Granted Patent B2

US 12,615,402 · App. 18/980,056 · Granted Apr 28, 2026

Inventor: Michael James Fiorentino (New York, NY)

H04N21/236H04N21/845

Abstract

Claims (181)

1 . An AI governance system for compliance enforcement, decision optimization, and media ecosystem coordination, comprising:

a Technology Administrator, configured to:

execute governance decisioning, apply compliance policies, and manage structured governance models across layered digital environments, including content, metadata, and monetization frameworks;

coordinate remixable media architectures through compliance-driven, stakeholder-defined, AI-driven, programmatic, or rule-based logic; and

facilitate structured arbitration across automated workflows, regulatory models, or governance enforcement mechanisms;

a Decisioning Engine, configured to:

apply governance policies to structured digital assets, comprising at least one of:

metadata-governed content structures;

stakeholder-defined assets;

licensing configurations;

governance-linked content identifiers; or

algorithmic decision protocols;

processing inputs related to arbitration, monetization, media transactions, or compliance enforcement across at least one of:

content,

licensing agreements,

brand integrations or custom messaging,

stakeholder preferences,

AI models,

datasets, or

digital value exchanges including currencies, tokens, or payments; and

update or maintain governance logic in response to arbitration outcomes or compliance modeling across multi-entity systems;

a governance enforcement mechanism, configured to:

validate and enforce compliance constraints across centralized, distributed, or multi-stakeholder governance environments using rule-based or hybrid enforcement methods; and

trigger overrides or intervention controls to prevent policy violations or unauthorized activity;

an adaptive governance module, wherein governance decisions and enforcement behaviors are dynamically refined based on system behavior, environmental signals, or predefined governance parameters;

wherein the system operates within a centralized, distributed, or decentralized network to apply governance arbitration and compliance structuring across structured digital environments.

2 . A computer-implemented application, comprising the AI governance system according to claim 1 configured to enable Technology Administrators to manage AI-driven, programmatic, or algorithmic decisioning, compliance enforcement, and transactional oversight, by performing at least one of:

executing event-driven triggers to transmit software or hardware commands for media playback, interactive adjustments, or enforcement of governance rules;

defining governance parameters, including compliance constraints, Al decisioning criteria, and financial oversight rules;

executing governance-driven media control operations, including provisioning, structuring, and transactional oversight;

processing governance directives to regulate media provisioning, content modifications, and monetization structures, based on Al-driven curation, stakeholder-defined preferences, or external compliance frameworks;

facilitating API-driven integrations with external auditing services, licensing verification systems, and regulatory compliance ecosystems, including jurisdictional auditing layers and monetization rule enforcement; and

issuing enforcement directives to suspend, override, or restrict system operations upon detecting governance violations.

3 . A computer-implemented method for AI-driven governance, the method comprising:

receiving governance inputs via a Technology Administrator, wherein governance inputs include at least one of:

AI-driven, programmatic, or algorithmic governance;

stakeholder-defined governance preferences;

licensing and financial structuring parameters;

external regulatory inputs from third-party systems; and

programmatic governance tracking, including transactional validation logs, arbitration records, and cross-platform policy enforcements;

processing governance inputs using weighted decision models and compliance engines, wherein the system:

evaluates media compliance, licensing restrictions, and transactional rules;

dynamically modifies or maintains governance parameters based on AI decisioning models, algorithmic processes, or structured policy enforcement; and

configures governance-controlled provisioning of media, licensing transactions, and regulatory compliance actions;

executing governance outputs, wherein the system:

transmits governance enforcement actions to applications, interfaces, and system components;

issues event-driven triggers to execute software or hardware commands modifying governance-controlled processes;

distributes governance updates across interconnected user environments; and

detects arbitration compliance or failure, triggering governance enforcement overrides, applying preemptive constraints, or requiring external validation before further execution.

4 . The AI governance system of claim 1 , wherein the Technology Administrator, Decisioning Engine, and Governance Enforcement Mechanism are configured to facilitate AI-driven governance oversight, arbitration, and compliance enforcement within digital media ecosystems, wherein the system is further configured to:

apply weighted governance parameters to decisioning criteria across media content, advertising integrations, stakeholder preference frameworks, data exchange mechanisms, AI models, and algorithmic distribution channels,

wherein a stakeholder comprises at least one of: an end-user, content producer, technology administrator, brand sponsor, licensing entity, compliance engine, regulatory authority, or autonomous agent;

validate resource exchanges, including monetization transactions, content licensing, and currency-based interactions between content producers, users, and third-party entities within a governance-regulated decisioning marketplace;

maintain authoritative governance records of cross-platform media interactions and AI-driven, programmatic, or rule-based decision-making processes;

process governance inputs using weighted computational models to generate compliance-regulated media experiences based on stakeholder preference data and governance policies;

execute automated arbitration processes for AI-driven content selection, advertising placement, and content distribution based on structured governance enforcement parameters; and

modify governance enforcement dynamically based on real-time regulatory updates, financial risk analysis, or stakeholder-defined governance preferences.

