[ AUTHENTICITY ]
Authenticity & Human-Trace Protocols
In an age of synthetic and automated content, proving "who produced or endorsed what, when, and with what intent" is the basis of trust. The following directions combine technical depth and societal value:
From capture device and authoring tools to distribution, building verifiable metadata and provenance chains so content and claims can be independently checked. With cryptography and standardized metadata, providing a technical basis for integrity from source to presentation.
Distinguishing content and decisions "directly produced or explicitly endorsed by humans" from "purely machine-generated." Through signatures, statements, and auditable workflows, marking where human intent intervenes, for accountability and ethics review.
Using hashes, digital signatures, and distributed ledgers so that once fixed, content and records can be checked for tampering. Implementing cross-platform, cross-institutional integrity verification under open standards to support trust in law, news, and archives.
Standardized disclosure and machine-readable labels for AI-generated, deepfake, or heavily edited content so audiences and systems can make informed choices and filters. Balancing innovation and trust through technical standards and industry norms.
Human–AI collaboration is increasingly tight; how much human involvement counts as "human trace"? Is authenticity correspondence to the physical world, to claims, or to some consensus? Concepts and legal definitions must evolve with technology and social consensus.
Strong provenance and identity binding can threaten privacy and anonymous expression; weak labeling undermines abuse prevention. Balancing verifiability with privacy and free expression is a shared design and governance challenge.
Forgery and detection will co-evolve; single technical fixes are easy to bypass. Multi-layered, iterable protocols and ecosystems combining technology, behavior, and institutions are needed, not silver bullets.
Authenticity standards and law vary widely across jurisdictions. Achieving interoperability and compliance for cross-border content and services while avoiding fragmentation and rent-seeking requires international cooperation and open standards.
Adopting and promoting Content Credentials, C2PA, and other open provenance and claim standards; implementing interoperable origin and edit history in cameras, editing tools, and platforms so authenticity is the default.
Synthetic media detection, tamper localization, and digital forensics; maintaining interpretability and robustness in adversarial settings. Providing usable tools for news, law, and platform governance and keeping pace with new forgery methods.
Verifiable credentials, decentralized identity, and selective disclosure; balancing "prove it's me" with "don't over-disclose." Supporting human trace and accountability while protecting privacy.
Regulation and norms on authenticity, disclosure obligations, and platform responsibility; interdisciplinary input so technical standards align with law and ethics and iterate in practice.
From capture, creation, and publication to consumption, building end-to-end verifiable, cross-vendor and cross-jurisdiction standards and implementations so "authenticity" is infrastructure, not an add-on.
Where technically feasible, forming consensus definitions and legal effect for "human-produced/endorsed" to provide a clear, evolvable framework for liability, copyright, and ethics review.
Keeping detection, provenance, and disclosure effective and interpretable as forgery advances; combining technical, behavioral, and institutional layers to avoid single-point failure.
Ensuring authenticity technology is not a barrier: small creators, vulnerable groups, and resource-limited regions can use and verify at affordable cost. Standards and policy must balance inclusion with compliance.