Saturday, November 10, 2012

Knowledge and uncertainty--a quotation


“Knowledge is an unending adventure at the edge of uncertainty”
British mathematician, biologist, historian of science, theatre author, poet and inventor
 
 
 

1 comment:

  1. From Pavel Barseghyan (blog http://pavelbarseghyan.wordpress.com/)


    John,
    Thank you for this quotation. In parallel with its general meaning, it is very interesting from the point of view of risk analysis.

    The fact is that new knowledge is usually born in the process of solving problems on the border of possible and impossible for a particular area of expertise. If we approach this issue from the point of view of the complexity / difficulty of solved problems, we can see that each time period in the process of development is characterized by a maximum feasible complexity / difficulty of problems in a particular area.

    In general, there are very interesting events happening near the upper limit of complexity / difficulty. First of all it is the center of gravity of innovations and progress, and it is the place where the whole front of basic science, as well as most high-tech projects is concentrated, with all of their problems, delays, feasibility risks and possible failures.
    If we approach this problem from the point of view of people performing the work, each individual (staff, design team, the company, even society as a whole), depending on their knowledge and skills has an upper limit of the difficulty of work, above which the work is simply not feasible for that individual.

    Besides, if the difficulty of the work increases and approaches the upper limit specified above, then work gradually becomes unfeasible and correspondingly the risk of failure increases.

    Quantitatively this means that a gradual transition from the linear region of risks to the nonlinear region of risks takes place. It is this very circumstance that leads to the usage of asymmetric risk functions, sometimes with fat tails.

    It is necessary to take into account that mathematical forms of risk functions can vary widely depending on the characteristics of a particular problem and the nature of nonlinearity. In other words, each concrete problem should have its own risk function, just like any linear or non-linear system has its specific input to output transfer function.

    Pavel

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