> 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/activity-codes.md).

# Activity Codes

Activity Codes describe how AI systems were used during the content lifecycle. While the FAIA Flags classify the overall nature of the resulting content, Activity Codes describe the structural role AI played within the workflow.

Unlike the FAIA Flags, multiple Activity Codes may be associated with a single declaration. This allows AI involvement to be described at a more granular level by capturing the different ways AI contributed during the creation, modification, or analysis of content.

## FAIA Activity Codes

### Co-Creation

AI and humans jointly produce content through an interactive process. The AI generates substantial parts of the content based directly on human-created material and structure. The resulting expressive contributions are interwoven and not cleanly separable.

### Contribution

AI produces discrete content elements that are incorporated into a primarily human-created work. The human determines the overall structure, intent, and final form of the resulting output.

### Enhancement

AI modifies or extends existing human-created content to improve quality, clarity, richness, completeness, or structure while preserving the original expressive intent and authorship of the source material.

### Refinement

AI performs limited adjustments that preserve the existing structure, meaning, expressive intent, and authorship of the content.

### Transformation

AI converts existing content into another form, modality, or representation while preserving semantic equivalence or maintaining a close relationship to the original content.

### Analysis

AI interprets existing content to derive structure, features, metadata, meaning, or analytical insights.

### Summary

| Code           | What the human provides                   | What the AI provides                                         |
| -------------- | ----------------------------------------- | ------------------------------------------------------------ |
| Co-Creation    | Core ideas, structure, or source material | Independent sections, elements, or content developed jointly |
| Contribution   | Overall structure and intent              | Discrete components integrated by the human                  |
| Enhancement    | Existing content                          | Extensions or quality improvements                           |
| Refinement     | Existing content                          | Minor surface-level or technical adjustments                 |
| Transformation | Prompt or task definition                 | Autonomous re-expression into another form                   |
| Analysis       | Prompt or analytical instruction          | Automated extraction, classification, or metadata generation |

## Domain-Specific Activity Codes

FAIA provides a generic, cross-domain set of Activity Codes that can be applied consistently across different media types. At the same time, it is designed to complement existing sector-specific standards and metadata ecosystems where appropriate.

Rather than replacing established classifications, FAIA allows domain-specific activity vocabularies to be incorporated into FAIA declarations, enabling interoperability while preserving terminology that is familiar within individual communities.

### STM AI Classification

The STM AI Classification is the first domain-specific activity vocabulary supported by FAIA. Developed by the STM Association, it provides a structured classification of AI use during the preparation of scholarly publications.

Unlike the generic FAIA Activity Codes, which apply across all media types, the STM vocabulary describes specific activities within academic research and publishing workflows. FAIA supports these classifications as machine-readable Activity Codes that can be included alongside FAIA Flags and System Attribution within the same declaration.

{% embed url="<https://stm-assoc.org/document/recommendations-for-a-classification-of-ai-use-in-academic-manuscript-preparation/>" %}

#### STM Language Refinement

AI tools are used to suggest or apply refinement, correction, editing, or formatting of manuscript text in order to improve clarity of language.

#### STM Manuscript Drafting

AI tools are used to generate rewrite, or draft part or all of the manuscript text.

#### STM Manuscript Translation

AI tools are used to assist translation of an author's original work into another language.

#### STM Data Presentation Refinement

AI tools are used to refine or format, or improve the presentation, clarity, or readability of the data reported in the manuscript or associated materials.

#### STM Illustrative Figure Generation

AI tools are used to generate, refine, correct, edit, or format images, diagrams, or other figures for illustrative or aesthetic purposes only, not as research data or research results.

#### STM Research Data Visualisation

AI tools are used to generate, refine, correct, edit, or format visualisations of research data or research results for inclusion in the manuscript.

#### STM Code Presentation Refinement

AI tools are used to refine or format code reported in the manuscript or associated materials in order to improve readability or clarity, without altering the functionality of the code.

#### STM Reference Gathering

AI tools are used to suggest references that may be relevant for inclusion in the manuscript's reference list.

Multiple STM Activity Codes may be associated with a single publication, allowing AI involvement to be described across different stages of the research and publication workflow.

### IPTC Digital Source Types

FAIA can also be used alongside the IPTC Digital Source Type vocabulary for photography and news media, allowing existing provenance classifications to be incorporated into FAIA declarations where appropriate.

## Design Principles

Activity Codes describe the role AI played during the content lifecycle rather than the overall nature of the resulting work. Every declaration may contain one or more Activity Codes, depending on the complexity of the workflow.

Together with the FAIA Flags and System Attribution, Activity Codes provide a structured and interoperable vocabulary for describing AI involvement across media types, sectors, and workflows.


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