True and full reflection of knowledge

True and full reflection of knowledge

Consider this question: "Will bitcoin to US Dollar exchange rate go up or down in 48 hrs?"

Different people will have different answers to this question, based on the information they have. Without any information, their answer will be a guess. However, that is hardly ever the case. Different people have different information. Sometimes, what we know is implicit. We may say: "I don't know why but I think bitcoin will go down". It does not mean that we have no information. Only that we cannot organize it or point to it directly. Others may have more concrete information. For example, they may know of a regulatory decision that was released recently and that may negatively affect the market, which they expect will result in the price of bitcoin going down.

Either way, different people have different sources of information, different methods for evaluating and predicting, and will therefore have different answers to this question.

If we asked all the people that have some knowledge this question, the sum of their answers – integrating their access to sources of information available to them, including formal, industry analyses and reports – will be a True and Full Reflection of Knowledge (available for consideration). Revisiting our 48-hour example, we know that after 48 hours, the question will be resolved. We also know that if after 47 hours and 59 minutes the bitcoin is significantly up, the prediction risk is much smaller. Over those 47 hours and 59 minutes, other people state their predictions at different times. In doing that, they provide information that, as we progress in time, reduces the uncertainty. The crowd-wisdom process will naturally fluctuate, until it will converge to a True and Full Reflection of Knowledge.

This intuitive perception of an adaptive and dynamic risk-reward evaluation is rarely applied. CloseCross includes the crowd wisdom in financial predictions as an integral part of its operation

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