{
  "id": 3398,
  "url": "https://arxiv.org/abs/2606.00621v1",
  "title": "Authenticity Debt and the Synthetic Content Threat Landscape: A Layered Framework for Trust, Provenance, and IP Governance in the Generative AI Era",
  "summary": "Generative artificial intelligence has fundamentally changed how content is now produced. It has enabled how high-fidelity text, images, audio, and videos are created, modified, and redistributed at near-zero marginal cost. This shift exposes enterprises and ecosystems to a number of risks across four reinforcing authenticity layers -- authenticity, provenance, integrity, and accountability -- that traditional controls are inadequate to address in isolation. We introduce the concept of authentic",
  "authors": "Shubhashis Sengupta, Benjamin McCarty, Milind Savagaonkar, Rhine Andotra",
  "category": "research",
  "topics": "regulation,transparency",
  "orgs": null,
  "regions": null,
  "published_at": "2026-05-30T08:51:55.000Z",
  "fetched_at": "2026-07-14T16:30:14.369Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/3398",
  "original_url": "https://arxiv.org/abs/2606.00621v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}