User Profile Inference System with Confirmation Feedback
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Solution Overview
Problem
Existing computing systems that infer user information for personalized services lack transparency, leading to user distrust due to unconfirmed and potentially incorrect data usage, as users are not actively involved in the data collection process.
Innovation Solution
Implementing a system that infers user information and actively seeks user confirmation or denial, using sensitivity and confidence thresholds to determine when to present input options, thereby promoting transparency and accuracy in user profiling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If systems infer user information automatically without user involvement, then productivity and service personalization are improved, but user trust and transparency deteriorate
Solution Approach 1:
The system implements a feedback mechanism where users can review inferred information and provide corrections. The patent shows users receiving notifications about inferred profile information with options to confirm or correct the data, creating a closed-loop feedback system that maintains both automation efficiency and user trust through continuous validation.
2Measurement precision
If systems solicit user input about inferred information frequently, then user trust and data accuracy are improved, but user burden and interaction complexity increase
Solution Approach 1:
The system applies partial action by soliciting user input only for specific inferred information items that meet certain criteria (confidence thresholds, sensitivity levels, relationship stages) rather than all inferred data. This selective approach maintains accuracy where needed while minimizing unnecessary user interactions and burden.
Solution Approach 2:
The system dynamically adjusts the frequency and timing of user input solicitation based on multiple parameters including confidence levels of inferences, sensitivity of information types, and the stage of user relationship with the system. These parameter changes optimize the balance between accuracy and user burden adaptively.
3Productivity
If systems present sensitive inferred information early in user relationship, then data collection speed is improved, but user comfort and social appropriateness deteriorate
Solution Approach 1:
The system performs preliminary actions by building user relationships and establishing trust before presenting sensitive inferred information. The patent implements relationship staging where the system tracks interaction history and only presents sensitive information after reaching appropriate relationship thresholds, ensuring social appropriateness before data collection acceleration.
4Reliability
If systems manually collect user profile data, then user trust and data accuracy are improved, but productivity and user convenience deteriorate
Solution Approach 1:
The system merges automated inference capabilities with user confirmation mechanisms into a unified profile creation process. Rather than choosing between fully manual or fully automated approaches, the patent combines both: automated systems generate initial profile data through inference, then users review and confirm key information, achieving both efficiency and accuracy simultaneously.
Data Source
AI summary
A system is described that infers information about a user and then provides the user with an opportunity to provide input about (e.g., confirm or deny) the inferred information. Inferred information is presented to a user only after certain triggering events have occurred. For example, a sensitive item of inferred information may be presented to a user only after the user has reached a certain stage of relationship with a system, device or service that is deemed compatible with presenting such sensitive information. As another example, an item of inferred information may be presented to a user only after it has been determined that the item of inferred information is likely to be correct with a certain degree of confidence. As a still further example, both sensitivity and confidence level may be used to guide when a particular item of inferred information will be presented to a user.