you need to make some pretty strong assumptions to overcome a 1:170,000,000,000 difference.
Actually you don’t. Consider the following highly simplified toy model.
You’re not sure where the great filter is but you think there is a 50% chance it’s before evolving intelligence (scenario A), and 50% that it’s afterward (scenario B).
In scenario A each galaxy only has a 0.1% chance of having intelligent life. (Note that nevertheless the observable universe will still have life somewhere since 0.1% is a lot more than 1⁄170,000,000,000.)
In scenario B each galaxy has (multiple) planets with intelligent life in it.
Combining these two scenarios gives 100% for life in the universe and 50.1% for life in the galaxy.
By changing these numbers and adding more scenarios you can get different but similar results. You should try this yourself, it’s a good way to get an intuition for how Bayesian probabilities work. For example, try adding a scenario C where intelligent life is extremely rare and we exist only due to the anthropic principal. What happens when you assign scenario C 40% and keep scenarios A and B equally likely?
There’s >170 billion galaxies in the observable universe; you need to make some pretty strong assumptions to overcome a 1:170,000,000,000 difference.
Actually you don’t. Consider the following highly simplified toy model.
You’re not sure where the great filter is but you think there is a 50% chance it’s before evolving intelligence (scenario A), and 50% that it’s afterward (scenario B).
In scenario A each galaxy only has a 0.1% chance of having intelligent life. (Note that nevertheless the observable universe will still have life somewhere since 0.1% is a lot more than 1⁄170,000,000,000.)
In scenario B each galaxy has (multiple) planets with intelligent life in it.
Combining these two scenarios gives 100% for life in the universe and 50.1% for life in the galaxy.
By changing these numbers and adding more scenarios you can get different but similar results. You should try this yourself, it’s a good way to get an intuition for how Bayesian probabilities work. For example, try adding a scenario C where intelligent life is extremely rare and we exist only due to the anthropic principal. What happens when you assign scenario C 40% and keep scenarios A and B equally likely?
I’m mentally tired from banging my head against R and can’t think through this, so I’m dropping it here.
Feel free to try tomorrow.