5 . The computer-implemented method of claim 3 , wherein the Technology Administrator:

allocates, configures, and provisions media elements in accordance with AI-driven, programmatic, or rule-based governance constraints;

adjusts modular content compositions, including channel lineup structuring and multi-layered media recomposition based on ai decisioning models, compliance enforcement, or stakeholder-defined preferences;

applies content adaptation rules to modify structured media playback and dynamically recompose media layers in response to governance-based restrictions, licensing compliance, or weighted financial parameters, wherein the adaptation occurs in real-time, according to preconfigured scheduling, based on stakeholder-defined rules, or through programmatic logic; and

enforces content moderation dynamically, restricting, reordering, or modifying playback parameters based on evolving governance policies, ai compliance filters, and audience engagement analytics.

6 . The computer-implemented method of claim 3 , wherein the Decisioning Engine is configured to facilitate governance enforcement through structured AI-driven decision processing, the Decisioning Engine performing at least one of:

evaluating governance inputs including regulatory constraints, compliance policies, monetization rules, stakeholder-defined preferences, or behavioral analytics;

filtering or weighting raw data inputs, including behavior logs, media interaction metrics, or regulatory flags, according to stakeholder-defined governance parameters prior to model evaluation or directive execution;

receiving and executing governance directives issued by Technology Administrators, AI compliance systems, or external governance frameworks;

dynamically adapting enforcement strategies in response to real-time conditions, content performance, or federated learning signals;

resolving conflicts through hierarchical governance prioritization or multi-entity reconciliation protocols; and

applying supervised, unsupervised, or reinforcement learning models, configured to adapt based on structured governance signals and observed behavioral outcomes.

7 . The computer-implemented method of claim 3 , wherein the Technology Administrator, AI Content Producer, or external governance systems coordinate via an interoperability framework, comprising at least one of:

synchronizing governance policies across multiple AI-driven entities, human-operated compliance models, and hybrid governance systems;

enabling structured governance exchanges between AI agents, regulatory bodies, and compliance verification frameworks;

facilitating AI-to-AI governance interactions to execute structured governance arbitration, wherein autonomous AI models validate, reconcile, and apply governance policies within decentralized and multi-entity ecosystems; and

applying protocol-agnostic governance enforcement, ensuring compliance operations function across cloud-based, on-premise, and decentralized infrastructures without reliance on fixed integration standards.

8 . The AI governance system of claim 1 , wherein the Technology Administrator and AI Content Producer are implemented as AI-driven software modules, human-operated governance systems, or hybrid AI-human compliance frameworks, wherein:

the Technology Administrator autonomously or collaboratively manages decisioning, compliance enforcement, and monetization operations, including regulating AI-driven transactions, structuring financial constraints, and overseeing adaptive governance models across AI and human workflows; and

the AI Content Producer functions as an AI-based content structuring system, generating, modifying, or curating dynamic multilayered media structures, leveraging real-time decisioning frameworks, compliance thresholds, and multi-system AI coordination.

9 . The computer-implemented method of claim 3 , wherein AI-driven monetization structures include at least one of:

allocating sponsorship placements and revenue distributions using AI-driven, programmatic, or algorithmic decision models based on weighted governance parameters;

managing subscription-based access models, including user-paid tiers, institution-based access, data collective-based access, or peer-to-peer lending of licensed media and digital resources;

facilitating sponsored content financing and advertising-driven monetization through API-based integrations;

processing automated compensation transactions for AI and human content producers, including fractionalized ownership, direct payments, smart contract execution, and tiered subscription models;

conducting blockchain-based resource exchanges, including digital assets, media tokens, and AI training data;

executing tokenized licensing transactions, blockchain-based resource exchanges, media element monetization flows, or smart contract-based compliance and attribution protocols;

optimizing AI execution efficiency by dynamically allocating computational workloads and processing power;

facilitating brand-subsidized content financing and advertising-driven monetization through API-based integrations; and

enforcing compliance-integrated monetization governance to align with financial regulations, copyright frameworks, and regional content distribution policies.

