
The Evidence Crisis in AI Copyright Litigation
Courts are drowning in unreliable AI detection statistics. Cryptographic provenance offers the mathematical certainty judges demand in billion-dollar copyright battles.
What Encypher does: Insights from the Co-Chair of the C2PA Text Provenance Task Force on AI content authentication, content attribution, and licensing infrastructure. Standard publishes January 8, 2026.
Who it's for: Publishers seeking licensing strategies, AI labs exploring compliance, legal professionals interested in content attribution, and developers building with our API and SDKs.
Key differentiator: Written by the team co-chairing C2PA (c2pa.org) with NYT, BBC, AP, Google, OpenAI, Adobe, Microsoft and others - insider perspective on standards development.
Primary value: Stay informed on market licensing frameworks, regulatory developments, and technical innovations in cryptographic watermarking.
From the Authors of the C2PA Text StandardFrom the Authors of the C2PA Text Standard: Building Infrastructure for the AI Content Economy.

Courts are drowning in unreliable AI detection statistics. Cryptographic provenance offers the mathematical certainty judges demand in billion-dollar copyright battles.

February 2025 marked a turning point in AI's legal landscape. For the first time, a U.S. court explicitly rejected an AI company's fair use defense in Thomson Reuters v. ROSS Intelligence, while the EU AI Act's enforcement deadline triggered global compliance scrambles worth billions.