Multi-stage approval and controlled distribution of AI-generated derivative content
A request is received associated with source content and including one or more user-specified parameters for creating a derivative work based on the source content. The derivative work is generated in response to evaluating the request against pre-generation preference data using an evaluation model, and is generated based on the source content in accordance with the one or more user-specified parameters by applying a generative artificial-intelligence model. The generative artificial-intelligence model includes a machine learning model configured to generate content based on the one or more user-specified parameters. A content approval score is generated by a content approval model based on an evaluation of the derivative work against post-generation preference data. In response to the content approval score satisfying a threshold, a digital identifier is generated based on the derivative work. At least one of distribution or usage of the derivative work is enabled in accordance with the digital identifier.
1 . A method for multi-stage approval and controlled distribution of a derivative work, the method comprising:
receiving a request associated with source content and including one or more user-specified parameters for creating a derivative work based on the source content;
in response to evaluating, using an evaluation model comprising a machine-learning classifier, the request against pre-generation preference data, generating, using at least one processor, the derivative work based on the source content in accordance with the one or more user-specified parameters by applying a generative artificial-intelligence model comprising a machine learning model configured to generate content based on the one or more user-specified parameters;
generating, by a content approval machine-learning model, a content approval score based on an evaluation of the derivative work against post-generation preference data;
in response to the content approval score satisfying a threshold, generating a digital identifier based on the derivative work;
providing at least one of the digital identifier or data associated with the digital identifier to a usage registry; and
enabling at least one of distribution or usage of the derivative work based on usage constraints associated with the at least one of the digital identifier or data associated with the digital identifier.
2 . The method of claim 1 , wherein the request is generated automatically by an application from contextual data without explicit user input.
3 . The method of claim 1 , wherein the machine-learning classifier is trained on historical approvals and rejections designated by a content authority.
4 . The method of claim 3 , further comprising:
transmitting the request to an external verification service designated by the content authority; and
approving the request for generation when both the machine-learning classifier and the external verification service return an approval indication.
5 . The method of claim 1 , wherein the pre-generation preference data specifies at least one of a temporal, quantitative, or geographic limit on derivative-work creation, and wherein the method further comprises rejecting the request when fulfilment of the request would exceed a limit on derivative-work creation.
6 . The method of claim 1 , wherein the generative artificial-intelligence model is a latent diffusion model.
7 . The method of claim 1 , wherein the threshold is a binary pass/fail threshold.
8 . The method of claim 7 , further comprising generating, when the derivative work fails the binary pass/fail threshold, a remediation report that identifies portions of the derivative work responsible for failing the binary pass/fail threshold.
9 . The method of claim 1 , wherein evaluating the derivative work further comprises:
comparing an audio fingerprint of the derivative work with a fingerprint library representing the source content; and
rejecting the derivative work when fingerprint similarity exceeds a similarity threshold.
10 . The method of claim 1 , wherein the digital identifier is a pointer that resolves to a remote record storing at least one of provenance data, attribution data or licensing data for the derivative work.
11 . The method of claim 10 , wherein the pointer comprises a cryptographically signed hash, and wherein the method further comprises verifying the cryptographically signed hash before enabling distribution of the derivative work.
12 . The method of claim 1 , further comprising detecting the digital identifier and replacing the digital identifier with a nested digital identifier that preserves provenance for successive derivative generations when the derivative work is subsequently received as source content.
13 . The method of claim 1 , wherein the digital identifier is associated with usage-constraint metadata comprising a time-to-live value and an authorization server automatically disables distribution of the derivative work upon expiry of the time-to-live value.
14 . The method of claim 1 , wherein the digital identifier is associated with usage-constraint metadata comprising at least one of: distribution channel restrictions; monetization parameters; attribution requirements; time-limited usage permissions; or geographical distribution limitations.
15 . The method of claim 1 , further comprising executing a smart contract that automatically allocates revenue from each authorized distribution of the derivative work to stakeholders identified in the usage registry.
16 . The method of claim 1 , wherein evaluating the derivative work against post-generation preference data comprises:
analyzing the derivative work for unauthorized incorporation of third-party content;
comparing the derivative work against objectionable content criteria; and
scoring the derivative work based on quality thresholds defined by a content authority.
