The Roles of Electronic Records Metadata (ERM) in Artificial Intelligence (AI) Growth
The paper highlights the roles of Electronic Records Metadata (ERM) in supporting the development of Artificial Intelligence (AI) in organizations. The issues occurred where the AI does not embed the ERM as part of its requirement in developing and manging the system in organizations. These include issues of inability of ERM in supporting any system in organizations which generated from AI technology. Based in these issues, the relationship between ERM and AI require a proper investigation in terms of its relation and connection. This issue has remained unsolved because it is still being discussed by scholars until today. This is where the main objective of this paper is to explore the roles of ERM in AI growth. Applying the method of Systematic Review Technique, the process of identifying the roles of ERM in AI are conducted adequately. Through the information gathered, the findings shows that there are Six (6) roles of ERM are gathered. There are data discovery and access, provenance and trustworthiness, interoperability, ethical and responsibility, quality of training, and long-term sustainability. Part of the relationship highlighted is ensuring whether the data that being generated by AI can be trusted or not. By embedding the ERM as part of AI system requirements, the data that being generated by any related system can be accessed, recovered and traced effectively. Through this justification, it has shown that the roles of ERM in AI are not only for its growth, but it is also can serve as evidence on any legal obligation.
Authors
- Aniza Jamaluddin (ORCID: https://orcid.org/0000-0002-5308-4805)
- Irwan Kamaruddin Abd Kadir
- Jafalizan Md Jali
- Ap-azli Bunawan (ORCID: https://orcid.org/0000-0003-2059-9797)
- Ezza Rafedziawati Kamal Rafedzi
- Hanis Diyana Kamarudin (ORCID: https://orcid.org/0000-0002-4089-4825)
Publication Details
- Journal
- International Journal of Research and Innovation in Social Science
- Published
- 2025-01-01
- DOI
- https://doi.org/10.47772/ijriss.2025.908000462
- Primary Topic
- Digital and Traditional Archives Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00