Interesting papers to read 5
Piero Giacomelli
CIO | Group IT Manager at Fidia Farmaceutici SpA | Packtpub Book Author | Manning Publication Reviewer | Passionate about math
Today I would like to share an article of 40 years ago that give the birth of the so called "Doomday argument".
The anthropic principle and it implications for biological evolution
By B. Carter.
Carter tried to estimate the possible numbers of human beings (Homo Sapiens Sapiens) to try to understand what would be our probability of extinction.
The premise of the argument is as follows: suppose that the total number of human beings that will ever exist is fixed. If so, the likelihood of a randomly selected person existing at a particular time in history would be proportional to the total population at that time. Given this, the argument posits that a person alive today should adjust their expectations about the future of the human race because their existence provides information about the total number of humans that will ever live.
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The surprisingly outcome of this argument is that if approximately 60 billion humans have been born so far, so it can be estimated that there is a 95% chance that the total number of humans N will be less than 20x60 billion = 1.2 trillion. Assuming that the world population stabilizes at 10 billion and a life expectancy of 80 years, it can be estimated that the remaining 1140 billion humans will be born in 9120 years. Depending on the projection of the world population in the forthcoming centuries, estimates may vary, but the argument states that it is unlikely that more than 1.2 trillion humans will ever live. The interesting fact is that the more people are born the more we will arrive faster at our extinction.
However this means that no matter how homo sapiens will go extinct at some point in the future but as for the Neanderthals, a new species of Homo could take our place.
The argument is still controversial to these days because some assumption could be wrong but I think it is a must read to understand how simple probability could get interesting result even outside the traditional math field.