The margin for error makes the studies that try to aggregate these things almost meaningless. For example, Google CoLab is running in Google data centers, whic

The margin for error makes the studies that try to aggregate these things almost meaningless. For example, Google CoLab is running in Google data centers, which are carbon neutral. Which is more or less true, but also depends on the exact nature of the source of their power and accuracy of the carbon offsets they purchase, and we all know Google is perfectly accurate and truthful all the time. /s lol I trust Google insofar as their publicized usage of renewables and extensive use of solar. I also suspect that they're on-grid and a net producer of energy, taking advantage of deals with power companies and governments to ekeout every last penny of value in their infrastructure. The problem is that without exact reporting of numbers, the margin of error for that source alone creates huge uncertainty in trying to assess the net carbon footprint of their service. How much research is being done using Google infrastructure? How much is being done on college campus data centers that run their hpsc on solar and wind? How much money is spent on offsets by those other sources? Again, the reality requires exact knowledge, since the usage of offsets introduces huge uncertainty, so aggregate reported usage could vary in accuracy as a proxy by more than 100% of the naively assumed footprint. The studies are only as good as their data, and the data isn't very good unless it's obtained through legal mandate, via subpoena or regulated reporting. To my knowledge, very little of the data available for these estimates is anything except self reported numbers. The math and analyses they do are great, but the margin of error likely exceeds 75%.