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Positioning paradata : A conceptual frame for AI processual documentation in archives and recordkeeping contexts Cameron, Scott; Franks, Pat; Hamidzadeh, Babak
Abstract
The emergence of sophisticated artificial intelligence and machine learning tools poses a challenge to archives and records professionals, who are accustomed to understanding and documenting the activities of human agents rather than the often-opaque processes of sophisticated AI functioning. Preliminary work has proposed the term ‘paradata’ to describe the unique documentation needs which emerge for archivists using AI tools to process records in their collections. For the purposes of archivists working with AI, paradata is here conceptualized as information recorded and preserved about records’ processing with AI tools; it is a category of data which is defined both by its relationship with other datasets and by the documentary purpose which it serves. This paper surveys relevant literatures across three contexts to scope the relevant scholarship which archivists may draw upon to develop appropriate AI documentation practices. From the statistical social sciences and the visual heritage fields, the paper discusses existing definitions of paradata and its ambiguous, often contextually dependent relationship with existing metadata categories. Approaching the problem from a sociotechnical perspective, literature on explainable AI insists pointedly that explainability be attuned to specific users’ stated needs – needs which archivists may better articulate using the framework of paradata. Most importantly, the paper situates AI as a challenge to accountability, transparency, and impartiality in archives by introducing an unfamiliar nonhuman agency, one which pushes the limits of existing archival practice and demands the development of new concepts and vocabularies to shape future technological and methodological developments in archives.
Item Metadata
| Title |
Positioning paradata : A conceptual frame for AI processual documentation in archives and recordkeeping contexts
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| Creator | |
| Publisher |
Association of Computing Machinery
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| Date Issued |
2023-11-16
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| Description |
The emergence of sophisticated artificial intelligence and machine learning tools poses a challenge to archives and records professionals, who are accustomed to understanding and documenting the activities of human agents rather than the often-opaque processes of sophisticated AI functioning. Preliminary work has proposed the term ‘paradata’ to describe the unique documentation needs which emerge for archivists using AI tools to process records in their collections. For the purposes of archivists working with AI, paradata is here conceptualized as information recorded and preserved about records’ processing with AI tools; it is a category of data which is defined both by its relationship with other datasets and by the documentary purpose which it serves. This paper surveys relevant literatures across three contexts to scope the relevant scholarship which archivists may draw upon to develop appropriate AI documentation practices. From the statistical social sciences and the visual heritage fields, the paper discusses existing definitions of paradata and its ambiguous, often contextually dependent relationship with existing metadata categories. Approaching the problem from a sociotechnical perspective, literature on explainable AI insists pointedly that explainability be attuned to specific users’ stated needs – needs which archivists may better articulate using the framework of paradata. Most importantly, the paper situates AI as a challenge to accountability, transparency, and impartiality in archives by introducing an unfamiliar nonhuman agency, one which pushes the limits of existing archival practice and demands the development of new concepts and vocabularies to shape future technological and methodological developments in archives.
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| Subject | |
| Genre | |
| Type | |
| Language |
eng
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| Date Available |
2023-12-08
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| Provider |
Vancouver : University of British Columbia Library
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| Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
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| DOI |
10.14288/1.0438178
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| URI | |
| Affiliation | |
| Citation |
Cameron, S., Franks, P., & Hamidzadeh, B. (2023). Positioning paradata: A conceptual frame for AI processual documentation in archives and recordkeeping contexts. Journal on Computing and Cultural Heritage.
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| Publisher DOI |
10.1145/3594728
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| Peer Review Status |
Unreviewed
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| Scholarly Level |
Faculty; Graduate
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| Rights URI | |
| Aggregated Source Repository |
DSpace
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Rights
Attribution-NonCommercial-NoDerivatives 4.0 International