Energy Usage Reports: Environmental awareness as part of algorithmic accountability
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Abstract (arXiv)
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.
Key facts. Cited by 44 papers in the map (data through 14 Oct 2026). First posted on arXiv 19 Nov 2019.
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Citing papers per year: 2021: 4; 2022: 3; 2023: 10; 2024: 10; 2025: 5; 2026: 12.
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- 2021Sustainable AI: Environmental Implications, Challenges and Opportunitiescited by 242
- 2024Calibrating Large Language Models Using Their Generations Onlycited by 65
- 2023Counting Carbon: A Survey of Factors Influencing the Emissions of Machine Learningcited by 42
- 2023How to estimate carbon footprint when training deep learning models? A guide and reviewcited by 34
- 2022Exploring Predictive Uncertainty and Calibration in NLP: A Study on the Impact of Method & Data Scarcitycited by 25
- 2024Non-Exchangeable Conformal Language Generation with Nearest Neighborscited by 21
- 2022Towards Climate Awareness in NLP Researchcited by 19
- 2023Towards energy-efficient Deep Learning: An overview of energy-efficient approaches along the Deep Learning Lifecyclecited by 14
- 2024TeenyTinyLlama: open-source tiny language models trained in Brazilian Portuguesecited by 13
- 2024Tucano: Advancing Neural Text Generation for Portuguesecited by 13
- 2024Hyperparameter Importance Analysis for Multi-Objective AutoMLcited by 9
- 2021Towards Quantifying the Carbon Emissions of Differentially Private Machine Learningcited by 8
32 more
- 2021NeurIPS 2020 NLC2CMD Competition: Translating Natural Language to Bash Commandscited by 7
- 2021EnergyVis: Interactively Tracking and Exploring Energy Consumption for ML Modelscited by 4
- 2022Position: Tensor Networks are a Valuable Asset for Green AIcited by 3
- 2024Towards Leveraging AutoML for Sustainable Deep Learning: A Multi-Objective HPO Approach on Deep Shift Neural Networkscited by 3
- 2024Evaluating the Energy Consumption of Machine Learning: Systematic Literature Review and Experimentscited by 3
- 2025SLM-Bench: A Comprehensive Benchmark of Small Language Models on Environmental Impacts--Extended Versioncited by 3
- 2025Benchmarking Energy Efficiency of Large Language Models Using vLLMcited by 3
- 2023Broadening the perspective for sustainable AI: Comprehensive sustainability criteria and indicators for AI systemscited by 2
- 2023Do Large Language Models have Shared Weaknesses in Medical Question Answering?cited by 2
- 2025La Leaderboard: A Large Language Model Leaderboard for Spanish Varieties and Languages of Spain and Latin Americacited by 2
- 2026The Environmental Cost of LLMs in AIED: Reporting and Practicescited by 2
- 2023Efficient Sentiment Analysis: A Resource-Aware Evaluation of Feature Extraction Techniques, Ensembling, and Deep Learning Modelscited by 1
- 2023An energy-based comparative analysis of common approaches to text classification in the Legal domaincited by 1
- 2023Tensor-Aware Energy Accountingcited by 1
- 2024An In-Depth Analysis of Data Reduction Methods for Sustainable Deep Learningcited by 1
- 2024OpenCarbonEval: A Unified Carbon Emission Estimation Framework in Large-Scale AI Modelscited by 1
- 2025Guidelines for the Quality Assessment of Energy-Aware NAS Benchmarkscited by 1
- 2023AI2: The next leap toward native language based and explainable machine learning frameworkcited by 0
- 2023An Analysis of Embedding Layers and Similarity Scores using Siamese Neural Networkscited by 0
- 2024A Comprehensive Sustainable Framework for Machine Learning and Artificial Intelligencecited by 0
- 2025Word Embedding Techniques for Classification of Star Ratingscited by 0
- 2026AI-CARE: Carbon-Aware Reporting Evaluation Metric for AI Modelscited by 0
- 2026The Compression Paradox in LLM Inference: Provider-Dependent Energy Effects of Prompt Compressioncited by 0
