Artificial Intelligence, Cyber Parties and Date-Driven policy making: Redefinition of Political Representation In Iran

Document Type : Research Article

Authors

1 Associate Professor of Political Science, Faculty of Law and Political Science, University of Tehran, Tehran, Iran

2 Ph.D. Student of Political Science, Faculty of Law and Political Science, University of Tehran, Tehran, Iran

10.22059/jppolicy.2026.106375

Abstract

The rapid advancement of emerging technologies—particularly AI and big data analytics—has profoundly transformed traditional structures of representative democracy. Political parties, long serving as intermediaries between citizens and governments, now face the rise of "cyber parties," compelling them to redefine their roles. This study examines how AI reshapes political representation and the role of cyber parties in fostering new models of political participation. It investigates how data-driven technologies challenge conventional notions of representation and explores cyber parties' influence in this process. The hypothesis posits that these technologies, by enabling direct citizen-state engagement and diminishing traditional parties' mediation, create a more transparent, agile, and data-informed model of representation. Findings suggest cyber parties leverage AI to predict voter behavior and tailor policies to real-time data, potentially enhancing democratic efficiency and legitimacy. However, risks include data platform monopolization, privacy violations, and marginalization of minority voices. Redefining representation in the data era demands revising democratic norms alongside algorithmic oversight and digital literacy mechanisms

Keywords


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