Comment author:kierangreig
20 May 2016 05:34:11PM
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0 points
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I believe a plausible cumulative distribution function for the probability of extinction would have an asymptote—or else something like an asymptote, e.g., the probability of extinction between 100 and 1000 years from now is about the same as the probability of extinction between 1000 and 10,000 years from now, etc.

Using that example the probability of value existing could be roughly modelled as: p(n)= (1-r)^(log(n-1)) Where p is the probability of value existing n years into the future, r is the extinction probability between 10 and 100 years, log means the log base 10 and n is the number of years in the future. This relationship works for n>2.

I was curious about what the average of p(n) for that type of function would be over the next 10^11 years. Some available extinction estimates put r between 10% and 50%. I imagine there’s also similar variance within EAs’ r value. Using r= 10% the average of p(n) over 10^11 years seems like it would be 3 * 10^-1 . Using r= 50% the average of p(n) over 10^11 years would be ~7 * 10^-4. I used Wolfram Alpha’s integral calculator for these calculations and I am not that it’s performing the calculation correctly. These averages for p(n) could make the impact on far future EV significant.

I don’t have strong views on which CPONE model is best and the ones I mention here may be flawed. I softly lean towards including CPONE models because the posterior then more closely reflects the user’s view of reality, it’s not too difficult to include CPONE models, reasonable people may have different CPONE models, and the addition of a CPONE model may result in different cause prioritization conclusions.

I think multi-cellular life on earth makes for a better reference class. Multi-cellular life has taken several big hits over the years, but it's always bounced back.

Interesting. I hadn’t thought of that reference class before :)

When you're looking at interventions' effects on the far future, the numbers are so big that the prior does a lot of work—10^54 and 10^55 expected utility don't look that different after updating on the prior.

Excellent point :) I wasn’t fully taking that into consideration. Updates me towards thinking that CPONE models are less important than previously thought. I think reasonable people could have a CPONE model which causes more than one order of magnitude difference in EV and therefore cause a more significant difference after updating on the prior.

[edited originally I accidentally used the natural logarithm instead of log base 10 when calculating the average of the probability function over 10^11 years]

## Comments (38)

Best*0 points [-]Using that example the probability of value existing could be roughly modelled as: p(n)= (1-r)^(log(n-1)) Where p is the probability of value existing n years into the future, r is the extinction probability between 10 and 100 years, log means the log base 10 and n is the number of years in the future. This relationship works for n>2.

I was curious about what the average of p(n) for that type of function would be over the next 10^11 years. Some available extinction estimates put r between 10% and 50%. I imagine there’s also similar variance within EAs’ r value. Using r= 10% the average of p(n) over 10^11 years seems like it would be 3 * 10^-1 . Using r= 50% the average of p(n) over 10^11 years would be ~7 * 10^-4. I used Wolfram Alpha’s integral calculator for these calculations and I am not that it’s performing the calculation correctly. These averages for p(n) could make the impact on far future EV significant.

I don’t have strong views on which CPONE model is best and the ones I mention here may be flawed. I softly lean towards including CPONE models because the posterior then more closely reflects the user’s view of reality, it’s not too difficult to include CPONE models, reasonable people may have different CPONE models, and the addition of a CPONE model may result in different cause prioritization conclusions.

Interesting. I hadn’t thought of that reference class before :)

Excellent point :) I wasn’t fully taking that into consideration. Updates me towards thinking that CPONE models are less important than previously thought. I think reasonable people could have a CPONE model which causes more than one order of magnitude difference in EV and therefore cause a more significant difference after updating on the prior.

[edited originally I accidentally used the natural logarithm instead of log base 10 when calculating the average of the probability function over 10^11 years]