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

  1. Identify specific AI technologies that can address critical records and archives challenges
  2. Determine the benefits and risks of using AI technologies on records and archives
  3. Ensure that archival concepts and principles inform the development of responsible AI
  4. 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

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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