> 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/technology/vocabulary/system-attribution.md).

# System Attribution

System Attribution identifies the AI system involved in the creation or modification of digital content. While the FAIA Flags describe the overall nature of the resulting work and Activity Codes describe how AI contributed during the workflow, System Attribution records which AI technology was used.

Identifying the AI system adds transparency, reproducibility, and context. Different AI systems, and different releases of the same system, can vary substantially in capabilities, training data, behaviour, limitations, safeguards, and licensing conditions. Recording this information allows AI involvement to be interpreted more accurately.

FAIA defines two complementary attribution fields: System and Version.

## System

The System field identifies the AI system, model, service, or model family used to generate or modify content. Where possible, the provider's official designation should be used.

Examples include:

* `ChatGPT`
* `Claude`
* `Google Gemini`
* `DALL·E`
* `Stable Diffusion 3`
* `Midjourney`

## Version

The Version field identifies the specific release or version of the AI system used. Where known, the designation should follow the naming or numbering scheme used by the system provider.

Examples include:

`5.2`\
`Sonnet 4`\
`2.5 Pro`\
`v1.3.2`\
`Beta-2`\
`2025-10-release`

## Why it matters

System and Version together support transparency, reproducibility, regulatory disclosure, rights management, and informed interpretation of AI-involved content. The version in particular provides precise context about system behaviour, capabilities, limitations, and known issues at the time of use, since different releases of the same system may differ substantially in performance, training data, safeguards, or output characteristics.

## Design Principles

System Attribution identifies the AI technology involved in the content lifecycle. It does not describe the degree of AI involvement or the role AI played during creation, which are represented separately through the FAIA Flags and Activity Codes.

Every System Attribution may contain a System value and, where available, a Version value. Together they provide a consistent, machine-readable way to identify the AI technology used, complementing the broader FAIA attribution framework.


---

# 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 dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://faia.liccium.com/technology/vocabulary/system-attribution.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

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.