Green algorithms and environmental justice. An analysis from ethics and law
DOI:
https://doi.org/10.46661/lexsocial.12830Keywords:
green algorithm, algorithmics, AI, digital society, environmental justice and sustainabilityAbstract
This article analyzes, from an ethical and legal perspective, the environmental impact of AI and algorithmic systems in contemporary digital society. Contrary to the purely instrumental view of green algorithms as technical efficiency solutions, it argues that they represent normative criteria of environmental justice.
The ecological footprint of AI -energy, water and mineral consumption- is examined, along with the shortcomings of the current regulatory framework, which focuses on the protection of fundamental rights, democracy and health, but makes no reference to its ecological impact. Furthermore, the article proposes expanding the principles of fairness to include environmental sustainability, integrating distributive justice in its spatial and temporal (intergenerational) dimensions. The work aims to lay the foundation for an ecological transition. The goal is to move toward a social, democratic, digital and eco-sustainable state, where environmental justice is a precondition for social justice.
Downloads
References
Aristóteles, Ética a Nicómaco, (2012), Alianza editorial, Madrid.
Beauchamp, T. y Childress, J., (1979), Principios de Ética biomédica (Oxford University Press, New York City).
Coeckelbergh, M., (2021), Ética de la Inteligencia Artificial, Cátedra, Madrid.
Cotino Hueso, L., "Transparencia y explicabilidad de la Inteligencia Artificial y compañía (comunicación, interpretabilidad, inteligibilidad auditabilidad, testabilidad, comprobabilidad y simulabilidad…) Para qué, para quién y cuánta". En Cotino Hueso, L. y Castellanos Claramunt, J., (Ed.) (2022), Transparencia y explicabilidad de la Inteligencia Artificial, Tirant lo Blanch, Valencia.
Diéguez, A., (2024), Pensar la tecnología. Una guía para comprender filosóficamente el desarrollo de la tecnología actual, Shackleton Books, España.
Etxebarría, J. y Almendros, L. (2023), Tecnopersonas. Cómo las tecnologías nos transforman. 2ª edición, Gijón, Trea Ensayo.
Floridi, L., et. al., (2018), AI4People's Ethical Framework for a Good AI Society: Opportunities, Risks, Principles and Recommendations, https://doi.org/10.1007/s11023-018-9482-5
Floridi, L. & Cowls, J, (2019), "A Unified Framework of Five Principles for AI in Society", Harvard Data Science Review. https://hdsr.mitpress.mit.edu/pub/l0jsh9d1/release/8 https://doi.org/10.1162/99608f92.8cd550d1
Gupta, U. et al. (2020), "Chasing Carbon: The Elusive Environmental Footprint of Computing", 28 Oct, arXiv:2011.02839 https://doi.org/10.1109/HPCA51647.2021.00076
Hansen, M. H. (2022), La democracia ateniense en la época de Demóstenes, Capitán Swing, Madrid, (primera edición en inglés: 1991).
Hajiesmaili, M, Ren, S., Sitaramen, R. K., Wierman, A. (2024), "Towards Environmentally Equitable AI", 21 Dec., https://arxiv.org/pdf/2412.16539
Istrate, R. et. Al. (2024), "The environmental sustainability of digital content consumption", Nature Communications. https://www.nature.com/articles/s41467-024-47621-w
Lacoste, A., Luccioni, A., Schmidt, V. y Dandres, T., (2019), "Quantifying the carbon emissions of machine learning", 4 Nov. https://arxiv.org/abs/1910.09700
Lanneloungue, L., Grealey, J. and Inouye, M. (2021), "Green Algorithms: Quantifying the carbon footprint of computation". https://doi.org/10.1002/advs.202100707
Mitchell, S., Potash, E., Barocas, S., D'Amour, A. & Lum, C., (2020), "Prediction-Based Decision and Fairness: A Catalogue of Choises, Assumptions and Definitions", April. https://arxiv.org/pdf/1811.07867
Moffatt, I., (2000), "Ecological footprints and sustainable development", Ecological Economics 32, Elsevier. https://staff.washington.edu/jhannah/geog270aut07/readings/population/Moffatt%20-%20Ecolog%20Footprint%20and%20Sustain%20Dev.pdf
Ortega y Gasset, J., (1965), Meditaciones de la técnica, Austral, Madrid, 1965.
Pasquale, F. (2015), Black Box Society, Harvard University Press, Cambridge, p. 10/320 (versión online en abierto: https://tetrazolelover.at.ua/Frank_Pasquale-The_Black_Box_Society-The_Secret_Al.pdf) https://doi.org/10.4159/harvard.9780674736061
Presno Linera, M. A. (2022), Derechos fundamentales e inteligencia artificial, Marcial Pons, Madrid. https://doi.org/10.2307/jj.4908196
Rawls, J., (1971), Teoría de la justicia, Harvard University Press, Cambridge.
Rawls, J., (2002), La justicia como equidad, Paidós, Barcelona.
Redclift, M. (2005), "Sustainable Development (1987-2005). An Oxymoron Comes of Age", Sustainable Development 13. https://www.homepages.ucl.ac.uk/~ucessjb/S3%20Reading/redclift%202005.pdf https://doi.org/10.1002/sd.281
Ren, S. et. al. (2025), "Making IA Less Thirsty: Uncovering and Addressing the Secret Water Footprint of AI Models", 26 Mar, arXiv:2304.03271
Riechmann, J. (2003), "Tres principios básicos de justicia ambiental", Revista Internacional de Filosofía Política, 21, p. 103-120. https://oai.e-spacio.uned.es/server/api/core/bitstreams/0d376386-edc6-47df-9398-a00133a565b1/content
Véliz, C., (2019), "Three things digital ethics can learn from medical ethics", Nature Electronics, 15 August 2019, https://philpapers.org/archive/VLITTD.pdf https://doi.org/10.1038/s41928-019-0294-2
Vieira De Feitas Neto, S. V., Falcao Sobral, M. F., Becerra Riveiro, A. R., Da luz Soares, G. R. (2020), "Concepts and Forms of greenwashing: a systematic review, Environmental Science Europe", Environmental Science Europe, 32:19. https://enveurope.springeropen.com/articles/10.1186/s12302-020-0300-3 https://doi.org/10.1186/s12302-020-0300-3
Yanofsky, Noson, S. (2024), "Towards a Definition of an Algorithm", Journal of Logic and Computation, 21(2), https://arxiv.org/pdf/math/0602053 https://eur-lex.europa.eu/resource.html?uri=cellar:b828d165-1c22-11ea-8c1f-01aa75ed71a1.0004.02/DOC_1&format=PDF
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Vanesa Morente Parra
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
-
Atribución — Usted debe dar crédito de manera adecuada, brindar un enlace a la licencia, e indicar si se han realizado cambios. Puede hacerlo en cualquier forma razonable, pero no de forma tal que sugiera que usted o su uso tienen el apoyo de la licenciante.
-
NoComercial — Usted no puede hacer uso del material con propósitos comerciales.
-
CompartirIgual — Si remezcla, transforma o crea a partir del material, deberá difundir sus contribuciones bajo la misma licencia que el original.
@Lex Social
Linkedin
@lexrevista.bsky.social