- 2026Accounting for AI Inference in Corporate GHG Inventories: A Four-Tier Methodology for Scope 3 Category 1 Reportingcited by 0
- 2026Classifying by Proxy: Explainable and Reproducible Ensemble of Proxy Tasks for Child Sexual Abuse Imagery Classificationcited by 0
- 2026Leveraging AutoML for Sustainable Deep Learning: A Multi-Objective HPO Approach on Deep Shift Neural Networkscited by 0
- 2026MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systemscited by 0
- 2026Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprintcited by 0
- 2026Environmental Impact of Generative and Agentic AI: An in-Depth Analysis and Green Solutionscited by 0
- 2026Greenpixie's AI Token Methodology: Assessing the Energy, Water and CO2-eq Impact of AI Tokens for Open and Closed Weight Modelscited by 0
- 2026A Holistic Assessment of the Carbon Footprint of Noor, a Very Large Arabic Language Modelcited by 0
- 2026Energy Variation in Training Modern Computer Vision Architecturescited by 0
- 2026Energy Variation in Training Modern Computer Vision Architectures29 Sep 2026
- 2026Greenpixie's AI Token Methodology: Assessing the Energy, Water and CO2-eq Impact of AI Tokens for Open and Closed Weight Models27 Sep 2026
- 2026Environmental Impact of Generative and Agentic AI: An in-Depth Analysis and Green Solutions26 Sep 2026
- 2026A Holistic Assessment of the Carbon Footprint of Noor, a Very Large Arabic Language Model22 Sep 2026
- 2026Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint7 Aug 2026
- 2026MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems28 Jun 2026
- 2026Leveraging AutoML for Sustainable Deep Learning: A Multi-Objective HPO Approach on Deep Shift Neural Networks22 Jun 2026
- 2026Classifying by Proxy: Explainable and Reproducible Ensemble of Proxy Tasks for Child Sexual Abuse Imagery Classification14 Jun 2026
- 2026Accounting for AI Inference in Corporate GHG Inventories: A Four-Tier Methodology for Scope 3 Category 1 Reporting9 Jun 2026
- 2026The Environmental Cost of LLMs in AIED: Reporting and Practices3 May 2026
- 2026The Compression Paradox in LLM Inference: Provider-Dependent Energy Effects of Prompt Compression6 Mar 2026
- 2026AI-CARE: Carbon-Aware Reporting Evaluation Metric for AI Models17 Feb 2026
32 more
- 2025Benchmarking Energy Efficiency of Large Language Models Using vLLM10 Sep 2025
- 2025SLM-Bench: A Comprehensive Benchmark of Small Language Models on Environmental Impacts--Extended Version21 Aug 2025
- 2025La Leaderboard: A Large Language Model Leaderboard for Spanish Varieties and Languages of Spain and Latin America1 Jul 2025
- 2025Guidelines for the Quality Assessment of Energy-Aware NAS Benchmarks21 May 2025
- 2025Word Embedding Techniques for Classification of Star Ratings18 Apr 2025
- 2024Tucano: Advancing Neural Text Generation for Portuguese12 Nov 2024
- 2024Evaluating the Energy Consumption of Machine Learning: Systematic Literature Review and Experiments27 Aug 2024
- 2024A Comprehensive Sustainable Framework for Machine Learning and Artificial Intelligence17 Jul 2024
- 2024OpenCarbonEval: A Unified Carbon Emission Estimation Framework in Large-Scale AI Models21 May 2024
- 2024Hyperparameter Importance Analysis for Multi-Objective AutoML13 May 2024
- 2024Towards Leveraging AutoML for Sustainable Deep Learning: A Multi-Objective HPO Approach on Deep Shift Neural Networks2 Apr 2024
- 2024An In-Depth Analysis of Data Reduction Methods for Sustainable Deep Learning22 Mar 2024
- 2024Calibrating Large Language Models Using Their Generations Only9 Mar 2024
- 2024Non-Exchangeable Conformal Language Generation with Nearest Neighbors1 Feb 2024
- 2024TeenyTinyLlama: open-source tiny language models trained in Brazilian Portuguese30 Jan 2024
- 2023An Analysis of Embedding Layers and Similarity Scores using Siamese Neural Networks31 Dec 2023
- 2023Tensor-Aware Energy Accounting19 Nov 2023
- 2023An energy-based comparative analysis of common approaches to text classification in the Legal domain2 Nov 2023
