In 2003 Bostrom imagined a technologically adept civilization that possesses immense computing power and needs a fraction of that power to simulate new realities with conscious beings in them. Given this scenario, his simulation argument showed that at least one proposition in the following trilemma must be true: First, humans almost always go extinct before reaching the simulation-savvy stage. Second, even if humans make it to that stage, they are unlikely to be interested in simulating their own ancestral past. And third, the probability that we are living in a simulation is close to one…
To get a better handle on Bostrom’s simulation argument, Kipping decided to resort to Bayesian reasoning. This type of analysis uses Bayes’s theorem, named after Thomas Bayes, an 18th-century English statistician and minister. Bayesian analysis allows one to calculate the odds of something happening (called the “posterior” probability) by first making assumptions about the thing being analyzed (assigning it a “prior” probability).
Kipping began by turning the trilemma into a dilemma. He collapsed propositions one and two into a single statement, because in both cases, the final outcome is that there are no simulations. Thus, the dilemma pits a physical hypothesis (there are no simulations) against the simulation hypothesis (there is a base reality—and there are simulations, too). “You just assign a prior probability to each of these models,” Kipping says. “We just assume the principle of indifference, which is the default assumption when you don’t have any data or leanings either way.”
So each hypothesis gets a prior probability of one half, much as if one were to flip a coin to decide a wager.