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Energy Usage Reports: Environmental awareness as part of algorithmic accountability

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arxiv 1911.08354 v2 pith:T6ZYH3ZO submitted 2019-11-19 cs.LG cs.CYstat.ML

classification cs.LGcs.CYstat.ML
keywords energypartreportsusageaccountabilityalgorithmiccomputerelectrical
verification ladder T0 review T1 audit T2 compute T3 formal
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The carbon footprint of algorithms must be measured and transparently reported so computer scientists can take an honest and active role in environmental sustainability. In this paper, we take analyses usually applied at the industrial level and make them accessible for individual computer science researchers with an easy-to-use Python package. Localizing to the energy mixture of the electrical power grid, we make the conversion from energy usage to CO2 emissions, in addition to contextualizing these results with more human-understandable benchmarks such as automobile miles driven. We also include comparisons with energy mixtures employed in electrical grids around the world. We propose including these automatically-generated Energy Usage Reports as part of standard algorithmic accountability practices, and demonstrate the use of these reports as part of model-choice in a machine learning context.

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Cited by 3 Pith papers

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