> For the complete documentation index, see [llms.txt](https://faia.liccium.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://faia.liccium.com/consortium/whitepaper.md). # Whitepaper ## Whitepaper The FAIA whitepaper presents the full framework for FAIR AI Attribution: the vocabulary for disclosing AI involvement, the attribution model built on FAIA Flags, Activity Codes, and System Attribution, and the technical infrastructure for persistent, verifiable declarations bound to content through ISCC fingerprints. It sets out the transparency problem FAIA addresses, the use cases and stakeholders it serves, and how declarations are created, signed, published, and resolved across federated registry infrastructure. It also positions FAIA in relation to related standards and initiatives, including C2PA, IPTC Digital Source Type, and the STM AI Classification. The whitepaper is available as a pre-publication on Zenodo. ### Read the whitepaper The FAIA Framework: A machine-readable vocabulary for AI attribution\ {% embed url="" %} ### How to cite Le Dévédec, S., Gambardella, A. A., Hettne, K., Posth, S., & Schultes, E. (2026). The FAIA Framework: A machine-readable vocabulary for AI attribution \[Whitepaper]. Zenodo. The whitepaper is published under a Creative Commons Attribution-ShareAlike 4.0 International licence (CC BY-SA 4.0). ### Funding This whitepaper is a deliverable under the Dutch Responsible AI in de praktijk programme, funded by SIDN fonds and Topsector ICT. See [Funding](/consortium/funding.md) for more about the programme and partners. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://faia.liccium.com/consortium/whitepaper.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.