Research Associate at the School of Fine Art, History of Art and Cultural Studies, University of Leeds. Currently working on the Congruence Engine project with the Science Museum Group.
My research intersects with digital cultural heritage, museum studies, collections management and online remix cultures. I am interested in action-focused, collaborative and autoethnographic research methodologies and exploring the use of humour in academic form.
This article explores collaborative conversation as a method to surface multiple perspectives on ... more This article explores collaborative conversation as a method to surface multiple perspectives on community engagement and forms of knowledge creation in the Congruence Engine project. Our exchanges naturally converged around four main areas: the multiple meanings of the term 'community' and the nature of these relationships; the modes and spaces for engagement; the different nature of knowledge emerging from these interactions; and, finally, a series of practical issues and challenges that can act as potential barriers. The article also reflects on the opportunities of dialogic writing to enable participatory, inclusive and polyvocal approaches in the development of a national collection.
Connect to Collect - Approaches to Collecting Social Digital Photography in Museums and Archives. , 2020
Recommendations for museums and archives collecting social digital photography. Appendix to publi... more Recommendations for museums and archives collecting social digital photography. Appendix to publication Connect to Collect - Approaches to Collecting Social Digital Photography in Museums and Archives.
Connect to collect: approaches to collecting social digital photography in museums and archives, 2020
Artificial intelligence (AI) has made huge leaps forward over the past decade, and the developmen... more Artificial intelligence (AI) has made huge leaps forward over the past decade, and the developments in machine learning in particular have led to increasingly sophisticated image recognition tools. A growing number of industries are moving towards using AI to undertake a variety of different tasks, and the cultural sector is not exempt from this. Agrawal et al. question the role of AI in the workforce, asking whether it will move towards substituting or complementing humans in specific roles (2019, 2). This was a question posed at the beginning of this image recognition testing project – can AI catalogue photographs as they are collected by museum and archive institutions? Other questions included: the compatibility of museum/archives-controlled vocabularies and the words used by image recognition tools; and the ability of AI to understand context and sensitive situations.
Policy makers produce digital records on a daily basis. A selection of records is then preserved ... more Policy makers produce digital records on a daily basis. A selection of records is then preserved in archival repositories. However, getting access to these archival materials is extremely complicated for many reasons-including data protection, sensitivity, national security, and copyright. Artificial Intelligence (AI) can be applied to archives to make them more accessible, but it is still at an experimental stage. While skills gaps contribute to keeping archives 'dark', it is also essential to examine issues of mistrust and miscommunication. This article argues that although civil servants, archivists, and academics have similar professional principles articulated through professional codes of ethics, these are not often communicated to each other. This lack of communication leads to feelings of mistrust between stakeholders. Mistrust of technology also contributes to the barriers to effective implementation of AI tools. Therefore, we propose that surfacing the shared professional ethics between stakeholders can contribute to deeper collaborations between humans. In turn, these collaborations can lead to the building of trust in AI systems and tools. The research is informed by semi-structured interviews with thirty government professionals, archivists, historians, digital humanists, and computer scientists. Previous research has largely focused on preservation of digital records, rather than access to these records, and on archivists rather than records creators such as government professionals. This article is the first to examine the application of AI to digital archives as an issue that requires trust and collaboration across the entire archival circle (from record creators to archivists, and from archivists to users).
This article explores collaborative conversation as a method to surface multiple perspectives on ... more This article explores collaborative conversation as a method to surface multiple perspectives on community engagement and forms of knowledge creation in the Congruence Engine project. Our exchanges naturally converged around four main areas: the multiple meanings of the term 'community' and the nature of these relationships; the modes and spaces for engagement; the different nature of knowledge emerging from these interactions; and, finally, a series of practical issues and challenges that can act as potential barriers. The article also reflects on the opportunities of dialogic writing to enable participatory, inclusive and polyvocal approaches in the development of a national collection.
Connect to Collect - Approaches to Collecting Social Digital Photography in Museums and Archives. , 2020
Recommendations for museums and archives collecting social digital photography. Appendix to publi... more Recommendations for museums and archives collecting social digital photography. Appendix to publication Connect to Collect - Approaches to Collecting Social Digital Photography in Museums and Archives.
Connect to collect: approaches to collecting social digital photography in museums and archives, 2020
Artificial intelligence (AI) has made huge leaps forward over the past decade, and the developmen... more Artificial intelligence (AI) has made huge leaps forward over the past decade, and the developments in machine learning in particular have led to increasingly sophisticated image recognition tools. A growing number of industries are moving towards using AI to undertake a variety of different tasks, and the cultural sector is not exempt from this. Agrawal et al. question the role of AI in the workforce, asking whether it will move towards substituting or complementing humans in specific roles (2019, 2). This was a question posed at the beginning of this image recognition testing project – can AI catalogue photographs as they are collected by museum and archive institutions? Other questions included: the compatibility of museum/archives-controlled vocabularies and the words used by image recognition tools; and the ability of AI to understand context and sensitive situations.
Policy makers produce digital records on a daily basis. A selection of records is then preserved ... more Policy makers produce digital records on a daily basis. A selection of records is then preserved in archival repositories. However, getting access to these archival materials is extremely complicated for many reasons-including data protection, sensitivity, national security, and copyright. Artificial Intelligence (AI) can be applied to archives to make them more accessible, but it is still at an experimental stage. While skills gaps contribute to keeping archives 'dark', it is also essential to examine issues of mistrust and miscommunication. This article argues that although civil servants, archivists, and academics have similar professional principles articulated through professional codes of ethics, these are not often communicated to each other. This lack of communication leads to feelings of mistrust between stakeholders. Mistrust of technology also contributes to the barriers to effective implementation of AI tools. Therefore, we propose that surfacing the shared professional ethics between stakeholders can contribute to deeper collaborations between humans. In turn, these collaborations can lead to the building of trust in AI systems and tools. The research is informed by semi-structured interviews with thirty government professionals, archivists, historians, digital humanists, and computer scientists. Previous research has largely focused on preservation of digital records, rather than access to these records, and on archivists rather than records creators such as government professionals. This article is the first to examine the application of AI to digital archives as an issue that requires trust and collaboration across the entire archival circle (from record creators to archivists, and from archivists to users).
Uploads
Papers by Arran J Rees
Articles by Arran J Rees