Humans are predication machines. Every second of every day, we are trying to navigate the world based on our predictions. We are making predictions when we book a holiday, based on our prior knowledge and beliefs, that our destination will still exist when we travel there next summer and that an airplane will still exist that is capable of flying us there safely.
We are constantly assessing our prior knowledge and beliefs and testing that against any new data that comes into us via our senses. This neatly describes how our brain works and is also the basis of a remarkable mathematical theorem called Bayes theorem, devised by Thomas Bayes, an obscure 19th-century English Presbyterian minister.
Bayes theorem can, according to the author (a science writer and twice winner of the Royal Statistical Society’s award for statistical excellence in journalism), be used to explain all human behaviour and perception and the workings of the natural world around us.
It can even explain depression, the author argues, by identifying the cause as being inappropriately strong prior beliefs about perceived negative aspects of the self – such as “I am a bad person”. When such “priors”, as the author calls them, are strong in an individual, they cannot be shifted no matter how much new evidence comes along to disprove them.
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It also explains why, the author argues, some people hold so strongly to the belief that vaccines cause autism. The evidence to the contrary is not enough to shift their prior belief that mainstream medicine is lying to us.
Based on our priors, we believe that an apple falls down from a tree when ripe, not up. Yet, if we saw an apple that fell upwards, we would have to update the likelihood of the next apple falling from a tree – our prior belief would shift to accommodate what we have seen.
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The constant updating of data about the world through our senses, and testing it against our belief system, is how our brains work. It is also how artificial intelligence works.
It is possible to predict the future, he says, with greater or lesser confidence depending on how close our priors match up with the new data we are constantly receiving.
Life is a poker game, the author says, where we are all trying to make the best decisions we can based on the limited amount of information we have. This book is about an equation, devised in 1763, which describes – mathematically – how we do that.
