October 20, 2022 Journal article Open Access

Cushing, Amber L.; Osti, Giulia

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  <identifier identifierType="URL">https://zenodo.org/record/7232001</identifier>
  <creators>
    <creator>
      <creatorName>Cushing, Amber L.</creatorName>
      <givenName>Amber L.</givenName>
      <familyName>Cushing</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0003-0186-0689</nameIdentifier>
      <affiliation>University College Dublin</affiliation>
    </creator>
    <creator>
      <creatorName>Osti, Giulia</creatorName>
      <givenName>Giulia</givenName>
      <familyName>Osti</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0003-3179-6980</nameIdentifier>
      <affiliation>University College Dublin</affiliation>
    </creator>
  </creators>
  <titles>
    <title>"So how do we balance all of these needs?": how the concept of AI technology impacts digital archival expertise</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2022</publicationYear>
  <subjects>
    <subject>Focus Groups</subject>
    <subject>Qualitative</subject>
    <subject>Archives</subject>
    <subject>Digital Preservation</subject>
    <subject>Template Analysis</subject>
    <subject>Artificial Intelligence (AI)</subject>
  </subjects>
  <dates>
    <date dateType="Issued">2022-10-20</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="JournalArticle"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/7232001</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1108/JD-08-2022-0170</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;&lt;strong&gt;Purpose&lt;/strong&gt;&lt;br&gt;
This study explores the implementation of Artificial Intelligence (AI) in archival practice by presenting the thoughts and opinions of working archival practitioners. It contributes to the extant literature with a fresh perspective, expanding the discussion on AI adoption by investigating how it influences the perceptions of digital archival expertise.&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;Design/methodology/approach&lt;/strong&gt;&lt;br&gt;
A two-phase data collection consisting of four online focus groups was held to gather the opinions of international archives and digital preservation professionals (n=16), that participated on a volunteer basis. The qualitative analysis of the transcripts was performed using template analysis, a style of thematic analysis.&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;Findings&lt;/strong&gt;&lt;br&gt;
Four main themes were identified: fitting AI into day to day practice; the responsible use of (AI) technology; managing expectations (about AI adoption) and bias associated with the use of AI. The analysis suggests that AI adoption combined with hindsight about digitisation as a disruptive technology might provide archival practitioners with a framework for re-defining, advocating and outlining digital archival expertise.&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;Research limitations/implications&lt;/strong&gt;&lt;br&gt;
The volunteer basis of this study meant that the sample was not representative or generalisable.&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;Originality/value&lt;/strong&gt;&lt;br&gt;
Although the results of this research are not generalisable, they shed light on the challenges prospected by the implementation of AI in the archives and for the digital curation professionals dealing with this change. The evolution of the characterisation of digital archival expertise is a topic reserved for future research.&lt;/p&gt;</description>
    <description descriptionType="Other">Pre-print version. This work was conducted with the financial support of the Science Foundation Ireland Centre for Research Training in Digitally-Enhanced Reality (d-real) under Grant No. 18/CRT/6224.

The authors would also like to thank Stephen Howell of Microsoft Ireland for his support with using
Microsoft Azure to request tags and descriptions for the phase one focus group prompts.
In addition, the authors would like to thank the following students who assisted with data collection
in the study: Rachael Agnew, MacKenzie Barry, Nancy Bruseker, Sinead Carey, Emma, Carroll, Lauren
Caravati, Na Chen, Caroline Crowther, Aoife Cummins Georghiou, Marc Dagohoy, Desree Efamaui,
Haichuan Feng, Laura Finucane, Nathan Fitzmaurice, Conor Greene, Yazhou He, Yuhan Jiang, Joang,
Zhou, Grainne Kavanagh, Kate Keane, Mark Keleghan, Miao Li, Danyang Liu, Xijia Liu, Siqi Liu,
Hannah Lynch, Conor Murphy, Niamh Elizabeth Murphy, Rebecca Murphy, Kyanna Murray, Kayse
Nation, Blaithin NiChathain, Roisin O'Brien, Niall O'Flynn, Abigail Raebig, Bernadette Ryan, Emma
Rothwell, John Francis Sharpe, Lin Shuhua, Zhongqian Wang, Robin Wharton, Zhillin Wei, India Wood,
Bingye Wu, Deyan Zhang, Zhongwen Zheng and Zheyuan Zhang.</description>
  </descriptions>
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