10 . The computer-implemented method of claim 3 , comprising at least two of:

logging real-time governance enforcement actions, compliance adjustments, AI-driven or programmatic interventions, stakeholder modifications, or financial transactions as structured metadata records;

applying algorithmic oversight to verify compliance modifications across Al and programmatic decisioning layers;

tracking secure metadata for AI-generated content modifications, licensing changes, and regulatory policy enforcement;

recording the origin, modification history, and attribution of media layers using metadata tagging and compliance records;

verifying licensing terms and content ownership through automated validation mechanisms;

adjusting governance enforcement dynamically based on external regulatory directives; and

applying privacy filters or protective safeguards to anonymize, obfuscate, or restrict access to personally identifiable information (PII) or sensitive user data during governance enforcement or decision logging processes.

11 . The AI governance system of claim 1 , wherein the governance model includes one or more of:

adaptive compliance thresholds that align regulatory enforcement with stakeholder-defined governance preferences;

multi-stakeholder weighted governance inputs, incorporating AI-driven or programmatically structured decision models for arbitration and compliance enforcement, external compliance rules, human governance interventions, and decentralized governance models;

distributed AI processing frameworks, blockchain-integrated compliance frameworks, and tokenized governance entities as governance enforcement mechanisms;

autonomous compliance enforcement mechanisms integrated with AI-driven or programmatically controlled monitoring tools;

real-time adaptive decisioning based on AI-generated or programmatic governance triggers; and

governance arbitration layers applying weighted AI assessments to resolve disputes between financial models, content ownership claims, and algorithmic compliance mechanisms.

12 . The computer-implemented method of claim 3 , wherein the Technology Administrator governs regulatory compliance structures by:

adjusting compliance structures in response to system-defined operational trends and engagement analytics;

applying predictive modeling to preemptively determine governance enforcement based on historical compliance patterns; and

modifying governance policies dynamically based on at least one of:

real-time regulatory updates, scheduled compliance refreshes, programmatically determined revision cycles, or event-triggered governance framework adjustments;

compliance risk factors;

AI-driven, programmatic, or algorithmic behavioral insights;

regulatory changes;

stakeholder-defined governance preferences;

multi-device, cloud-based, distributed, and decentralized AI governance synchronization;

risk-based governance optimization methodologies;

cross-platform regulatory alignment frameworks;

federated compliance validation signals; or

automated governance arbitration outcomes.

13 . The computer-implemented method of claim 3 , wherein the Technology Administrator facilitates governance enforcement mechanisms, by performing at least one of:

validating governance modifications, tracking decision consistency, and refining decisioning models;

evaluating AI and human decision-making processes, recording decision rationale, and mapping governance actions to decision pathways;

logging governance activities as structured metadata while maintaining comprehensive records of compliance actions, financial transactions, and content modifications, with integrated privacy safeguards that filter personally identifiable information (PII) and sensitive data according to access authorization levels;

enforcing compliance constraints based on local community standards, governance policies, and individual or collective stakeholder-defined preferences; and

modifying governance parameters in response to externally defined governance policies, compliance validation mechanisms, or system-determined operational criteria.

14 . The AI governance system of claim 1 , wherein governance structures are applied across:

distributed governance systems that coordinate compliance validation between AI-driven, programmatic, or algorithmic financial oversight entities, transactional exchanges of structured digital assets, and decentralized economic models;

tokenized revenue-sharing models that apply compliance-driven sponsorship financing, AI-managed monetization constraints, or dynamic exchange mechanisms between media, advertising, algorithmic resources, and other value-based assets; and

cross-platform regulatory alignment ensuring that financial transactions, licensing rules, and compliance structures remain interoperable across jurisdictional frameworks, collective agreements, or authorized content distribution systems.

15 . The computer-implemented method of claim 3 , wherein governance enforcement structures comprise adaptable frameworks that perform operations including but not limited to:

implementing AI driven, programmatic, or algorithmic decisioning models for evaluating stakeholder inputs compliance signals, and monetization policies;

decisioning models across various network configurations, including cloud-based networks, ad-hoc networks, local area networks (LANs), wide area networks (WANs), or portions of the Internet;

executing licensing enforcement for media elements and dynamic multilayered media structures through applying programmatic decisioning, enforcing compliance frameworks, verifying third-party certifications, or aligning with community standards;

authenticating resource exchanges by utilizing blockchain integrations, recording secured metadata, maintaining data profiles with version histories, or operating API-driven validation systems that process transactions between stakeholders; and

utilizing structured enforcement methodologies including at least one of:

rule-based enforcement;

automated intervention models;

hierarchical compliance prioritization; or

hybrid governance structures that integrate human and automated oversight.

