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...
Guardado en:
| Autores principales: | , , , |
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| Formato: | Artículo revista |
| Lenguaje: | Español |
| Publicado: |
Facultad de Filosofía y Humanidades. Escuela de Archivología
2022
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| Acceso en línea: | https://revistas.unc.edu.ar/index.php/anuario/article/view/37898 |
| Aporte de: |
| Sumario: | 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 |
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