Authors: Dalganjan Singh
Abstract: This paper examines how political parties and campaign actors in India deploy artificial intelligence (AI) and social media to target individual voters, evaluates the effects of such targeted information campaigns on voter behaviour and electoral outcomes, and analyses the regulatory and ethical challenges—especially around data privacy and AI governance—that arise in the Indian context. Drawing on published studies, Election Commission of India (ECI) guidance, investigative journalism, and legislative texts, the paper constructs a conceptual framework of political microtargeting in India, documents contemporary tactics (data harvesting, predictive modelling, message personalization, use of closed-messaging platforms and influencer networks, and automated content generation), and assesses impacts (persuasion, mobilization/demobilization, selective information exposure, and polarisation). The paper then examines India’s legal landscape, focusing on the Digital Personal Data Protection Act (DPDPA) and ECI rules, and identifies gaps in regulation, enforcement challenges posed by platform practices and cross-border data flows, algorithmic opacity, and limitations of existing election law. The paper concludes with policy recommendations for transparency, stronger data governance for political processes, platform accountability, auditability of AI systems used in political communication, and electoral best practices to protect democratic deliberation.
DOI: https://doi.org/10.5281/zenodo.17569174
