Browsing by Author "Justina Ekwutosi Ogbonna"

Now showing 1 - 1 of 1
  • No Thumbnail Available
    Item
    REDEFINING RECORDS MANAGEMENT IN THE AI ERA: A HUMAN-CENTRED, COLLABORATIVE FRAMEWORK FOR INTELLIGENT DIGITAL PRESERVATION
    (LEAD CITY INTERNATIONAL JOURNAL OF LIBRARY, INFORMATION & COMMUNICATION SCIENCES [LCIJLICS]., 2025-07) Habib Shehu; Justina Ekwutosi Ogbonna; Ify Evangel Obim
    The integration of artificial intelligence (AI) into records management is transforming digital preservation, enabling automation of metadata generation, classification, and retention. However, reliance on AI without human oversight risks bias, opacity, and erosion of archival principles. Traditional frameworks like ISO 15489 and OAIS are ill-equipped for AI-driven environments, creating a critical gap between technological innovation and ethical governance. This study proposes a Human-Centred, Collaborative Framework for Intelligent Digital Preservation that integrates AI with interdisciplinary governance and organisational stewardship. Using a systematic literature review (SLR) following PRISMA 2020 guidelines, 41 peerreviewed and authoritative sources were analysed through thematic synthesis. Findings reveal that while AI enhances efficiency, fewer than a third of studies address transparency or human oversight. Interdisciplinary collaboration is widely acknowledged, yet formal governance structures remain underdeveloped. Ethical concernssuch as algorithmic bias and marginalisation of underrepresented voices are prominent, with limited integration of frameworks like CARE and UNESCO’s AI Ethics Guidelines. The proposed framework consists of three layers: (1) a Technological Layer (AI automation, predictive appraisal), (2) a Human-Centred Governance Layer (multi-staff oversight, ethical review), and (3) an Organisational Stewardship Layer (alignment with OAIS, ISO 15489, FAIR, and CARE principles). This model redefines records management as a socio-technical process where AI supports, rather than supplants, human judgment. Three recommendations are offered: implement AI within auditable workflows, establish collaborative governance committees, and pilot the framework in institutional settings. This research advances a holistic, ethical, and sustainable approach to digital preservation in the AI era.