Acta Informatica Pragensia 2025, 14(2), 272-281 | DOI: 10.18267/j.aip.2701516

Universal Basic AI Access: Countering the Digital Divide

Petr Špecián ORCID...1,2, Jitka Špeciánová ORCID...3
1 Institute of Political Science, Faculty of Social Sciences, Charles University, Prague, Czech Republic
2 Department of Philosophy, Faculty of Economics, Prague University of Economics and Business, Prague, Czech Republic
3 Department of Managerial Economics, Faculty of Business Administration, Prague University of Economics and Business, Prague, Czech Republic

Generative artificial intelligence (GAI) presents an opportunity to democratize access to high-performance, easy-to-use tools of productivity enhancement. However, current adoption patterns suggest that it may instead amplify existing digital divides. The aim of this paper is to propose a policy intervention to ensure equitable access to frontier GAI capabilities: the universal basic AI access (UBAI). Relying on literature research and theoretical analysis, we examine two implementation variants: a voucher-based system making use of commercial providers (UBAI-Light) and direct public provision of GAI services (UBAI-Heavy). We also consider a gradual implementation approach that allows policymakers to support an immediate capture of democratizing benefits while building the capacity for a more substantive future government involvement, should it become necessary. Given the rapid pace of GAI development and adoption, we conclude that timely implementation of UBAI could help prevent the spread of GAI-driven inequalities before they become entrenched.

Keywords: Generative artificial intelligence; Digital divide; Technology policy; Universal basic services; Digital inequality; AI governance.

Received: February 2, 2025; Revised: May 23, 2025; Accepted: May 31, 2025; Prepublished online: June 29, 2025; Published: July 26, 2025  Show citation

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Špecián, P., & Špeciánová, J. (2025). Universal Basic AI Access: Countering the Digital Divide. Acta Informatica Pragensia, 14(2), 272-281. doi: 10.18267/j.aip.270
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