- 2023Do Large Language Models have Shared Weaknesses in Medical Question Answering?11 Oct 2023
- 2023Efficient Sentiment Analysis: A Resource-Aware Evaluation of Feature Extraction Techniques, Ensembling, and Deep Learning Models3 Aug 2023
- 2023Broadening the perspective for sustainable AI: Comprehensive sustainability criteria and indicators for AI systems22 Jun 2023
- 2023How to estimate carbon footprint when training deep learning models? A guide and review14 Jun 2023
- 2023Counting Carbon: A Survey of Factors Influencing the Emissions of Machine Learning16 Feb 2023
- 2023Towards energy-efficient Deep Learning: An overview of energy-efficient approaches along the Deep Learning Lifecycle5 Feb 2023
- 2023AI2: The next leap toward native language based and explainable machine learning framework9 Jan 2023
- 2022Exploring Predictive Uncertainty and Calibration in NLP: A Study on the Impact of Method & Data Scarcity20 Oct 2022
- 2022Position: Tensor Networks are a Valuable Asset for Green AI25 May 2022
- 2022Towards Climate Awareness in NLP Research10 May 2022
- 2021Sustainable AI: Environmental Implications, Challenges and Opportunities30 Oct 2021
- 2021Towards Quantifying the Carbon Emissions of Differentially Private Machine Learning14 Jul 2021
- 2021EnergyVis: Interactively Tracking and Exploring Energy Consumption for ML Models30 Mar 2021
- 2021NeurIPS 2020 NLC2CMD Competition: Translating Natural Language to Bash Commands3 Mar 2021
- 2021Sustainable AI: Environmental Implications, Challenges and Opportunitiescited by 242
- 2024Calibrating Large Language Models Using Their Generations Onlycited by 65
- 2023Counting Carbon: A Survey of Factors Influencing the Emissions of Machine Learningcited by 42
- 2023How to estimate carbon footprint when training deep learning models? A guide and reviewcited by 34
- 2022Exploring Predictive Uncertainty and Calibration in NLP: A Study on the Impact of Method & Data Scarcitycited by 25
- 2024Non-Exchangeable Conformal Language Generation with Nearest Neighborscited by 21
- 2022Towards Climate Awareness in NLP Researchcited by 19
- 2023Towards energy-efficient Deep Learning: An overview of energy-efficient approaches along the Deep Learning Lifecyclecited by 14
- 2024TeenyTinyLlama: open-source tiny language models trained in Brazilian Portuguesecited by 13
- 2024Tucano: Advancing Neural Text Generation for Portuguesecited by 13
- 2024Hyperparameter Importance Analysis for Multi-Objective AutoMLcited by 9
- 2021Towards Quantifying the Carbon Emissions of Differentially Private Machine Learningcited by 8
12 most cited of 42 All 42 (JSON)
- 2026Energy Variation in Training Modern Computer Vision Architectures29 Sep 2026
- 2026Greenpixie's AI Token Methodology: Assessing the Energy, Water and CO2-eq Impact of AI Tokens for Open and Closed Weight Models27 Sep 2026
- 2026A Holistic Assessment of the Carbon Footprint of Noor, a Very Large Arabic Language Model22 Sep 2026
- 2026Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint7 Aug 2026
- 2026MLSYSIM: First-Principles Infrastructure Modeling for Machine Learning Systems28 Jun 2026
- 2026Leveraging AutoML for Sustainable Deep Learning: A Multi-Objective HPO Approach on Deep Shift Neural Networks22 Jun 2026
- 2026Classifying by Proxy: Explainable and Reproducible Ensemble of Proxy Tasks for Child Sexual Abuse Imagery Classification14 Jun 2026
- 2026Accounting for AI Inference in Corporate GHG Inventories: A Four-Tier Methodology for Scope 3 Category 1 Reporting9 Jun 2026
- 2026The Environmental Cost of LLMs in AIED: Reporting and Practices3 May 2026
- 2026AI-CARE: Carbon-Aware Reporting Evaluation Metric for AI Models17 Feb 2026
- 2025Benchmarking Energy Efficiency of Large Language Models Using vLLM10 Sep 2025
- 2025SLM-Bench: A Comprehensive Benchmark of Small Language Models on Environmental Impacts--Extended Version21 Aug 2025
12 newest of 42 All 42 (JSON)