17 . The method of claim 1 , wherein a post-generation evaluation is performed by a third-party service independent from an entity generating the derivative work.
18 . The method of claim 1 , wherein:
the pre-generation preference data comprises exclusionary criteria identifying at least one of themes, topics, or content elements prohibited from inclusion in the derivative work; and
evaluating the request against pre-generation preference data comprises:
identifying keywords or semantic elements within the request;
comparing the identified keywords or semantic elements against the exclusionary criteria; and
rejecting the request if the identified keywords or semantic elements match the exclusionary criteria.
19 . The method of claim 1 , wherein generating the derivative work comprises maintaining predetermined elements of the source content while modifying other elements according to the one or more user-specified parameters.
20 . The method of claim 19 , wherein the predetermined elements comprise at least one of original vocals, melody lines, rhythm patterns, or visual components.
21 . A method for approval and controlled distribution of a derivative work, the method comprising:
receiving a request associated with source content and including one or more user-specified parameters for creating a derivative work based on the source content;
in response to evaluating, using an evaluation model comprising a machine-learning classifier, the request against pre-generation preference data, generating, using at least one processor, the derivative work based on the source content in accordance with the one or more user-specified parameters using a generative artificial-intelligence model comprising a machine-learning model configured to generate content based on the one or more user-specified parameters;
generating, by a content approval machine-learning model, a content approval score based on an evaluation of the derivative work against post-generation preference data;
in response to the content approval score satisfying a threshold, generating a digital identifier based on the derivative work;
providing at least one of the digital identifier or data associated with the digital identifier to a usage registry; and
enabling or disabling at least one of distribution or usage of the derivative work based on usage constraints associated with the at least one of the digital identifier or data associated with the digital identifier.
22 . The method of claim 21 , wherein evaluating the request against pre-generation preference data comprises confirming compliance with content authority guidelines before generating the derivative work.
23 . The method of claim 21 , further comprising:
receiving a subsequent request to access the derivative work;
verifying the subsequent request by querying the usage registry using the digital identifier to retrieve associated usage constraints; and
selectively enabling or disabling playback, viewing, or distribution of the derivative work in accordance with the associated usage constraints.
24 . The method of claim 23 , wherein the subsequent request is received from a requestor, the requestor comprising at least one of:
a user device attempting to access the derivative work via a media application;
a content platform or distribution service requesting playback or download authorization;
an automated system performing periodic license verification; or
a third-party service querying usage permissions for compliance monitoring purposes.
25 . The method of claim 21 , wherein the pre-generation preference data comprises exclusionary criteria identifying at least one of themes, topics, or content elements prohibited from inclusion in the derivative work.
26 . The method of claim 21 , wherein the usage constraints include at least one of: distribution channel restrictions, monetization parameters, attribution requirements, time-limited usage permissions, or geographical distribution limitations.
27 . The method of claim 21 , wherein the digital identifier is a pointer that resolves to a remote record storing at least one of provenance data, attribution data, or licensing data for the derivative work.
28 . The method of claim 21 , wherein enabling or disabling at least one of distribution or usage of the derivative work based on usage constraints associated with the at least one of the digital identifier or data associated with the digital identifier is based on detection of at least one of a watermark or embedded data in the derivative work.
29 . A method for creating a derivative work, comprising:
receiving source content from at least one of a database server or a user upload;
receiving a request to transform the source content into a derivative work, wherein the request includes one or more user-specified parameters directed to one or more characteristics of the derivative work, and wherein at least one processor executes transformation operations based on the source content and the one or more user-specified parameters;
evaluating, using an evaluation model comprising a machine-learning classifier, the request against pre-generation preference data;
in response to the request satisfying the pre-generation preference data, creating the derivative work as a function of the source content and the one or more user-specified parameters using generative artificial intelligence comprising a generative machine-learning model configured to generate content based on the one or more user-specified parameters;
evaluating, using a content approval machine-learning model, the derivative work against post-generation preference data to generate a content approval score;
in response to the content approval score satisfying a threshold, generating a digital identifier based on the derivative work;
providing at least one of the digital identifier or data associated with the digital identifier to a usage registry;
enabling at least one of distribution or usage of the derivative work based on usage constraints associated with the at least one of the digital identifier or data associated with the digital identifier; and
fixing at least a portion of the derivative work in computer storage media.