Saturday, October 04, 2014

On the future ...

The Chinese philosopher Lao Tzu once stated, “Those who have knowledge don’t predict. Those who predict don’t have knowledge”. However, let us assume that there is future change that is known to everyone and change that is unknown to all (i.e. we’re forced to speculate and predict). Advantage can be created by a business through change that is known only to a few and “unevenly distributed”. 

This raises a question; can we determine a means of identifying future change that is knowable but not known to all? When examining literature, we can often cite examples of past science fiction novels that appear prophetic. However, the sheer volume of publications (in excess of 70K novels & short stories per annum) means that this can be attributable to pure coincidence and often such predictions suffer from interpretation effects (i.e. we read into them prophecy where there is none, the prognosticators’ equivalent of the P.T Barnum effect). 

The challenge is whether we could develop a means of more accurately predicting change beyond random coincidence. Could we predict the predictable because the knowledge was already there even if we were only vaguely aware of it? Could we create a more ‘prophetic’ story? To exploit the future, we need to somehow create a framework that allows us to uncover knowable change. Such a framework must be inherently holistic, interdisciplinary, relative, repeatable and useful: - 
  • Holistic because of the potential for combinations to be greater than the individual change (e.g. standard electricity plus material science leading to computing. 
  • Interdisciplinary because it impacts not just technological, economic and physical systems but also social systems. 
  • Relative because the changes may be different depending upon the observers’ viewpoint i.e. the impacts in one industry may not be the same in all. 
  • Repeatable because the validity of single, one off predictions provides no method of testing beyond the scope of the single prediction. 
  • Useful because vague generalisations and known effects provides no means of exploitation. 
Is this possible? The answer turns out to be ... sort of, maybe ... but I'll leave that to another day ... well, to be precise ... another 7,200 days approximately in order to gather the data to validate it.