Automated Assistant Privacy Scoring for Multi-Source Responses
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Solution Overview
Problem
Existing automated assistants face challenges in responding to requests that require access to multiple user data sources, particularly when such access involves sensitive or private information, without compromising user privacy.
Innovation Solution
Automated assistants aggregate individual privacy scores from various data sources and determine whether to respond based on an aggregate privacy score, formulating responses or taking actions only if the score meets a privacy threshold, and optionally seek user permission before divulging sensitive information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the automated assistant accesses multiple data sources to respond to a user's request, then the response accuracy and completeness is improved, but the user's privacy is compromised
Solution Approach 1:
The patent segments the privacy protection mechanism by introducing intermediate representations that separate the original sensitive data from the response generation process. Multiple data sources are accessed and transformed into segmented, privacy-preserving representations that can be processed without exposing raw sensitive information, thus maintaining both response accuracy and user privacy.
Solution Approach 2:
The patent employs intermediary components including privacy-preserving representations, intermediate models, and transformation layers that act as mediators between the multiple data sources and the response generation system. These intermediaries enable accurate responses while preventing direct exposure of sensitive user data, effectively resolving the contradiction between data access and privacy protection.
2Loss of information
If the automated assistant accesses multiple data sources to respond to a user's request, then the response completeness is improved, but the network resource consumption increases
Solution Approach 1:
The patent applies preliminary action by pre-processing and transforming data from multiple sources into privacy-preserving representations before the actual response generation. This preliminary transformation consolidates data access requirements, enabling the system to retrieve comprehensive information more efficiently and reduce redundant network operations during the response generation phase.
Solution Approach 2:
The patent merges multiple data source accesses into a unified processing framework where data from various sources are combined and transformed together through intermediate representations. This merging approach reduces the overall network resource consumption by consolidating data retrieval and processing operations, while still achieving complete and accurate responses.
3Measurement precision
If the automated assistant provides specific data points in responses, then the information accuracy is improved, but the user privacy is exposed
Solution Approach 1:
The patent extracts only the necessary information elements needed to answer user queries while leaving out sensitive identifying details. Through intermediate representations and transformation processes, the system extracts accurate factual information from multiple data sources and presents it in a privacy-preserving format, maintaining information accuracy without exposing user privacy.
Solution Approach 2:
The patent applies local quality by differentiating between information that should be disclosed (accurate response content) and information that should remain private (sensitive user data). The system selectively processes and discloses only the locally relevant information needed for accurate responses while maintaining privacy protection for sensitive elements through specialized transformation and representation techniques.
Data Source
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AI summary
Techniques are described herein for assembling/evaluating automated assistant responses for privacy concerns. In various implementations, a free-form natural language input may be received from a first user and may include a request for information pertaining to a second user. Multiple data sources may be identified that are accessible by an automated assistant to retrieve data associated with the second user. The multiple data sources may collectively include sufficient data to formulate a natural language response to the request. Respective privacy scores associated with the multiple data sources may be used to determine an aggregate privacy score associated with responding to the request. The natural language response may then be output at a client device operated by the first user in response to a determination that the aggregate privacy score associated with the natural language response satisfies a privacy criterion established for the second user with respect to the first user.