AI Consent Behavior Analysis for Personal Data Sensitivity

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Solution Overview

Problem

Current technologies face challenges in objectively determining the sensitivity of user information and managing personal information collection, leading to excessive data collection and user inconvenience, as well as difficulties in specifying appropriate purposes for data collection and managing collected information.

Innovation Solution

A device and method for personal information interest management and inclusion prediction that analyzes user behavior data during the consent process, assessing sensitivity and predicting the likelihood of information inclusion, using artificial intelligence to customize management strategies and generate personalized consent forms.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If personal information is collected with consent, then the purpose of collection is achieved, but it is difficult to objectively determine the level of sensitivity and manage the collected information

Engineering Contradiction:

Improveobjective determination of information sensitivityVSAvoidcomplexity of information management

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system automatically analyzes user behavior data during the consent process to determine information sensitivity levels and generates personalized management strategies without requiring manual intervention. The AI algorithm self-evaluates the consent behavior patterns and autonomously creates management plans, enabling the system to serve itself in determining sensitivity and managing information.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system collects user behavior data during the consent process and uses this feedback to analyze sensitivity levels. The analyzed results are then fed back into the system to generate customized management strategies and consent forms, creating a closed-loop feedback mechanism that continuously improves information management based on actual user behavior patterns.

Inventive Principle:

Principle #23Feedback

2Adaptability or versatility

If comprehensive personal information is collected, then the purpose of collection is achieved, but unnecessary information is collected resulting in user inconvenience

Engineering Contradiction:

Improvecompleteness of information collectionVSAvoiduser convenience

Core Design Contradiction:

Adaptability or versatilityVSEase of operation

Solution Approach 1:

The system determines the appropriate level of information collection for each specific case based on analyzed user behavior data and sensitivity levels. Instead of collecting comprehensive information uniformly, the system tailors the collection scope to local requirements, generating personalized consent forms that request only necessary information for each user's specific situation.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The system dynamically adjusts the information collection parameters based on analyzed behavior data. By changing the scope, type, and depth of information collection according to the determined sensitivity level and user context, the system achieves comprehensive information gathering when needed while minimizing unnecessary collection in other cases.

Inventive Principle:

Principle #35Parameter changes

3Ease of manufacture

If conventional consent processes are used, then the basic consent function is provided, but it is difficult to specify appropriate purposes for collecting personal information

Engineering Contradiction:

Improvesimplicity of consent processVSAvoidclarity of collection purpose

Core Design Contradiction:

Ease of manufactureVSLoss of information

Solution Approach 1:

The system performs preliminary analysis of user behavior data during the consent process to pre-determine the appropriate information collection purposes before the actual collection occurs. This preliminary action enables the system to generate personalized consent forms with clear, specific purposes tailored to each user's behavior patterns, preventing ambiguous or unclear collection purposes.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system creates personalized consent forms by copying and adapting standard consent templates to match the specific analyzed behavior data and determined purposes for each user. This copying process maintains the basic simplicity of standard forms while customizing the content to reflect the specific collection purposes identified through behavior analysis.

Inventive Principle:

Principle #26Copying

Data Source

PatentUS20260065401A1Device for personal information interest management and inclusion prediction and method for controlling same

Publication Date: 2026.03.05 O NE PEOPLE CO LTD

AI summary

The present disclosure relates to a device for personal information interest management and inclusion prediction and a method for controlling the same, and may include collecting user behavior data regarding viewing a consent of the user through the input module; analyzing the behavior data; determining abnormal and normal behavior based on the analysis result of the behavior data; processing the behavior data based on the analysis result to calculate a personal information interest level; and assigning a rating based on the calculated personal information interest level.