Information Systems for Environmental Sustainability

IT, Resource Productivity, Environmental Preservation, and the Fourth Industrial Revolution

AI Should Incorporate Environmental Costs When Evaluating Effectiveness

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Research manuscript published by Emma Strubell, Ananya Ganesh, and Andrew McCallumin in June 2019 and available on ( develops an AI environmental cost framework and assesses several algorithms. Popular NLP approaches exhibit wide variation in power, hours, and emissions. Recommendation:

Authors should report training time and sensitivity to hyperparameters. Our experiments suggest that it would be beneficial to directly compare different models to perform a cost-benefit (accuracy) analysis.

Author: nigelpm

Associate Professor of Information Systems, Stephen M. Ross School of Business, University of Michigan - Helping organizations to navigate digital transformation.

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