Published June 17, 2026 | Version 0.9

FAIA - FAIR AI Attribution White Paper

  • 1. ROR icon Leiden University
  • 2. Leiden Academic Center for Drug Research
  • 3. partners in FAIR
  • 4. ROR icon GO FAIR Foundation
  • 5. Liccium

Contributors

  • 1. mabablue GmbH
  • 2. GO FAIR Foundation

Description

This white paper describes the FAIA - FAIR AI Attribution Framework. FAIA provides a vocabulary and technical framework for machine-readable, persistent, and verifiable disclosure of AI involvement. It defines three complementary elements: high-level attribution flags (human-created, AI-assisted, AI-generated), activity codes describing the role AI played in the content lifecycle, and optional system attribution identifying the AI system and version involved. FAIA declarations can be bound to ISCC fingerprints, allowing attribution information to remain resolvable even when files are copied, transformed, or stripped of metadata.

FAIA supports consistent transparency across sectors including publishing, journalism, research, and media production. It supports compliance with emerging obligations such as the EU AI Act and provides a foundation for services that depend on reliable provenance information, including content verification, moderation, search, and training data curation.

Notes (English)

This white paper is a deliverable under the Dutch “Responsible AI in de Praktijk” programme, funded by SIDN fonds and Topsector ICT.

Files

2026-06-18_FAIA_whitepaper_draft_0.9.pdf

Files (2.4 MB)

Name Size Download all
md5:b76351e1470ed7a59d98799a23202170
2.4 MB Preview Download

Additional details

Funding

SIDN Fonds

Dates

Available
2026-06-17