Specification

DRAFT 2025-01-14

Vocabulary

Before a rights reservation can be expressed, it is necessary to define from what activity content should be excluded.

The following specification is a draft. It will be most likely enhanced by using a slightly more enhanced vocabulary that will distinguish between the following options:

1) TDM

The act of using assets in the context of any automated analytical technique aimed at analyzing text and data in digital form in order to generate information which includes but is not limited to patterns, trends and correlations.

2) TDM for AI Training Purposes

The act of training general-purpose AI models, or other types of AI models that are capable of performing a wide range of possible tasks. Such tasks include, without limitation, labeling or classifying content, semantically understanding content, recognising patterns, making decisions.

3) TDM for generative AI Training Purposes

The act of training general-purpose AI models, improving their capacity to generate text, images or other forms of synthetic content, or training other types of AI models that have the purpose of generating text, images or other forms of synthetic content.

Opt-out Declaration

This is an example of a machine-readable declaration by the rightsholder prohibiting the use of content for training models and applications of generative AI (see 3) TDM for generative AI Training Purposes).

Opt-out Declaration

{
  "iscc": "ISCC:KEC7VSV5QH7FTV7N5YVD5UMF4TUKFFGDGCOI4UDFKE4FNPW6C3L7J2Y",
  "TDMAI": false,
  "TDMAI_summary": "Content must not be used for training generative AI.",
  "TDMAI_policy": "Automated analysis of the work to extract information from it, especially about patterns, trends, and correlations for the purpose of training models and applications of generative AI, is reserved. Text and Data Mining (TDM) is permitted for general purpose AI systems that do not generate synthetic audio, image, video, or text content and for scientific research purposes or for temporary acts of reproduction as provided for in Article 5(1) of Directive 2001/29/EC."
}

https://liccium.app/api/v1/cid/optoutliccium.app

Expression of an opt-out declaration

When we speak of a "machine-readable opt-out", we mean an explicit reservation by the rightsholder that reproductions and extractions of lawfully accessible works and other protected subject matter are not permitted for the purposes of TDM for the purpose of training models and applications of generative AI. An opt-out is not possible for use for scientific research purposes.

Opt-out Revocation

Example of a machine-readable statement indicating that the rightsholder has revoked a previously issued opt-out declaration for TDM for AI, thus changed its position on the previous restriction.

Opt-out Revocation

{
  "iscc": "ISCC:KEC7VSV5QH7FTV7N5YVD5UMF4TUKFFGDGCOI4UDFKE4FNPW6C3L7J2Y",
  "TDMAI": true,
  "TDMAI_summary": "Content may be used for training generative AI.",
  "TDMAI_policy": "A reservation against the automated analysis of the work in order to extract information from it, in particular about patterns, trends and correlations for the purpose of training models and applications of generative AI, is not declared."
}

https://liccium.app/api/v1/cid/optinliccium.app

Expression of an opt-out revocation

An “opt-out Revocation” indicates that the rightsholder has made a declaration that should be interpreted in a way that no opt-out applies (anymore). While one might argue that such a declaration is redundant because permission is the default assumption, there are scenarios where the rightsholder may have initially expressed a machine-readable reservation but subsequently changed their stance.