InterPARES Trust Artificial Inteligence (I Trust AI)

Definition

InterPARES Trust AI 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.

Goals

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
Validate outcomes from Objective 3 through case studies and demonstrations

Chronology

Starting date: 2021
End date: 2026

Working Groups

Creation and Use
Appraisal and Acquisition
Arrangement and Description
Retention and Preservation
Management and Administration
Reference and Access
General Studies

Participants

People and institutions from 30 countries and 5 continents participate in the project. 83 universities, 22 businesses and international organizations, 16 national and regional archives, 118 academics, 102 professionals and 41 students-researchers.

Related activities

Faber-Llull Residence: Artificial Intelligence and Archives. April 24-28
Seminar "Artificial Intelligence and Archives". Girona, April 27

Programme

The InterPARES Trust Artifical Intelligence Project	Muhammad Abdul-Mageed, University of British Columbia
Linking AI to Archives and Records	Peter Sullivan, University of British Columbia
Archival challenges and AI	Hrvoje Stancic, University of Zagreb
Model for an AI-Assisted Digitization Project	Eng Sengsavang, UNESCO Zeljko Trbusic, University of Zagreb Peter Sullivan, University of British Columbia
AI and Archives: Basic Requirements	Pilar Campos, Barcelona City Council
AI literacy for access and archives preservation	Moises Rockembach, KU Leuven
Artificial Intelligence to support public digital archiving	Mashilo Modiba, University of South Africa Ngoako Marutha, University of South Africa
AI and Human Rights Archives	Gerard Corbella, La Foneria
Automated transcription: palaeography and AI	Thiara Alves, National Archives of Brazil Leonardo Augusto Silva Fontes, National Archives of Brazil
First steps and main expectations from CRDI’s experience in AI	David Iglésias, Girona City Council

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