Between Exploitation and Resilience: Reconciling AI’s Role in Surveillance Capitalism and Disaster Risk Management

Sharifi Poor Bgheshmi, Mohammad Sharif; Sharajsharifi, Mahsa; Saeidabadi, Mohammad Reza

doi:10.22059/jcss.2025.396045.1165

Between Exploitation and Resilience: Reconciling AI’s Role in Surveillance Capitalism and Disaster Risk Management

Articles in Press

Document Type : Original article

Authors

¹ Department of Civil Engineering, Structural Engineering, Azad University, Qeshm, Iran.

² Department of Architectural Engineering, Azad University, North Tehran Branch, Iran.

³ Department of European Studies, Faculty of World Studies, University of Tehran, Tehran, Iran.

10.22059/jcss.2025.396045.1165

Abstract

Background: This study explores the paradoxical role of artificial intelligence as both a tool of exploitation within surveillance capitalism and a force for resilience in disaster risk management, highlighting the ethical and governance challenges that arise at the intersection of these domains.
Aims: This article aims to enable the ethical use of AI in DRM while insulating public systems from the structural harms of commercial data exploitation.
Methodology: Drawing from a comparative qualitative analysis of 35 academic sources, the study investigates how BigTech corporations and data brokers leverage AI to commodify personal data, consolidate informational power, and erode democratic agency.
Results: The present study critically examines the dual role of artificial intelligence in contemporary digital society, contrasting its exploitative deployment within surveillance capitalism with its constructive use in disaster risk management (DRM). Simultaneously, it highlights a parallel body of research showcasing AI’s capacity to enhance early warning systems, situational awareness, and post-disaster recovery, especially in resource-constrained and climate-vulnerable regions.
Conclusion: To reconcile these conflicting trajectories, the article proposes the Public AI for Resilience (PAIR) framework—a governance model grounded in data sovereignty, public infrastructure, algorithmic explainability, and cross-sectoral collaboration. Ultimately, the article argues for a normative recalibration of AI governance that prioritizes equity, transparency, and collective resilience over market imperatives, demonstrating that AI’s public good potential can be realized without surrendering to surveillance-based capitalism.

Keywords

Main Subjects

humanities & social sciences

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