Maturity Assessment of Appraisal Processes in the AI Age: Ongoing Framework and Measuring Method

The increasing volume of generated data and archives raises pertinent questions regarding the effectiveness of traditional archival appraisal methods, which largely depend on human expertise. As automation and artificial intelligence (AI) become prevalent in various sectors, the field of archiving stands on the brink of significant transformation.This paper explores the integration of AI within archival appraisal processes, framed within the context of the Maturity Assessment for Appraisal (MAA) project (2023-2025). The MAA seeks to evaluate the defensibility, stability, and appropriateness of current appraisal practices while assessing the readiness of records for automated appraisal. Employing exploratory qualitative research, the study outlines a systematic approach that includes a literature review, testing of a maturity model, and consultations with archival professionals. The MAA encompasses six key dimensions: principles, vision/strategic framework, compliance, methodology, tools, and criteria, providing a structured framework for assessing the maturity of appraisal practices in the AI age. Preliminary results highlight the potential benefits of AI in enhancing appraisal efficiency and effectiveness, paving the way for more informed and defensible archival decisions. Some applied use cases are already started and primarily derived results will be highlighted

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Published
2024-12-15
DOI
https://doi.org/10.1109/bigdata62323.2024.10826084
Citations
1
Primary Topic
Impact of AI and Big Data on Business and Society
Type
article
Field-Weighted Citation Impact
0.49
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article

Maturity Assessment of Appraisal Processes in the AI Age: Ongoing Framework and Measuring Method

Basma Makhlouf Shabou
1 citations
Impact of AI and Big Data on Business and Society
0.49
article

Maturity Assessment of Appraisal Processes in the AI Age: Ongoing Framework and Measuring Method

Basma Makhlouf Shabou
article en
1 citations

Abstract

The increasing volume of generated data and archives raises pertinent questions regarding the effectiveness of traditional archival appraisal methods, which largely depend on human expertise. As automation and artificial intelligence (AI) become prevalent in various sectors, the field of archiving stands on the brink of significant transformation.This paper explores the integration of AI within archival appraisal processes, framed within the context of the Maturity Assessment for Appraisal (MAA) project (2023-2025). The MAA seeks to evaluate the defensibility, stability, and appropriateness of current appraisal practices while assessing the readiness of records for automated appraisal. Employing exploratory qualitative research, the study outlines a systematic approach that includes a literature review, testing of a maturity model, and consultations with archival professionals. The MAA encompasses six key dimensions: principles, vision/strategic framework, compliance, methodology, tools, and criteria, providing a structured framework for assessing the maturity of appraisal practices in the AI age. Preliminary results highlight the potential benefits of AI in enhancing appraisal efficiency and effectiveness, paving the way for more informed and defensible archival decisions. Some applied use cases are already started and primarily derived results will be highlighted

HES-SO University of Applied Sciences and Arts Western Switzerland (CH)
Openalex Percentile: Top 27%
Impact of AI and Big Data on Business and Society
0.49
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