Deepfake Governance During National Election Campaigns

Abstract

Background: The expansion of policy activity around deepfakes has exposed a potential gap between formal design and day-to-day implementation, particularly in relation to elections.

Objective: We evaluated the administrative operation of policy concerning deepfakes, emphasizing transparency, practical implementation conditions, and elections.

Methods: Evidence from 14 jurisdictions and 24 institutions was assessed in a mixed-method observational design. Standardized coding of documentary and administrative material was supplemented where appropriate by stakeholder or practitioner data, followed by descriptive and multivariable analysis.

Results: Only 67% of institutions met the predefined standard for consistent procedures around deepfakes. Settings with stronger coordination performed 25% better on the principal measure. The recurring constraints were insufficient capacity and uncertainty over institutional responsibility.

Conclusion: The study suggests that variation in outcomes related to deepfakes is driven substantially by how institutions organize implementation and oversight. This means that responsible AI adoption requires governance arrangements that can be implemented consistently across agencies, not merely high-level principles.

Study design: content-monitoring and policy study.

Publication history: Originally published in print on 15 June 2024, Volume 4, Article 2. Online abstract record added on 16 September 2026. Full-text PDF will be added when the digital galley is ready.