DOI: https://doi.org/10.14710/mmh.55.2.2026.310-347

GOVERNING DEEPFAKES: A LEGAL FRAMEWORK FOR ELECTORAL INTEGRITY IN SIERRA LEONE

*Thomas Sheku Marah orcid scopus  -  Departments of Business, Humanities and Law, Nusa Putra University, Indonesia
Bram B. Baan scopus  -  Departments of Business, Humanities and Law, Nusa Putra University, Indonesia
Ujang Badru Jaman scopus  -  Departments of Business, Humanities and Law, Nusa Putra University, Indonesia
Open Access Copyright (c) 2026 Masalah-Masalah Hukum under http://creativecommons.org/licenses/by-nc/4.0.

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Abstract

The rapid development of generative artificial intelligence has created significant legal challenges for electoral governance through the emergence of deepfake technologies capable of producing highly realistic but fabricated political content. Unlike conventional misinformation, deepfakes generate synthetic representations of reality that challenge traditional understandings of authenticity, evidence, public trust, and democratic accountability. This study examines the adequacy of Sierra Leone’s legal framework in addressing AI-generated electoral manipulation through an integrative legal research approach combining doctrinal legal analysis, comparative legal analysis, and regulatory governance analysis. The study evaluates the Constitution of Sierra Leone 1991, the Public Elections Act 2022, the Cyber Security and Crime Act 2021, and the Independent Media Commission Act 2020, while incorporating comparative perspectives from the European Union, selected United States jurisdictions, and Singapore. The findings reveal that Sierra Leone does not face a complete legal vacuum concerning deepfake-related electoral harms. Existing technology-neutral provisions may address specific forms of synthetic electoral interference where statutory requirements are satisfied. Nevertheless, the current framework remains fragmented and inadequate in regulating synthetic representation, deceptive authenticity, provenance transparency, platform accountability, and time-sensitive electoral remedies. To address these limitations, this study introduces the concept of Synthetic Electoral Manipulation (SEM) as a distinct legal category of electoral interference characterized by synthetic representation, electoral nexus, deceptive authenticity, legally relevant culpability, and democratic harm. The study further proposes a Synthetic Electoral Integrity Framework (SEIF), consisting of five pillars: Electoral Deepfake Classification System, Political AI Transparency Obligations, Platform Accountability Duties, Electoral Deepfake Offences, and Emergency Electoral Response Mechanism. This framework provides a constitutionally grounded approach that seeks to protect electoral integrity while preserving freedom of expression, due process, and democratic participation. The study contributes to emerging debates on AI governance, electoral law, and digital constitutionalism by offering a context-sensitive model for Sierra Leone and other emerging democracies confronting AI-enabled electoral manipulation.

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Keywords: Deepfakes; Electoral Integrity; Artificial Intelligence Governance; Synthetic Electoral Manipulation; Digital Constitutionalism

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