For hundreds of years, philosophers and scientists have encouraged one another to keep their explanations of the natural world as simple as possible. Ockham’s razor, attributed to the 14th century Franciscan friar, William of Ockham, is a well-established and much-cited philosophical principle that of two possible explanations, the simpler one is more likely to be correct. More recently, Albert Einstein is supposed to have said: ‘everything should be made as simple as possible, but not simpler’. I don’t think that William of Ockham and Albert Einstein were arguing that we should keep everything simple; but rather that we should not make scientific explanations more complicated than necessary. However, do we have a strong preference for focusing on phenomena whose behaviour is sufficiently uncomplex that it can be explained by relatively simple theories and models? In other words, to quote William Wimsatt, ‘we tend to ignore phenomena whose complexity exceeds the capability of our detection apparatus and explanatory models’. Most of us find science hard; perhaps, this is not just about the language used by the cognoscenti to describe it [see my post on ‘Why is thermodynamics so hard?‘ on February 11th, 2015]; but, more about the complexity of the world around us. To think about this level of complexity requires us to assemble and synchronize very large collections of neurons (100 million or more) in our brains, which is the very opposite of the repetitive formation of relatively small assemblies of neurons that Susan Greenfield has argued are associated with activities we find pleasurable [see my post entitled ‘Digital hive mind‘ on November 30th, 2016]. This might imply that thinking about complexity is not pleasurable for most us, or at least requires very significant effort, and that this explains the aesthetic appeal of simplicity. However, as William Wimsatt has pointed out, ‘simplicity is not reflective of a metaphysical principle of nature’ but a constraint applied by us; and which, if we persist in its application, will render the world incomprehensible to us.
Sources:
William C. Wimsatt, Randomness and perceived randomness in evolutionary biology, Synthese, 43(2):287-329, 1980.
Sometimes things only look simple in models but it a heck of a job to get the required variables. For example the question if it gets warmer on Earth looks very simple to answer but it probably is a whole lot of work to find out if it really is the case.
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