Digital Inequality in AI Governance: Inclusive Pathways for Aging Populations
DOI:
https://doi.org/10.54097/k5fzak34Keywords:
Digital inequality; AI governance; aging populations; inclusive governance; digital literacy; algorithmic bias; participatory design.Abstract
The rapid expansion of artificial intelligence governance frameworks at the national and international levels has generally lacked any substantive involvement from older people; as they interact with digital technologies, their unique relationship to these systems makes them particularly vulnerable to AI-based policy decisions but also one of the groups least engaged in regulating these systems. Examines digital inequality in terms of its manifestation at the level of AI governance; analyzes the structural barriers faced by older adults in accessing AI-mediated services and participating in related governance activities; proposes an inclusiveness pathway to promote more adequate realisation of governance systems that serve the interests and dignity of ageing individuals. According to Van Dijk's multidimensional model of digital inequality, Gaventa's inclusive governance framework and the literature on seniors' technology adoption, it is argued that realising genuine inclusive AI governance requires intervention at three interrelated levels: physical access; Digital skills and AI literacy; Policy participation. Based on the data of the International Telecommunication Union, policy guidelines such as the European Union's AI Act and the World Health Organization's global strategy for ageing and health are used to provide empirical basis and regulatory references for this research's suggestions.
Downloads
References
[1] van Dijk JAGM. The Deepening Divide: Inequality in the Information Society. SAGE Publications; 2005.
[2] Gaventa J. Finding the spaces for change: A power analysis. IDS Bulletin. 2006;37(6):23–33.
[3] Renaud K, van Biljon J. Predicting technology acceptance and adoption by the elderly: A qualitative study. In: Proceedings of the 2008 Annual Research Conference of the South African Institute of Computer Scientists and Information Technologists. ACM; 2008. p. 210–219.
[4] World Health Organization. Global Strategy and Action Plan on Ageing and Health 2016–2020. WHO; 2017.
[5] European Parliament and Council of the European Union. Regulation on Artificial Intelligence (EU AI Act). Official Journal of the European Union; 2024.
[6] International Telecommunication Union. Measuring Digital Development: Facts and Figures 2023. ITU; 2023.
[7] Friemel TN. The digital divide has grown old: Determinants of a digital divide among seniors. New Media and Society. 2016;18(2):313–331.
[8] Knowles B, Hanson VL. The wisdom of older technology (non)users. Communications of the ACM. 2018;61(3):72–77.
[9] Mitzner TL, Boron JB, Fausset CB, et al. Older adults talk technology: Technology usage and attitudes. Computers in Human Behavior. 2010;26(6):1710–1721.
[10] Ragnedda M. Conceptualizing digital capital. Telematics and Informatics. 2018;35(8):2366–2375.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 International Journal of Education and Social Development

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.









