Ensuring Quality in the OECD AI Lifecycle Through ISO/IEC Standards

Autores
Torres, Juan Ignacio; Pasini, Ariel Cristian; Pesado, Patricia Mabel
Año de publicación
2025
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
The integration of artificial intelligence (AI) technologies within organizations presents both significant opportunities and complex challenges. To manage this complexity, ISO/IEC standards provide a structured framework for the adoption and management of AI systems throughout their lifecycle. This article explores the role of ISO/IEC standards in ensuring the quality, security, and ethical alignment of AI systems, based on the lifecycle framework defined by the Organisation for Economic Co-operation and Development (OECD). The paper outlines how these standards support AI system development, from planning and design through deployment and monitoring, addressing critical issues such as governance, data quality, bias detection, and system reliability. A comprehensive quality model is proposed, drawing on ISO/IEC 25058 and 25059 standards, to assess the effectiveness and transparency of AI systems in real-world environments. The adoption of these standards is shown to enhance corporate reputation, improve regulatory compliance, and mitigate risks, positioning organizations to leverage AI technologies responsibly and efficiently.
Instituto de Investigación en Informática
Materia
Ciencias Informáticas
AI Governance
ISO/IEC Standards
AI System Lifecycle
Quality Management
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-nd/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/182612
Acceder
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repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Ensuring Quality in the OECD AI Lifecycle Through ISO/IEC StandardsTorres, Juan IgnacioPasini, Ariel CristianPesado, Patricia MabelCiencias InformáticasAI GovernanceISO/IEC StandardsAI System LifecycleQuality ManagementThe integration of artificial intelligence (AI) technologies within organizations presents both significant opportunities and complex challenges. To manage this complexity, ISO/IEC standards provide a structured framework for the adoption and management of AI systems throughout their lifecycle. This article explores the role of ISO/IEC standards in ensuring the quality, security, and ethical alignment of AI systems, based on the lifecycle framework defined by the Organisation for Economic Co-operation and Development (OECD). The paper outlines how these standards support AI system development, from planning and design through deployment and monitoring, addressing critical issues such as governance, data quality, bias detection, and system reliability. A comprehensive quality model is proposed, drawing on ISO/IEC 25058 and 25059 standards, to assess the effectiveness and transparency of AI systems in real-world environments. The adoption of these standards is shown to enhance corporate reputation, improve regulatory compliance, and mitigate risks, positioning organizations to leverage AI technologies responsibly and efficiently.Instituto de Investigación en Informática2025-06info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf90-95http://sedici.unlp.edu.ar/handle/10915/182612enginfo:eu-repo/semantics/altIdentifier/isbn/978-950-34-2583-1info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-nd/4.0/Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:49:52Zoai:sedici.unlp.edu.ar:10915/182612Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:49:53.036SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Ensuring Quality in the OECD AI Lifecycle Through ISO/IEC Standards
title Ensuring Quality in the OECD AI Lifecycle Through ISO/IEC Standards
spellingShingle Ensuring Quality in the OECD AI Lifecycle Through ISO/IEC Standards
Torres, Juan Ignacio
Ciencias Informáticas
AI Governance
ISO/IEC Standards
AI System Lifecycle
Quality Management
title_short Ensuring Quality in the OECD AI Lifecycle Through ISO/IEC Standards
title_full Ensuring Quality in the OECD AI Lifecycle Through ISO/IEC Standards
title_fullStr Ensuring Quality in the OECD AI Lifecycle Through ISO/IEC Standards
title_full_unstemmed Ensuring Quality in the OECD AI Lifecycle Through ISO/IEC Standards
title_sort Ensuring Quality in the OECD AI Lifecycle Through ISO/IEC Standards
dc.creator.none.fl_str_mv Torres, Juan Ignacio
Pasini, Ariel Cristian
Pesado, Patricia Mabel
author Torres, Juan Ignacio
author_facet Torres, Juan Ignacio
Pasini, Ariel Cristian
Pesado, Patricia Mabel
author_role author
author2 Pasini, Ariel Cristian
Pesado, Patricia Mabel
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
AI Governance
ISO/IEC Standards
AI System Lifecycle
Quality Management
topic Ciencias Informáticas
AI Governance
ISO/IEC Standards
AI System Lifecycle
Quality Management
dc.description.none.fl_txt_mv The integration of artificial intelligence (AI) technologies within organizations presents both significant opportunities and complex challenges. To manage this complexity, ISO/IEC standards provide a structured framework for the adoption and management of AI systems throughout their lifecycle. This article explores the role of ISO/IEC standards in ensuring the quality, security, and ethical alignment of AI systems, based on the lifecycle framework defined by the Organisation for Economic Co-operation and Development (OECD). The paper outlines how these standards support AI system development, from planning and design through deployment and monitoring, addressing critical issues such as governance, data quality, bias detection, and system reliability. A comprehensive quality model is proposed, drawing on ISO/IEC 25058 and 25059 standards, to assess the effectiveness and transparency of AI systems in real-world environments. The adoption of these standards is shown to enhance corporate reputation, improve regulatory compliance, and mitigate risks, positioning organizations to leverage AI technologies responsibly and efficiently.
Instituto de Investigación en Informática
description The integration of artificial intelligence (AI) technologies within organizations presents both significant opportunities and complex challenges. To manage this complexity, ISO/IEC standards provide a structured framework for the adoption and management of AI systems throughout their lifecycle. This article explores the role of ISO/IEC standards in ensuring the quality, security, and ethical alignment of AI systems, based on the lifecycle framework defined by the Organisation for Economic Co-operation and Development (OECD). The paper outlines how these standards support AI system development, from planning and design through deployment and monitoring, addressing critical issues such as governance, data quality, bias detection, and system reliability. A comprehensive quality model is proposed, drawing on ISO/IEC 25058 and 25059 standards, to assess the effectiveness and transparency of AI systems in real-world environments. The adoption of these standards is shown to enhance corporate reputation, improve regulatory compliance, and mitigate risks, positioning organizations to leverage AI technologies responsibly and efficiently.
publishDate 2025
dc.date.none.fl_str_mv 2025-06
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info:eu-repo/semantics/publishedVersion
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info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/182612
url http://sedici.unlp.edu.ar/handle/10915/182612
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/isbn/978-950-34-2583-1
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-nd/4.0/
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
dc.format.none.fl_str_mv application/pdf
90-95
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
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reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
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