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Overestimating AI's water footprint

Researchers need to be more careful about the inputs into their models. Overestimates undermine the goal of reducing the environmental impact of IT.

Influencing the carbon emissions of AI

There is a correlation between the training time and energy consumption, but that doesn’t mean there is a correlation between training time and carbon emissions.



Dirty data? Carbon footprint of photo storage

An example of poor quality research with flawed assumptions designed as click-bait to get news coverage timed to land during COP26. Deleting a few photos will have zero impact on your carbon footprint.

Standardizing carbon accounting

It is currently impossible to properly compare how sustainable one product is vs another. Pictures of wind farms look nice, but how do you choose which cloud region to deploy (or move) your resources if there is no way to compare them?


Spectrum of transparency

More rigorous transparency regulations for negative externalities to force companies to measure, and reduce.