Image is in the public domain via Īsimov was inspired in his vision of a collapsing empire by the eighteenth century book The History of the Decline and Fall of the Roman Empire by Edward Gibbon. Republic (Red), Empire (Purple), Eastern/Byzantine Empire (Yellow) and Western Empire (Blue). Animated map of the Roman Republic and Empire between 510 BCE and 530 CE. Psychohistory could never work in practice. But in reality there was never any need for such a far-fetched reason for the system fail. In the books, this process fails when a mutant somehow falls outside the system’s predictive ability. In Asimov’s Foundation series, a team of mathematicians led by Hari Seldon lays out a broad brush prediction of the way that the galactic Empire would fall apart, leaving recorded messages that predict future events through the centuries. This involved an extremely powerful form of statistics, which was able to predict the development of the culture it studies, down to individual events. Asimov based his Foundation series of stories on a fictional concept called psychohistory. The failure of the pollsters would have saddened that doyen of American science fiction writers, the late, great Isaac Asimov. “Let’s assume the racehorse is a sphere.” The Decline and Fall of the Roman Empire, Asimov’s Inspiration “No,” she says, “the important thing is to breed selectively for the essential characteristics of speed.” The physicist frowns and turns to a whiteboard. The dietician says “We just need to develop a perfect diet for physical stamina.” This makes the geneticist shake her head. This leads to the old scientist’s joke: a dietician, a geneticist and a physicist are arguing about how to produce the perfect racehorse. To make their numbers work, physicists often apply extremely broad simplifications. By Phillip Leonian from New York World-Telegram & Sun. Science has come increasingly to depend on math, to the extent that much modern physics is driven by it – yet mathematics and reality are very different things, especially when dealing with as complex a system as a country’s electorate. This is the kind of issue that is at the heart of my recent book Are Numbers Real?, exploring the relationship between mathematics and reality. If there’s one lesson that we have learned from recent shock political results, whether it’s Brexit in the UK, or the election of Donald Trump to the White House, it is that we can’t trust the polls, which failed miserably to predict the outcomes.
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