Deepfake-induced harm and AI accountability: a layered civil-liability framework for generative models, platforms, and digital identity
Deepfake and other synthetic-media harms create a civil-liability problem that ordinary tort doctrine does not easily resolve: harmful content may be generated, amplified, monetised, and redistributed through a chain of actors in which no single participant controls the whole causal process. The objective of this article is to develop a layered civil-liability framework for that problem. It examines the Saudi and Jordanian civil-liability regimes as the principal doctrinal focus, while using selected EU, US, UAE…
Generative deepfake systems produce reputational, identity-based and corporate harms through chains of developers, prompting users, platforms and distributors that ordinary Saudi and Jordanian tort doctrine struggles to remedy.
Analysis is explicitly private-law centred and doctrinally limited to Saudi and Jordanian civil-liability regimes, with other jurisdictions used only as comparative reference, and does not claim to replace AI regulation with civil law.
Evidence
- Peer-reviewedFrontiers in Artificial Intelligence2026-07-02
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Truvace Impact Record TRV-2026-0132, v1: “Deepfake-induced harm and AI accountability: a layered civil-liability framework for generative models, platforms, and digital identity.” Truvace, 2026-07-13. /record/TRV-2026-0132 (accessed at citation time). sha256 9f01c26598a7ce64…
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