Lessons from Quantum Mechanics
When Quantum Mechanics was being developed at the beginning of the 20th century it was incredibly weird to establish a theory based on probabilities. Nothing was further from the mind of scientists at the time from a probability approach that seemed as if God was playing dice with the world... All the paradoxes of quantum mechanics including the infamous Schroedinger's cat experiment stem from this difficulty to understand the essence of the probability predictions as part of physical phenomena.
Nearly a century later we - think we - understand quantum mechanics a lot better than we did back then and we have certainly developed the tools and state of mind to understand the probabilistic nature of physical phenomena in the microscales.
But what about the macroscales?
When we predict that 'tomorrow will rain with a probability of 70%' we are not able to use a frequentist probabilistic approach in which we do 1000 experiments in which we find that it rained in 700 of them and did not rain in 300. We imply something completely different, that can be parallelized with Schrodinger's cat. We face tomorrow as an event that includes both occurrences weighted with a series of probabilities. The 'wave function' of tomorrow exists in both states of rain and non-rain and takes a value only when we wake up tomorrow and observe that it is raining or not. Similar to Schrodinger's cat when we observe the state that the cat is in only when we open the box. Of course, the Schroedinger paradox has to do with the link from the microcosm of the element that breaks the cyanide bottle which causes an effect in the macrocosm, so it aims at something completely different, but the bottom line is the superposition of the two states that are plainly probabilistic, and are helping us to plan our future based on the probabilities that make up the complete state.
Similarly - and perhaps I should write a more detailed article on this - Feynman's formulation of Quantum Mechanics based on the path integral formulation gives an extra insight for the decision trees that can be created for complex processes like the ones that we deal with in Lawptimize.
One hundred years later it seems like it's quantum mechanics can assist us and play a role as a tool in the interpretation of our results and the calculation of our probabilities. Our minds seem to be more trained to the idea of understanding the relationships.
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