Session 4.2 - Artificial Intelligence In The Archival Domain

Dr. Jenny Bunn, Prof. Moises Rockembach, Prof. Mazzeo Antonino, Prof. Amato Flora, Dr. Campanile Antonio, Dr. Ciampi Mario
Date Added:
21 September 2022

Chair: Maria Guercio

The panel explores the AI technologies, showing how they can support the digitisation of analogue records through innovative massive processes, and identifying the competencies for a critical assessment of the different approaches adopted by AI. The panel investigates the nature of AI in order to face with the hype and encourage archivists and record managers to interact with experts on the basis of both their established methods and newer ones such as linked data and knowledge graphs.


A. Meaning Is Not Maths: Where’s The Intelligence In Artificial Intelligence?

  • Dr. Jenny Bunn, The National Archives, United Kingdom

This paper draws on the author’s own experience and exploration to provide a view under the hood of artificial intelligence (AI). An explanation will be offered of how it works and the question of whether or not that constitutes intelligence will be discussed. As AI becomes the new must-have feature in archives and records management systems and processes, this paper will help you retain your own intelligence and critical faculties when faced with the hype.


B. Artificial Intelligence Literacy In The Context of Archives and Records Management

  • Prof. Moises Rockembach, Universidade Federal do Rio Grande do Sul, Brazil

This work addresses issues involving literacy or competences development in Artificial Intelligence (AI) and its relationship with Records Management and Archival Science. Our goals are to identify competencies for critical assessment of AI; analyze the digital transition scenario and impacts on work environments; identify the challenges that involve the interaction between humans and AI; propose ways of engaging in Records Management and Archival Science solutions based on AI.


C. A new AI and IoT based Massive Digitisation Process

  • Prof. Mazzeo Antonino,
  • Prof. Amato Flora,
  • Dr. Campanile Antonio,
  • Dr. Ciampi Mario3

1Università degli Studi di Napoli Federico II, Dip. Ingegneria Elettrica e delle Tecnologie dell'Informazione,Italy; 2CSA Documents, CSA S.C.p.A. Via della Minerva, 1, 00186 Roma RM; 3Istituto di Calcolo e Reti ad Alte Prestazioni (ICAR), Consiglio Nazionale delle Ricerche (CNR)

Short Description

In this work, the authors propose an innovative massive digitisation process. They implement and use innovative services and AI technologies to guarantee digital copies compliant with the provisions of art. 22 of the Digital Administration Code and automatically extract valuable knowledge from the digitised documents.