I Trust AI, the latest InterPARES research project

The new InterPARES project, I Trust AI, is addressed to design, develop, and leverage AI to support the ongoing availability and accessibility of trustworthy public records by forming a sustainable, ongoing Partnership producing original research, training students and other highly qualified personn...

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Autores principales: Duranti, Luciana, Abdul-Mageed, Muhammad, Hofman, Darra, Sullivan, Peter
Formato: Artículo revista
Lenguaje:Español
Publicado: Facultad de Filosofía y Humanidades. Escuela de Archivología 2022
Acceso en línea:https://revistas.unc.edu.ar/index.php/anuario/article/view/37898
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spelling I10-R345-article-378982022-06-09T03:37:08Z I Trust AI, the latest InterPARES research project I Trust AI, el Nuevo Proyecto de investigación de InterPARES Duranti, Luciana Abdul-Mageed, Muhammad Hofman, Darra Sullivan, Peter The new InterPARES project, I Trust AI, is addressed to design, develop, and leverage AI to support the ongoing availability and accessibility of trustworthy public records by forming a sustainable, ongoing Partnership producing original research, training students and other highly qualified personnel (HQP), generating a virtuous circle between academia, archival institutions, government records professionals, and industry. With about 200 participants and 87 partners, the approach is fully interdisciplinary in order to support the comprehensive examination of the administrative, archival, technological, ethical, legal, and social dimensions of implementing AI to control and provide access to trustworthy public records. The challenge facing with this project has never before been systematically and globally dealt with. However, while the risks of using AI to solve the problems of managing the ever-growing of public records throughout their lifecycle are unknown, the risks of not acting in concert to do so are unacceptable: loss of the ability to secure people’s rights; of evidence as a foundation for decision making; and of historical memory. That is the reason why the project is extremely significant to government agencies and archives, to AI specialists, and to universities educating the records and archival professionals and the AI experts of the future.   Keywords: Artificial Intelligence and Archives, Machine Learning and Archives, Technologies and Archives El nuevo proyecto InterPARES, I Trust AI, tiene por objetivo diseñar, desarrollar y aprovechar la IA para respaldar la disponibilidad y accesibilidad continuas de documentos públicos confiables mediante la formación de una colaboración sostenible y continua que produzca investigaciones originales, capacite a estudiantes y otro personal altamente calificado, generando un círculo virtuoso entre la academia, las instituciones archivísticas, los profesionales de documentos gubernamentales y la industria. Con alrededor de 200 participantes y 87 socios, el enfoque es completamente interdisciplinario para respaldar el examen integral de las dimensiones administrativas, de archivo, tecnológicas, éticas, legales y sociales de la implementación de IA en el control y acceso a documentos públicos confiables. El desafío al que se enfrenta este proyecto nunca antes había sido abordado de manera sistemática y global. No obstante, y si bien se desconocen los riesgos de usar la IA para resolver los problemas de administrar el incesante crecimiento de los documentos públicos a lo largo de su ciclo de vida, los riesgos de no actuar de manera concertada para hacerlo son inaceptables: pérdida de la capacidad de garantizar los derechos de las personas; de la evidencia como base para la toma de decisiones; y de la memoria histórica. Esa es la razón por la cual el proyecto es extremadamente importante para las agencias gubernamentales y los archivos, para los especialistas en IA y para las universidades que educan a los profesionales de archivos y a los expertos en IA del futuro.   Palabras clave: Inteligencia Artificial y Archivos, Machine Learning y Archivos, Tecnologías y Archivos Facultad de Filosofía y Humanidades. Escuela de Archivología 2022-06-09 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://revistas.unc.edu.ar/index.php/anuario/article/view/37898 Anuario Escuela de Archivología; Núm. 13 (2021): Anuario Escuela de Archivología; 36-55 1852-6446 1853-3949 spa https://revistas.unc.edu.ar/index.php/anuario/article/view/37898/37827 Derechos de autor 2022 Esta obra está bajo una Licencia Creative Commons Atribución – No Comercial – Sin Obra Derivada 4.0 Internacional. https://creativecommons.org/licenses/by-nc-nd/4.0/
institution Universidad Nacional de Córdoba
institution_str I-10
repository_str R-345
container_title_str Anuario Escuela de Archivología
language Español
format Artículo revista
author Duranti, Luciana
Abdul-Mageed, Muhammad
Hofman, Darra
Sullivan, Peter
spellingShingle Duranti, Luciana
Abdul-Mageed, Muhammad
Hofman, Darra
Sullivan, Peter
I Trust AI, the latest InterPARES research project
author_facet Duranti, Luciana
Abdul-Mageed, Muhammad
Hofman, Darra
Sullivan, Peter
author_sort Duranti, Luciana
title I Trust AI, the latest InterPARES research project
title_short I Trust AI, the latest InterPARES research project
title_full I Trust AI, the latest InterPARES research project
title_fullStr I Trust AI, the latest InterPARES research project
title_full_unstemmed I Trust AI, the latest InterPARES research project
title_sort i trust ai, the latest interpares research project
description The new InterPARES project, I Trust AI, is addressed to design, develop, and leverage AI to support the ongoing availability and accessibility of trustworthy public records by forming a sustainable, ongoing Partnership producing original research, training students and other highly qualified personnel (HQP), generating a virtuous circle between academia, archival institutions, government records professionals, and industry. With about 200 participants and 87 partners, the approach is fully interdisciplinary in order to support the comprehensive examination of the administrative, archival, technological, ethical, legal, and social dimensions of implementing AI to control and provide access to trustworthy public records. The challenge facing with this project has never before been systematically and globally dealt with. However, while the risks of using AI to solve the problems of managing the ever-growing of public records throughout their lifecycle are unknown, the risks of not acting in concert to do so are unacceptable: loss of the ability to secure people’s rights; of evidence as a foundation for decision making; and of historical memory. That is the reason why the project is extremely significant to government agencies and archives, to AI specialists, and to universities educating the records and archival professionals and the AI experts of the future.   Keywords: Artificial Intelligence and Archives, Machine Learning and Archives, Technologies and Archives
publisher Facultad de Filosofía y Humanidades. Escuela de Archivología
publishDate 2022
url https://revistas.unc.edu.ar/index.php/anuario/article/view/37898
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