John Kay here again is at his best.
Do read the post below, published as his weekly culumn in The Financial Times.
I commented on it as follows:
Important post, as always trying to combat orthodoxies long past and denounce, often in oblique way, the vested interests who profit from the blindness, biases and ignorance of the many.
Yes, decision making in our era almost always involves elements of Uncertainty, hence the field called DMUU (Decision Making Under Uncertainty), and the problem is compounded when it also involves Contradictory Certainties (in this case the field is called DMUCC), or ignorance of certain essential elements (the field of DMUI).
I would love to see John also study and write about pioneers who try to break the veil of ignorance, and propose new, groundbreaking paradigms, for example:
1. the Theory of Socio-Cultural Viability, who informs so many of the reasons why poor decisions have been and are still made,
2. the work of Robert Kegan who is so preoccupied by human meaning-making and the evolution of consciousness, not in tune with demands of our environment”
I believe Joh’n colum participates in the ideas brought forward recently here, “Weaving the Ideas of Mary Catherine Bateson, Hartmut Rosa, Robert Kegan, and Cities as Forces for Good, into a Grand Challenge for Retirees to Save the Future”
A wise man knows one thing – the limits of his knowledge
We do great damage by claiming to know things that are not known, by asserting certainty in the face of uncertainty and ambiguity, and by attaching a veneer of rationality to decisions that have in fact been made on other, rarely articulated, grounds. The paradoxical result is all too obvious. The public sector and large bureaucratic organisations appear as paragons of good decision making process and exemplars of bad decisions.
John Maynard Keynes, who never tried to conceal that he knew more than most people, also knew the limits to his knowledge. He wrote “about these matters – the prospect of a European war, the price of copper 20 years hence – there is no scientific basis on which to form any calculable probability whatever. We simply do not know.”