Provable Accountability for Synthetic Harm: Binding Cryptographic Provenance to Evidentiary Presumptions

Synthetic content can cause measurable harm to real people, yet existing legal and technical frameworks struggle to establish who is accountable when that harm occurs. Current provenance systems can help identify where content originated, but they do not provide a reliable mechanism for attributing responsibility among the parties involved in its creation and deployment. This paper proposes a conceptual accountability architecture that creates a provable, non-repudiable connection between synthetic content generation and the entities that controlled the process. The framework introduces signed generation attestations that bind the producing system, the invoking party through a payment-linked zero-knowledge commitment, and the operative instruction and safety state at the moment of execution. Building on these verified facts, the paper presents an Evidentiary Presumption Generator (EPG), a mechanism that transforms cryptographically verified records into rebuttable legal presumptions while preserving judicial discretion. Rather than determining liability directly, the framework aims to reduce accountability ambiguity by providing courts with a stronger evidentiary foundation for evaluating synthetic harm claims. Designed as an extension to existing provenance standards such as C2PA and reinforced through auditable execution proofs and transparency-log anchoring, the architecture reframes accountability from after-the-fact inference toward cryptographically verifiable evidence. This work does not attempt universal enforcement across all AI systems, particularly offline or open-weight models. Instead, it proposes a practical accountability infrastructure for participating ecosystems and explores how cryptographic provenance may support future governance, compliance, and legal accountability mechanisms in the age of synthetic media.

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