InterPARES Trust AI
InterPARES Trust AI (2021-2026) is a multi-national interdisciplinary project aiming to design, develop, and leverage Artificial Intelligence 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), and generating a virtuous circle between academia, archival institutions, government records professionals, and industry, a feedback loop reinforcing the knowledge and capabilities of each party.
The project is coordinated by the School of Information, University of British Columbia. Principal investigator is prof. Luciana Duranti who co-directs the project with ass. prof. Muhammad Abdul-Mageed. The Department of ALM is participating in the project as a partner with prof. Isto Huvila as a co-applicant.
The I Trust AI goals are to:
- Identify specific AI technologies that can address critical records and archives challenges;
- Determine the benefits and risks of using AI technologies on records and archives;
- Ensure that archival concepts and principles inform the development of responsible AI; and
- Validate outcomes from Objective 3 through case studies and demonstrations.