Chatbot Data Subject Access Request Processing System
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Solution Overview
Problem
Current systems lack effective methods for managing and migrating personal data while ensuring compliance with regulatory restrictions and minimizing data breaches, particularly in cases of device or data center failures, and individuals seek tools to control data processing entities.
Innovation Solution
A data subject access request processing system comprising data subject access request management servers, local storage nodes, and processors that receive, route, and process requests to identify and manage personal data, while ensuring compliance with regulations through data transfer assessments and risk calculations, and utilizing chatbots for user inquiries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual processes are used to manage personal data and process data subject access requests, then flexibility and adaptability to individual cases can be maintained, but processing time and operational complexity increase significantly
Solution Approach 1:
The system enables automated self-service processing of data subject access requests through chatbot interactions. The chatbot autonomously collects user information, identifies personal data across multiple systems, and executes requests without requiring manual intervention for each individual case, thereby reducing processing time while maintaining operational effectiveness.
Solution Approach 2:
The system performs preliminary actions by pre-mapping personal data across multiple data systems and maintaining updated inventories of where personal data is stored. This preliminary organization allows the chatbot to quickly locate and process requests without time-consuming manual searches, resolving the contradiction between automated speed and accurate data location.
2Measurement precision
If comprehensive data mapping and inventory systems are implemented to track personal data across multiple systems, then data subject access requests can be fulfilled accurately, but system complexity and implementation difficulty increase
Solution Approach 1:
The system implements a universal data mapping framework that can interface with multiple different data systems and storage locations through standardized protocols. This multi-functional approach allows accurate tracking of personal data across diverse systems without requiring separate complex solutions for each system, reducing overall implementation complexity while maintaining precision.
Solution Approach 2:
The chatbot serves as an intermediary layer between users and the complex data mapping infrastructure. It handles user interactions and translates them into precise data location queries, shielding users from system complexity while leveraging the detailed data maps for accurate personal data identification across multiple systems.
3Productivity
If automated chatbot systems are deployed to process data subject access requests, then processing efficiency and speed improve, but the ability to handle complex judgment calls and edge cases deteriorates
Solution Approach 1:
The system incorporates feedback mechanisms where the chatbot learns from processed requests and user interactions. This allows the automated system to improve its ability to handle complex cases over time by adapting to edge cases and refining its decision-making algorithms based on accumulated experience, thereby maintaining both efficiency and adaptability.
Solution Approach 2:
The chatbot system is designed to be dynamic and adaptable rather than static. It can adjust its processing logic based on the complexity of incoming requests, escalating to human review when appropriate while handling routine cases autonomously. This dynamic approach allows the system to maintain high productivity for standard cases while preserving adaptability for complex situations.
Data Source
AI summary
A chat robot may be used to facilitate interaction with a user in the determination of whether to initiate and process a data subject access request (DSAR). At a DSAR submission webpage, the chatbot may interact with a user to determine the information the user is in need of and/or the actions that the user may take. The chatbot may provide the information desired by the user, avoiding the processing overhead of submission and fulfillment of a DSAR. The chatbot may also facilitate completion of a DSAR on behalf of the user when needed.