Generative AI Output Customization via Facial Recognition Analysis

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Solution Overview

Problem

Generative AI systems lack the ability to customize output based on user-specific characteristics, leading to generic responses that may not align with the user's preferences, age, education level, or cultural sensitivities, resulting in suboptimal user experience.

Innovation Solution

A method and system that utilize facial recognition data to determine user characteristics, such as age, gender, and religious affiliation, and adjust the output using generative AI to customize aspects like vocabulary, grammar, and content, ensuring personalized responses through image analysis and social media data integration.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If generative AI creates output based on generic input processing, then the system is simple and fast, but the output lacks personalization and user relevance

Engineering Contradiction:

Improveoutput personalizationVSAvoidsystem complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system performs preliminary facial recognition and characteristic determination before generating the main AI output. By pre-analyzing user characteristics from facial images and storing them, the system prepares personalization data in advance, enabling customized output generation without adding significant complexity to the core generative AI process

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent introduces an intermediary layer between generic AI input/output that includes facial recognition analysis, characteristic determination, and output customization modules. This intermediary layer processes user-specific characteristics and modifies the AI output accordingly, adding personalization functionality while maintaining the core generative AI system's integrity

Inventive Principle:

Principle #24Intermediary (Mediator)

2Adaptability or versatility

If the system collects and analyzes facial recognition data to determine user characteristics, then output customization improves, but user privacy concerns and data processing complexity increase

Engineering Contradiction:

Improvecustomization capabilityVSAvoidprivacy concerns

Core Design Contradiction:

Adaptability or versatilityVSObject-affected harmful factors

Solution Approach 1:

The system extracts only the necessary characteristics (age, gender, ethnicity, etc.) from facial recognition data that are relevant for output customization, rather than collecting or storing complete facial images or excessive personal information. This extraction approach minimizes privacy intrusion while maintaining customization capability

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The system processes and analyzes facial data locally to determine characteristics, and only uses the derived characteristic information (not the raw facial images) for output customization. This localized processing approach reduces privacy risks by keeping sensitive data processing contained and using only the minimal necessary information

Inventive Principle:

Principle #3Local quality

Data Source

PatentUS20240338971A1Method and system for providing customized generative ai output

Publication Date: 2024.10.10 DONNENFELD GREGG

AI summary

A method includes determining at least one characteristic of or associated with a user based on facial recognition data of the user, using generative artificial intelligence (AI) to create output for the user based on input from the user, and customizing at least one aspect of the output based on the at least one characteristic. A system is also disclosed.