\u201cSynchronicity is a phenomenon in which people interpret two separate \u2013 and seemingly unrelated \u2013 experiences as being meaningfully intertwined, even though there is no evidence that one led to the other or that the two events are linked in any other causal way.\u201c [Psychology Today]<\/p>\n\n\n\n
Psychologists see this mainly as a confirmation bias \u2015 people see coincidences as meaningfully related because they want to see them this way. In other words, the urge to see meaningful patterns may overshoot. Of course, confirmation bias is a well-understood phenomenon that plays a role in many fields. People may \u2018suggest\u2019 themselves into the conviction that there is no bias but reality, and that there are meaningful patterns where there are none. This is a natural phenomenon that may explain at least a number of cases.<\/p>\n\n\n\n
So, does synchronicity not exist scientifically at all, or do we need to discard science? In my view, neither of both. Put without the double negations: Synchronicity exists in a number of cases and is a scientifically valid concept.<\/p>\n\n\n\n
Two options in one picture<\/strong><\/p>\n\n\n\n A and B are mental patterns that correspond with observations.<\/p>\n\n\n\n The two options:<\/p>\n\n\n\n a) A and B are related through synchronicity (y) \u2192 the grey area<\/p>\n\n\n\n b) A and B are related through C, synchronously (x) \u2192 the total area<\/p>\n\n\n\n Let\u2019s make A a person and B a happening, as in the above example:<\/p>\n\n\n\n The feeling and the explanation<\/strong><\/p>\n\n\n\n The feeling may be the same in a) and b).<\/p>\n\n\n\n The explanations are very different \u2015 at first sight. At second sight, it depends:<\/p>\n\n\n\n The more A experiences this profoundly instead of only at the surface level, the more these two options may come together. Note that in the image, C is depicted as a larger pattern. This can be very large and deep.<\/p>\n\n\n\n The proof is always challenging.<\/strong><\/p>\n\n\n\n A synchronicitor might say that conceptual proof is difficult, and that modern science doesn\u2019t count in this since it lacks subtlety. Indeed, experimental proof is hard \u2015 in both ways.<\/p>\n\n\n\n However, epidemiological proof is feasible. Probably, A.I. will clarify this in the future, capturing patterns A, B, and C from a time perspective.<\/p>\n\n\n\n What leads to C?<\/strong><\/p>\n\n\n\n This is the same question as: \u201cWhere does depth end?\u201d<\/p>\n\n\n\n Present-day science is limited in this. That doesn\u2019t mean that anything goes. Confirmation bias may lead one astray in any direction. Precisely, therefore, one needs to fully take into account rationality and depth<\/a>.<\/p>\n\n\n\n <\/p>\n![\"\"](\"https:\/\/i1.wp.com\/aurelis.org\/blog\/wp-content\/uploads\/2022\/07\/image.png?resize=520%2C274&ssl=1\")
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