A review of green artificial intelligence: Towards a more sustainable future

UDC.coleccionInvestigaciónes_ES
UDC.departamentoCiencias da Computación e Tecnoloxías da Informaciónes_ES
UDC.grupoInvLaboratorio de Investigación e Desenvolvemento en Intelixencia Artificial (LIDIA)es_ES
UDC.journalTitleNeurocomputinges_ES
UDC.startPage128096es_ES
UDC.volume599es_ES
dc.contributor.authorBolón-Canedo, Verónica
dc.contributor.authorMorán-Fernández, Laura
dc.contributor.authorCancela, Brais
dc.contributor.authorAlonso-Betanzos, Amparo
dc.date.accessioned2024-07-10T11:39:23Z
dc.date.available2024-07-10T11:39:23Z
dc.date.issued2024-09-28
dc.descriptionFinanciado para publicación en acceso aberto: Universidade da Coruña/CISUGes_ES
dc.description.abstract[Abstract]: Green artificial intelligence (AI) is more environmentally friendly and inclusive than conventional AI, as it not only produces accurate results without increasing the computational cost but also ensures that any researcher with a laptop can perform high-quality research without the need for costly cloud servers. This paper discusses green AI as a pivotal approach to enhancing the environmental sustainability of AI systems. Described are AI solutions for eco-friendly practices in other fields (green-by AI), strategies for designing energy-efficient machine learning (ML) algorithms and models (green-in AI), and tools for accurately measuring and optimizing energy consumption. Also examined are the role of regulations in promoting green AI and future directions for sustainable ML. Underscored is the importance of aligning AI practices with environmental considerations, fostering a more eco-conscious and energy-efficient future for AI systems.es_ES
dc.description.sponsorshipThis work was supported by CITIC, a Research Center accredited by Galician University System, which is funded by "Consellería de Cultura, Educación e Universidade from Xunta de Galicia", supported in an 80% through ERDF Funds, ERDF Operational Programme Galicia 2014-2020, and the remaining 20% by "Secretaría Xeral de Universidades" (Grant ED431G 2019/01). It was also partially funded by Xunta de Galicia/FEDER-UE under Grant ED431C 2022/44; Ministerio de Ciencia e Innovación MCIN/AEI/10.13039/501100011033 and "NextGenerationEU"/PRTR under Grants [PID2019-109238GB-C22; PID2021-128045OA-I00; ED2021-130599A-I00] and Ministry for Digital Transformation and Civil Service under grant TSI-100925-2023-1. Funding for open access charge: Universidade da Coruña/CISUGes_ES
dc.description.sponsorshipXunta de Galicia; ED431G 2019/01es_ES
dc.description.sponsorshipXunta de Galicia; ED431C 2022/44es_ES
dc.identifier.citationV. Bolón-Canedo, L. Morán-Fernández, B. Cancela, and A. Alonso-Betanzos, "A review of green artificial intelligence: Towards a more sustainable future", Neurocomputing, Vol. 599, 128096, 28 Sept. 2024, doi: 10.1016/j.neucom.2024.128096es_ES
dc.identifier.doi10.1016/j.neucom.2024.128096
dc.identifier.issn0925-2312
dc.identifier.urihttp://hdl.handle.net/2183/37880
dc.language.isoenges_ES
dc.publisherElsevier B.V.es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-109238GB-C22/ES/APRENDIZAJE AUTOMATICO ESCALABLE Y EXPLICABLEes_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-128045OA-I00/ES/APRENDIZAJE PROFUNDO ETICOes_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/TED2021-130599A-I00/ES/ALGORITMOS DE SELECCIÓN DE CARACTERÍSTICAS VERDES Y RÁPIDOSes_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/TSI-100925-2023-1/ES/CÁTEDRA UDC-INDITEX DE INTELIGENCIA ARTIFICIAL EN ALGORITMOS VERDESes_ES
dc.relation.urihttps://doi.org/10.1016/j.neucom.2024.128096es_ES
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 Españaes_ES
dc.rights.accessRightsopen accesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subjectGreen machine learninges_ES
dc.subjectGreen-by AIes_ES
dc.subjectGreen-in AIes_ES
dc.subjectSustainabilityes_ES
dc.titleA review of green artificial intelligence: Towards a more sustainable futurees_ES
dc.typejournal articlees_ES
dspace.entity.typePublication
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