Prediction of the future has always been man’s dream. However, there is an overwhelming amount of physical evidence that this is quite impossible. This is because the future is permanently under construction. Therefore, as every second passes, the future is changed. The cause of this are the laws of physics. If the future were predictable with all likelihood we would have different physical laws and life would probably not even exist.
But man is a subborn species. The unhealthy desire to predict the future has pushed mathematicians to devise utterly unnatural methods which, in virtue of prolonged and often distorted use, are now deeply rooted in the practises in virtually all spheres of social life. Scientists speak of predictive models, just as the economists, the weather man, etc. Some people believe in horoscopes while others buy lucky lottery numbers.
Much of the contemporary “predictive machinery” is based on statistics – looking back in time, building some model of what has actually happened, extrapolating into the future. The concept of probability plays a central role here. Bertrand Russel is known to have said, back in 1929, that “probability is the most important concept in modern science, especially as nobody has the slightest notion what it means”. In fact, probability is not a physical entity and it is not subjected to any laws in the strict scientific meaning. As a matter of fact, there are no laws of probability. If a future event will take place, it will do so irrespective of the probability that we may have attached to it. If an extremely unlikely event will happen, it’s probability of occurrence is already 100%.
Predictions are of major interest in the realm of uncertainty. Clearly, one can predict with a high degree of accuracy when an object will hit the ground when it is dropped from a certain height (providing it is not a feather). What we are more concerned with is the desire to predict phenomena and events of interest to economists, investors, managers or politicians.
But there is another problem with predictions. Suppose you do indeed know with certainty that an event of interest to you will happen at a specific time in the future. You will surely take action based on that knowledge. What this can cause, however, is a change in the chain of events such that you inevitably alter that event. As an example, suppose that you are extremely wealthy and that you know the exact value of certain stocks some months in advance. You will immediately start to buy and /or sell massive amounts of these stocks. This will surely cause other investors to react. Inevitably, the flow of events will be such that the predicted values of these stocks will not be the ones you knew with “certainty”. What does this mean? It means that you can only verify a prediction if you do nothing. The moment you act based on your knowledge of the future you automatically alter it and the prediction cannot be verified. Consequently, the phrase “predictive model” is an oxymoron. As mentioned, because of the way the laws of physics work, the future is permanently under construction. And if you add Goedel to the picture …… The Creator is indeed very smart!
So, it seems that our efforts to devise some sort of predictive analytical machinery is futile. The current planetary meltdown of the economy eloquently underscores this fact. The severity and depth of this crisis has not been predicted (had this been the case we would have taken measures, right?) and this speaks of the quality of the contemporary economic and econometric models and of their predictive capability. With all respect, their predictive capability is not too exciting.
In actual fact, we still don’t even really understand the crisis and its multiple causes. But how can one speak of predicting phenomena which are poorly understood? Shouldn’t we change the order of things? Shouldn’t we try to first understand better the dynamics of highly complex interconnected and turbulent economic systems and devote less resources to fortune telling and high-tech circle-squaring? How about:
- Taking a holistic view of things, analysing systems of entities not single entities.
- Searching for recognisable patterns, not repeatable details. The closer you look the less you see!
- Moving from sophisticated (and subjective) models to model-free approaches.
- Developing a new kind of maths, which is less “digital” and closer to reality.
- Dedicating more effort to understanding the way things work, the way Nature works.
What cannot be achieved should not be pursued. Our efforts and resources should be focused on real problems that admit real solutions. Omnis ars naturae imitatio est.