Stochastic Conspiracies?

Note: This is the third blog post in a four part series.

When are conspiracies real? We have been reviewing a recent New York Times column on this question, “A Better Way to Think about Conspiracies,” in which Ross Douthat formulates an elaborate four-part test for deciding which alleged conspiracies to keep an open mind about. Two of Douthat’s rules of thumb can be combined into a single global criterion: stochastic selectivity. Specifically, Douthat concludes his essay with the following two guidelines: (1) we should consider taking conspiracy theories more seriously only when “the mainstream narrative has holes,” and (2) just because one particular fringe theory or myth might be true doesn’t mean all of them are.

Alas, Douthat’s stochastic selectivity criterion is neither here nor there. Why? For starters, because even so-called “mainstream” or consensus narratives, will always have gaps or holes in them. A narrative is just a story, and by definition all stories are necessarily incomplete. Furthermore, even a story with a single hole or gap might be called into question, depending on the size of that gap or its nature. The German stab-in-the-back myth of the Weimar Republic era (1919 to 1933), for example, fills a gap in the story of Imperial Germany’s defeat in the First World War. After all, how could one of the best-trained and most well-equipped military forces in the world, an invincible army that was said to be “undefeated on the battlefield,” lose the war? Although the mainstream view today is that Imperial Germany had lost the war by late 1918 because her army was out of reserves and was overwhelmed by the entrance of the United States into the war, there are still significant holes in this story, especially from the perspective of a post-war demoralized German public. After all, the United States’ first major offensive in WWI did not occur until the Battle of Cantigny in mid-1918, and in any case, the German public at that time had no way of knowing the true number of Germany’s reserves, as that number was classified information.

That said, to the extent that two or more imagined conspiracies are stochastically independent, then point #2 appears to be logically sound, since the probability of all such conspiracies being true is the product of their individual probabilities. But (wait for it!) what happens if we are considering overlapping conspiracies, i.e. conspiracies with similar goals or with the same subset of members? Stated formally, what happens when the conspiracies or secret plots under consideration are dependent events instead of independent ones? (Two events are said to be “independent” if knowing that one event has occurred doesn’t change the probability of the other event’s occurrence.) By way of historical example, given the anti-Semitic origins of many interwar European conspiracy theories, many people in Weimar Germany who fell for “The Protocols of the Elders of Zion” hoax might be more likely to believe in stab-in-the-back betrayal myth as well. Either way, whether we classify two or more conspiracies as dependent or independent events, there is a much bigger problem with Douthat’s approach to conspiracy thinking. I shall identify this fatal flaw in my next post.

Dependent Events (video lessons, examples and solutions)
Image credit: Online Math Learning

About F. E. Guerra-Pujol

When I’m not blogging, I am a business law professor at the University of Central Florida.
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1 Response to Stochastic Conspiracies?

  1. Pingback: Conspiracies and Religion | prior probability

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