Several great thinkers defined risk in different ways and laid the foundation of our understanding of the meaning of risk and its corresponding relationship with uncertainty and knowledge. The most influential in this domain, Frank Knight, had devised an analytical framework to clarify an important distinction among risk, uncertainty, and full knowledge (Langlois and Cosgel 1993). He based his categorization on the fact that it is ultimately based on whether the classification of states (or instances) of a particular uncertain event is exhaustive, and not on the assigned subjective probabilities of these states (Langlois and Cosgel 1993). This classification scheme is based on three types of probabilities, a priori probability (the universe of outcomes is known and thus can be mathematically determined), statistical probability (lack of homogeneity, empirical determination of the universe of outcomes), and estimated probability (universe of outcomes can not be defined) (Jarvis 2011). Based on these types of probabilities, Knight associated risk with a lack-of-knowledge situation or state where outcomes are either known (a priori probability) or probable (statistical probability), meaning that the list of outcomes with their frequencies of occurrence and their impacts can be assessed objectively. On the other hand, he associated uncertainty with a black vacuum (knowledge vaccum) characterized by the inability to exhaustively classify all of its ‘unique’ outcomes, yet the latter can be judged through qualitative and estimated probabilities (Jarvis 2011). Recent interpretations have associated uncertainty with the inability to make predictions due to discontinuities, complexities, and heterogeneity of environments (Richard and Susan 2010).
Posts Tagged ‘priori’
May 20th, 2012 2 comments
Categories: Risk Management
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