16 . The computer-implemented application of claim 2 , wherein the governance interface enables modification of governance parameters through:

stakeholder-defined governance preferences and decision overrides;

rule sets for arbitration across multi-stakeholder environments;

tokenized licensing conditions, usage permissions, or attribution requirements;

governance logic models, content ranking factors, compliance thresholds, or monetization parameters, implemented through AI-driven, programmatic, or algorithmic systems;

visualization tools including compliance dashboards, hierarchical policy maps, or real-time governance feedback interfaces;

privacy enforcement rules, audit access configurations, or data minimization settings;

proposal, review, and voting mechanisms facilitated by governance entities or stakeholder groups; and

integration with external governance frameworks, regulatory protocols, or interoperable rule systems.

17 . The computer-implemented method of claim 3 , wherein configuring the governance interface comprises one or more of the following:

receiving stakeholder-defined governance preferences and decision modifications;

applying arbitration rule sets across multi-stakeholder governance environments;

implementing token-based licensing terms, usage constraints, or attribution requirements;

modifying governance logic, content ranking factors, monetization settings, or compliance enforcement models using AI-driven, programmatic, or algorithmic systems;

enforcing privacy filters, access permission structures, or data protection mechanisms;

triggering administrator-level overrides or jurisdiction-specific governance actions;

capturing governance operations, enforcement actions, and decision activities as structured metadata for verification and system continuity; and

enabling authorized governance entities to access decision records, policy pathways, or validation layers in accordance with defined role-based permissions.

18 . The computer-implemented method of claim 3 , wherein governance enforcement and media ecosystem compliance comprises one or more of the following:

executing AI-driven, programmatic, or algorithmic enforcement and arbitration mechanisms based on stakeholder-defined governance models and regulatory factors;

detecting discrepancies across compliance decisions, financial policies, or content governance frameworks and adapting logic to maintain policy consistency;

managing AI-to-AI arbitration exchanges through automated systems that route unresolved issues to governance validation mechanisms or stakeholder oversight structures;

applying localized enforcement actions, access restrictions, or regionally scoped governance requirements across distributed systems;

modifying governance instructions dynamically in response to behavior patterns, regulatory signals, or system-detected governance anomalies; and

recording governance enforcement activities, resolution actions, and policy adjustments as structured metadata accessible through permissioned governance interfaces.

19 . The computer-implemented method of claim 3 , wherein the Technology Administrator facilitates AI-managed ownership and monetization structures by:

evaluating stakeholder-defined compliance preferences and licensing terms within dynamic media structures;

enabling tokenized licensing for fractionalized ownership of digital content and AI-generated assets;

processing audit data generated by stakeholder-defined inputs, programmatic logic, or algorithmic decisioning to determine risk exposure across content reuse and remix activities;

structuring programmatic sponsorship models aligned with stakeholder-defined inputs, AI-driven audience segmentation, or algorithmic decisioning;

executing smart contracts for licensing, fractional ownership, and automated payment distribution;

detecting ownership inconsistencies and monetization anomalies within tokenized content structures; and

generating comprehensive audit records for administrative validation.

20 . The AI governance system of claim 1 , wherein governance enforcement applies across computing environments and devices, including at least one of:

cloud-based systems supporting centralized or distributed governance rule execution;

on-device environments configured for local compliance enforcement and playback control;

distributed edge computing infrastructures supporting latency-sensitive governance decisions;

federated compliance layers operating across multiple nodes or stakeholder jurisdictions;

embedded or real-time governance engines integrated into hardware, smart appliances, or playback systems;

immersive media environments, including virtual reality (VR), augmented reality (AR), mixed reality (MR), or spatial computing interfaces;

blockchain-integrated or decentralized storage systems operating with distributed ledgers;

internet-of-things (IOT) connected devices, generic computing devices, or industrial computing systems; and

hybrid architectures using AI-driven, programmatic, algorithmic, or rule-based decision logic for enforcement, synchronization, and playback control;

wherein governance logic may include monetization rules, content access policies, and playback permissions; and

wherein a stakeholder comprises at least one of: an end-user, content producer, technology administrator, brand sponsor, licensing entity, compliance engine, regulatory authority, or autonomous agent.

Continuity (5)

References Cited (20)