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Training and Data Mining Assertion

The C2PA technical specification allows actors in a workflow to make cryptographically signed assertions about the produced C2PA asset.

The training and data mining assertion enables a human actor to provide a C2PA Manifest Consumer information about whether an asset with C2PA metadata may be used as part of a data mining or AI/ML training workflow.

Version 1.0 Approved 18 March 2024 · [_version_history]

Maintainers:

1. Introduction

This section is non-normative.

1.1. Scope

Important
 For purposes of the Community Specification License, the scope.md document at the root of this project’s GitHub repository is the governing document of this specification’s scope.

3. Assertion definition

3.1. Overview

This assertion enables a human actor to provide a Manifest Consumer information about whether the asset may be used as part of a data mining or AI/ML training workflow. This is expressed in the assertion through a map of one or more training-mining-entries. Each entry describes whether its use is allowed, notAllowed, or constrained.

There are four pre-defined entries:

cawg.data_mining

Can any text or data content be extracted from the asset for purposes of determining “patterns, trends, and correlations.”

Note
 This would include images containing text, where the text could be extracted via OCR.
cawg.ai_inference

Can the asset be used as input to a trained AI/ML model for the purposes of inferring a result.

cawg.ai_generative_training

Can the asset be used as training data to an AI/ML model that could generate assets.

cawg.ai_training

Can the asset be used as data to train non-generative AI/ML models, such as those used for classification, object detection, etc.

Note

cawg.ai_generative_training and cawg.ai_training are separate values because generative AI training enables new assets to be created from training assets, while other types, such as object detection, do not.

In addition to the pre-defined entries, a claim generator may also add their own custom keys, provided that they conform to the same syntax for custom labels as defined in Section 6.2, “Labels,” of the C2PA Technical Specification. Labels beginning with the prefix cawg. are reserved for use in future versions of this specification and MUST NOT be assigned by any other claim generator.

The value of constrained implies that permission is not unconditionally granted for this usage. Consumers of this content that wish to use the content in this way may wish to contact the actor which is the rights holder, author, or signer to get more info or obtain permission. In the absence of additional information, constrained shall be treated as equivalent to notAllowed. More details on the constraints may be provided in the constraints_info text field.

Note
 Some possible things that could be put into constraints_info include a well-known description of a license (e.g., Creative Commons), a URL to a policy file, or just some free text.

A training and data mining assertion SHALL have a label of cawg.training-mining.

Warning
Notice to implementers of previous (C2PA 1.x) definition of this assertion

Implementers who are transitioning from the earlier definition of this assertion should pay special attention to label names.

The training and data mining assertion as defined in version 1.4 of the C2PA technical specification used labels with the prefix c2pa. for the assertion itself and for the pre-defined training-mining-map entries.

This specification is not a product of the C2PA itself, so it can not use the c2pa. prefix. Therefore, though structurally similar to the C2PA 1.x definition, the labels have been changed to cawg. in this specification.

3.2. Schema and example

The CDDL Definition for this type is:

link:../partials/schemas/cddl/training-mining.cddl[role=include]

An example in CBOR Diagnostic Format (.cbordiag) is shown below:

link:../partials/schemas/cddl/examples/training-mining.cbordiag[role=include]