One premise of IMT is that there is no randomness, that there are “natural laws and initial conditions [that] define all events, and all event outcomes are predictable with all information” (28). The assumption that there exists no randomness is subject to closer examination. There exists a theory called Chaos Theory, also known as the butterfly effect. An article by Margaret Rouse discusses the implications of this theory, which looks to research by Edward Lorenz. Lorenz found that if you set up the exact same initial conditions to predict weather conditions, the outcomes are drastically different and unpredictable. The article states, “the slightest difference in initial conditions-beyond human ability to measure-made prediction of past or future outcomes impossible, an idea that violated the basic conventions of physics” (Rouse, 2008). This article provides an example of the unpredictability of a final outcome based on a set of initial conditions—which refutes a major component of IMT theory.
Does this article support or contradict IMT concepts? Because of our human limitations can we ever know 100% information? Given this information how should we treat complex systems?
Article Reference: Chaos Theory – What is .com -March 2009 – http://whatis.techtarget.com/definition/chaos-theory
Kashiwagi, D. (2013). 2013 Information Measurement Theory.