I see my one time drinking buddy David Grimes made the front page of the BBC (and a lot of other places) with his paper on the how possible is it to keep a conspiracy theory secret for any length of time.

He cleverly user data from some real conspiracies (NSA Prism, the Tuskegee syphilis experiment, and the Federal Bureau of Investigation (FBI) forensic scandal) to model the likelihood that a secret held by many will eventually come out.

And then he applied that to some of the big “popular” conspiracies – that the moon landings were faked, global warming is a conspiracy amongst scientists, and that pharmaceutical companies are concealing a cure for cancer.

The model shows that it would be impossible to keep such large conspiracies under wraps for any length of time. But then what would you expect. Think of all the trivial persona; secrets you are aware of that have gotten out. And then think could thousands of people keep massive things quiet in defiance of their conscience like – We have a cure for cancer. We lied to the world about the moon landings. We are causing deceiving the world about climate change, just so we can get some research funding. The moon landing one always struck me as particularly daft, as you would need the Russians (ostensible “losers” in the race to the moon) to keep quiet as well.

And like all good scientists Dr Grimes used his work to make some predictions. To keep something like the moon landings secret for nearly 50 years the would need a group of conspirators of about 250 people. Considering how many were involved just in running each of the Apollo missions it’s farcical to maintain there is a great secret here.

There is great scope for future work here. Looking at some other real failed conspiracies would refine the model and allow for better estimates. And then I want it applied to some other great conspiracies. Not we can at last figure out how big and how extensive is the reach of the Illuminati, and the Elders of Zion! My bet is the size will come out to be around 0-1 with the greater probability of the lower estimate 🙂