Sobre La Teoría de Actor Red y el papel de la IA en el cambio climático
DOI:
https://doi.org/10.31637/epsir-2024-518Palabras clave:
Cambio climático, inteligencia artificial, actante, anti-programa, asociaciones, relaciones de poder, uso intensivoResumen
Introducción: El cambio climático se presenta como el desafío más grande para la humanidad. Metodología: Sin embargo, las nuevas tecnologías, especialmente la inteligencia artificial (IA), ofrecen herramientas fundamentales para comprender este fenómeno y desarrollar mecanismos que permitan mitigarlo, adaptarse a él e incluso combatirlo. Resultados: A pesar de sus beneficios potenciales, la IA también juega un papel significativo al contribuir a los problemas asociados con el cambio climático, tanto en su proceso de entrenamiento, implementación y mantenimiento, como en su notable consumo de recursos como el agua. Discusión y Conclusión: Por ende, este ensayo busca emplear las herramientas y conceptos de la Teoría de la Actor-Red para analizar críticamente el papel de la IA en el cambio climático: cómo su implementación y gobernanza pueden diseñarse para maximizar los beneficios y minimizar los impactos negativos, así como entender cómo actúa como un agente que puede agravar este fenómeno global.
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Blackman, R. (2022). Ethical machines: Your concise guide to totally unbiased, transparent, and respectful AI. Harvard Business Review Press.
Callon, M. (1986). Éléments pour une sociologie de la traduction: La domestication des coquilles Saint-Jacques et des marins-pêcheurs dans la baie de Saint-Brieuc. L’Année sociologique, 36, 169-208.
Changlani, Kishan y Renuka Thakore. Artificial Intelligence for Climate Action. https://doi.org/10.13140/RG.2.2.21102.18245
Chen, L., Chen, Z., Zhang, Y., Liu, Y., Osman, A. I., Farghali, M., Hua, J., Al-Fatesh, A., Ihara, I., Rooney, D. W. y Yap, P. (2023). Artificial intelligence-based solutions for climate change: a review. Environmental Chemistry Letters, 21(5), 2525-2557. https://doi.org/10.1007/s10311-023-01617-y DOI: https://doi.org/10.1007/s10311-023-01617-y
Cowls, J., Tsamados, A., Taddeo, M. y Floridi, L. (2021). The AI gambit: leveraging artificial intelligence to combat climate change—opportunities, challenges, and recommendations. AI & Society, 38(1), 283-307. https://acortar.link/ORJcCh DOI: https://doi.org/10.1007/s00146-021-01294-x
De los Santos, M. D. L., Do, K., Muller, M. y Savage, S. (2024). Designing sousveillance tools for gig workers. https://doi.org/10.1145/3613904.3642614 DOI: https://doi.org/10.1145/3613904.3642614
Dhar, P. (2020). The carbon impact of artificial intelligence. Nature Machine Intelligence, 2(8), 423–425. https://doi.org/10.1038/s42256-020-0219-9 DOI: https://doi.org/10.1038/s42256-020-0219-9
George, A., George, A. y Martin, A. (2023). The Environmental Impact of AI: A case study of water consumption by Chat GPT. Zenodo. CERN European Organization for Nuclear Research. https://doi.org/10.5281/zenodo.7855594
Gonzalo, M. (2023, 7 de septiembre). El impacto climático de la IA y su huella ecológica. Newtral. Newtral. https://acortar.link/rxNv4V
IPCC. (2023). Summary for Policymakers. In: Climate Change 2023: Synthesis Report. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, H. Lee and J. Romero (eds.)]. Geneva, Switzerland: IPCC. https://acortar.link/UC7Jjk
Latour, B. (1990). Technology is Society Made Durable. The Sociological Review, 38(1_suppl), 103-131. https://doi.org/10.1111/j.1467-954X.1990.tb03350.x DOI: https://doi.org/10.1111/j.1467-954X.1990.tb03350.x
Latour, B. (1993). We have never been modern. Harvard University Press.
Latour, B. (2017). On Actor-Network Theory. A few clarifications, plus more than a few complications. Logos, 27(1), 173-197. https://acortar.link/qfCYFJ DOI: https://doi.org/10.22394/0869-5377-2017-1-173-197
Lawie, M. (2023). Analysing the impact of CO2 emissions from the largest artificial intelligence systems and its consequences for global warming. https://doi.org/10.13140/RG.2.2.24138.95680
Li, P., Yang, J., Islam, M. A. y Ren, Sh. (2023). Making AI less «thirsty»: Uncovering and addressing the secret water footprint of AI models. arXiv:2304.03271. http://arxiv.org/abs/2304.03271
Luccioni, A. S. y Hernandez-Garcia, A. (2023). Counting carbon: A survey of factors influencing the emissions of machine learning. arXiv:2302.08476. https://doi.org/10.48550/arXiv.2302.08476
Masterson, V. (12 de febrero de 2024). 9 ways AI is helping tackle climate change. World Economic Forum. https://bit.ly/3W9k9pp
Mohammad, A. y Mahjabeen, F. (2023). Revolutionizing solar energy with AI-driven enhancements in photovoltaic technology. Jurnal Multidisiplin Ilmu, 2. https://journal.mediapublikasi.id/index.php/bullet/article/view/3427 DOI: https://doi.org/10.47709/ijmdsa.v2i1.2599
Olatunde-Aiyedun, T. y Olatunde, M. (2022). State and prediction of the global climate change: 2012-2026.
Quach, K. (4 de noviembre de 2020). AI me to the Moon. Carbon footprint for “training GPT-3” same as driving to our natural satellite and back. The Register. https://bit.ly/3W9wYQL
Raihan, A. (2023). Artificial intelligence and machine learning applications in forest management and biodiversity conservation. Natural Resources Conservation and Research, 6(2), 3825. https://doi.org/10.24294/nrcr.v6i2.3825 DOI: https://doi.org/10.24294/nrcr.v6i2.3825
Rayhan, A. y Rayhan, S. (2023). The role of artificial intelligence in climate change mitigation and adaptation. Artificial Intelligence. https://doi.org/10.13140/RG.2.2.10346.70087/1
Star, S. L. y Griesemer, J. R. (1989). Institutional Ecology, `Translations’ and Boundary Objects: Amateurs and Professionals in Berkeley’s Museum of Vertebrate Zoology, 1907-39. Social Studies of Science, 19(3), 387-420. https://doi.org/10.1177/030631289019003001 DOI: https://doi.org/10.1177/030631289019003001
Taddeo, M. y Floridi, L. (2018). How AI can be a force for good. Science, 361(6404), 751-752. https://doi.org/10.1126/science.aat5991 DOI: https://doi.org/10.1126/science.aat5991
Wong, C. (2024). How climate change is hitting Europe: three graphics reveal health impacts. Nature Climate Change. https://pubmed.ncbi.nlm.nih.gov/38890517/ DOI: https://doi.org/10.1038/d41586-024-02006-3
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