AI Prompt Enforcement via Smart Contract Validation

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Solution Overview

Problem

The use of advanced AI technologies like ChatGPT raises ethical concerns regarding misinformation, bias, privacy, and intellectual property, necessitating a balanced approach to regulate their use while preserving freedom of expression and leveraging their benefits.

Innovation Solution

An AI prompt enforcement method utilizing natural language processing analysis, smart contracts, and decentralized networks to register and validate AI prompts, ensuring that specific conditions are met before execution, thereby ensuring compliance with enforcement policies and protecting fundamental rights.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Object-affected harmful factors

If AI technologies are banned or limited to address ethical concerns, then harmful factors are reduced, but productivity and benefits of AI are lost

Engineering Contradiction:
Improveethical concernsVSAvoidAI benefits
Core Design Contradiction:
Object-affected harmful factorsVSProductivity

Solution Approach 1:

The patent introduces enforcement policies and regulatory intermediaries that mediate between AI technologies and their deployment. These policies act as intermediaries that enable AI use while addressing ethical concerns through structured governance frameworks, allowing productivity benefits to be realized without uncontrolled harmful effects.

Inventive Principle:
Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent implements feedback mechanisms through enforcement policies that monitor and regulate AI deployment. This feedback system allows continuous adjustment of AI usage to maintain ethical standards while preserving productive benefits, creating a dynamic balance rather than static prohibition.

Inventive Principle:
Principle #23Feedback

2Object-affected harmful factors

If enforcement policies are applied to regulate AI use, then harmful factors are controlled, but device complexity increases

Engineering Contradiction:
Improvemisuse riskVSAvoidregulatory system complexity
Core Design Contradiction:
Object-affected harmful factorsVSDevice complexity

Solution Approach 1:

The patent segments enforcement policies into distinct, modular components that can be applied selectively to different AI applications and contexts. This segmentation reduces overall system complexity by allowing only relevant policies to be activated for each specific use case, rather than requiring all policies to be implemented universally.

Inventive Principle:
Principle #1Segmentation

3Object-affected harmful factors

If AI prompts are restricted to protect intellectual property, then harmful factors are reduced, but ease of operation deteriorates

Engineering Contradiction:
Improveintellectual property violationsVSAvoidprompt execution convenience
Core Design Contradiction:
Object-affected harmful factorsVSEase of operation

Solution Approach 1:

The patent applies preliminary action by pre-attaching enforcement policies to AI prompts before they are executed. This ensures that intellectual property protections are automatically enforced without requiring users to manually check or configure settings, maintaining ease of operation while preventing violations through advance configuration.

Inventive Principle:
Principle #10Preliminary action

Data Source

PatentUS20250103892A1Ai prompt enforcement method, system and computer programs
Publication Date: 2025.03.27 TELEFÉNICA INNOVACIÉN DIGITAL SL
  • US20250103892A1 patent drawing
  • US20250103892A1 patent drawing
  • US20250103892A1 patent drawing

AI summary

An AI prompt enforcement method, system and computer program are provided. The method comprises receiving, from a prompt generator, an AI prompt for the AI model; performing a natural language processing analysis over the received AI prompt to recognize features thereof; selecting an enforcement policy, comprising conditions for the AI prompt, from the stored enforcement policies, and attach the conditions to the AI prompt using the dedicated smart contract; registering the AI prompt to a decentralized and distributed network using the smart contract, providing a validated AI prompt as a result; receiving a request to execute the validated AI prompt from a prompt executor; checking if the prompt executor satisfies the enforcement policy; and forwarding the AI prompt to the AI-based model only if the selected enforcement policy is satisfied by the prompt executor.