June 12, 2015 at 03:29PM
"in nonlinear, highly networked systems, a more accurate estimation of risk [is] long-tailed distribution." #readingToday  

_The study of complexity has shown that in nonlinear, highly networked systems, a more accurate estimation of risk would be a so-called "long-tailed" distribution.  Figure 1(b) shows a hypothetical long-tailed distribution of risk (here, only the "loss" side is shown). The longer non-zero "tail" (far right-hand side) of this distribution shows that the probability of a catastrophic loss is significantly higher than for a system obeying a normal distribution.  If risk models in 2008 had employed long-tailed rather than normal distributions, the possibility of an "extreme event"—here, "catastrophic loss"—would have be judged more likely. _

In 1894, the physicist and Nobel laureate Albert Michelson declared that science was almost finished; the human race was within a hair's breadth of understanding everything: It seems probable that most of the grand underlying principles have now been firmly established and that further advances ...