s ability to gather and discern the information but to intelligently analyse it. It can do all the heavy lifting, research, analysis, trend spotting, find hitherto unknown correlations and more.
We know a few years ago that the high frequency traders who were intercepting buy orders from the markets by gaining fractional speed advantages (by quite literally moving their machines closer to the trading centres!) were able to take billions out of private investors funds for their own benefit. This is different with AI, because it will not require such extravagant and complex mechanisms for forward looking and entrepreneurial types, who could be age 15 and sitting in their pyjamas, to get in front of this.
So, this causes – potentially – the equivalent of a race, who is going to get furthest, fastest?
The point is this, markets are always net zero. For every buyer there has to be a seller, so person A cannot make a profit without person B making a loss. Its only economic growth, allied to profits, that raises the entire market up over time. Stock markets when they are efficient are simply a function of the profitability of the companies in the market. If person A has an information advantage over person B, they will probably do better, as they can use their information advantage to buy lower and sell higher.
Most modern day investing by private investors is conducted through large funds, with a growing bias in the past 20 years towards passive funds, i.e. those that track the market, so investors accept their fate and simply look to the macro picture for their growth and income. They rely on the adage that markets go up over time, so take the dips along the way, and stay invested, all will work out.
There is no real reason to expect this to change in an instant, apart from the fact that we have no idea what will occur when super intelligent entities get involved. Their information advantage will be huge, and those humans that leverage on this will prosper, it cannot be any other way.
The more money the 15 year olds start to make from their bedrooms, the less there is for the traditional private investors who are following the traditional methods, at least this is the theory.
As with our last article (#4 in the series), the real message here is to be aware. Not necessarily today to do anything different, but to be highly conscious something is possibly changing, and we could see some interesting market times ahead.
In the conventional way of approaching all of this we have to be attentive to the long-term cyclical nature of markets, twenty years ago passive investing was hardly a thing, today it is the bedrock of everything. It may just be that AI is going to take us into a new cycle, and we shouldn’t be caught out if this turns out to be the case.
More to follow in part six, where we look at some specific AI models that are being developed to support investors with their investment planning.