Hmmm, you are entirely correct. I ran the numbers as log (150,000) / log (2), and got 17. This was on the assumption that Alcor probably doesn’t handle more than a single patient in a day.
More conservatively, I should have probably assumed Alcor handles ~10/year (based on 2010 figures). At that point we get 0.025 per day, which is about 5 additional doublings. So it looks like a fairer number would have been 22 doublings, assuming that this rule holds true. Thus, my padding to triple was probably slightly pessimistic, given the assumptions I made.
Which is fortunate because 17 increases by 10% would give us a total increase of just over 5x, but 10.5 increases by 10% give us a 2.7x increase, or (as in the article) a tripling if we’re generous.
Either the two mistakes cancel each other out, or there’s a typo, or some clever math trick I’m not aware of.
Going from 100 to 150,000 is not 17 doublings, but log(150000/100)/log(2), about 10.5
Why is that the figure used? 150,000 is the number of people who die every day—how is that relevant to the calculations in this article?
Hmmm, you are entirely correct. I ran the numbers as log (150,000) / log (2), and got 17. This was on the assumption that Alcor probably doesn’t handle more than a single patient in a day.
More conservatively, I should have probably assumed Alcor handles ~10/year (based on 2010 figures). At that point we get 0.025 per day, which is about 5 additional doublings. So it looks like a fairer number would have been 22 doublings, assuming that this rule holds true. Thus, my padding to triple was probably slightly pessimistic, given the assumptions I made.
Which is fortunate because 17 increases by 10% would give us a total increase of just over 5x, but 10.5 increases by 10% give us a 2.7x increase, or (as in the article) a tripling if we’re generous.
Either the two mistakes cancel each other out, or there’s a typo, or some clever math trick I’m not aware of.