docs(EIPS/eip-7517.md): update the Rationale section based on reviewe…

…rs' inputs

Signed-off-by: Bofu Chen (bafu) <[email protected]>

EIPS/eip-7517.md

@@ -112,10 +112,13 @@ The mining preference example for allowing generative AI training if mentioning
 
 ## Rationale
 
-The introduction of the `miningPreference` property in digital asset metadata covers the considerations including
+The technical decisions behind this EIP have been carefully considered to address specific challenges and requirements in the digital asset landscape. Here are the clarifications for the rationale behind:
 
-Accessibility: A clear and easily accessible method with human-readibility and machine-readibility for digital asset creators and license owners to express their preferences for how their assets are used in data mining and AI/ML training workflows. The AI/ML creators can check and collect data systematically.
-Adoption: As Coalition for Content Provenance and Authenticity (C2PA) already outlines guidelines for indicating whether an asset may be used in data mining or AI/ML training, it's crucial that onchain metadata aligns with these standards. This ensures compatibility between in-media metadata and onchain records.
+1. Adoption of JSON schema: The use of JSON facilitates ease of integration and interaction, both manually and programmatically, with the metadata.
+2. Detailed control with training types: The different categories like `aiGenerativeTraining`, `aiTraining`, and `aiInference` let creators control in detail, considering both ethics and computer resource needs.
+3. Authorship options included: Options like `aiGenerativeTrainingWithAuthorship` and `aiTrainingWithAuthorship` make sure creators get credit, addressing ethical and legal issues.
+4. Introduction of `constrained` category: The introduction of `constrained` category serves as an intermediary between `allowed` and `notAllowed`. It signals that additional permissions or clarifications may be required, defaulting to `notAllowed` in the absence of such information.
+5. C2PA alignment for interoperability: The standard aligns with Coalition for Content Provenance and Authenticity (C2PA) guidelines, ensuring seamless mapping between onchain metadata and existing offchain standards.
 
 ## Security Considerations