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 I Trust AI goals are to:

  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; and
  4. Validate outcomes from Objective 3 through case studies and demonstrations.

Recent Activity

CTV News - CTV Vancouver Your Morning June 5 interview with Dr. Muhammad Abdul-Mageed to discuss the Government of Canada’s newly announced National Artificial Intelligence Strategy: AI for All, released June 4.

RP04: Preserving AI Techniques as Paradata - Final Report. Scott Cameron, Patricia C Franks (lead), Kaila Fewster, Isto Huvila, Norman Mooradian. March 30, 2026.

Module 5: AI/ML for Processing Audiovisual Records in Archives. Teachable AI for the Archival Professions, AD01 - DRAFT. Nataliya Radke and Richard Arias-Hernandez. March 2026.

CU05 The role of AI for records management: findings from case studies - Final Report. Stefano Allegrezza, Gabriele Bezzi, Maria Mata Caravaca, Massimiliano Grandi, Mariella Guercio, Bruna La Sorda, Francesca Magnoni, Marianna Tascone. Febuary 2026.

Potter, A. - Andrew Potter. "Algorithms, Archives, and the Layers We Usually Forget: Why algorithm preservation needs to come off the back burner." Metaarchivist-Substack. November 18, 2025.

Suderman, J.|Rivard, N.|Khuhro, I.|Gilmore, E.|Barbeau, M.|Hofman, D.|Simard, F.|Beauchamp, M. - Operationalizing Context: Contextual Integrity, Archival Diplomatics, and Knowledge Graphs, 10th Computational Archival Science workshop, part of: 2025 IEEE Big Data Conference (IEEE BigData 2025)

Feliciati, P. - "Archival functions and responsible AI from the perspective of InterPARES: approach, research lines and results." Workshop 2025: Artificial Intelligence in the Papers: Reflections and Perspectives, Anai – Piedmont and Valle d'Aosta. Torino. November 19, 2025.

Module 4: AI/ML for Processing Image-based Records in Archives. Teachable AI for the Archival Professions, AD01 - DRAFT. Kaila Fewster and Richard Arias-Hernandez. September 2025.

Huvila, I.|Sköld, O.|Andersson, L.|Friberg, Z.|Liu, Y-H. - Paradata: Documenting Data Creation, Curation, and Use. Cambridge University Press. 2025.

CU09 Artificial Intelligence, Warfare, and Evidence in International Contexts: A Select Annotated Bibliography. Patrick McGee, Archival Technologies Lab, City University of New York. For the Creation and Use Working Group, InterPARES Trust AI. March 2025.