Browser Task Ingestion for Lower Cognitive Load Delegation
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Solution Overview
Problem
Users face high processing loads from managing various tasks, which can prevent them from implementing higher priority tasks and degrade efficiency, and existing systems fail to effectively manage task facilitation and delegation.
Innovation Solution
A task facilitation service collects data from multiple sources, including user profiles and third-party applications, to generate and recommend tasks, and can delegate tasks to representatives or third-party providers, reducing cognitive load by managing the entire task lifecycle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users manually manage various tasks, then they maintain control over task execution, but their processing load increases and efficiency decreases
Solution Approach 1:
The patent introduces a task facilitation service as an intermediary between users and task execution. This service collects data from multiple sources (user profiles, third-party applications, browser data), generates task recommendations, and manages task delegation to representatives or third-party providers. Users retain control by reviewing and approving recommended tasks, while the intermediary handles the cognitive load of task management, thus resolving the contradiction between user control and efficiency.
2Reliability
If users manage all tasks themselves, then they ensure task accuracy and quality, but their cognitive load and processing resources are depleted
Solution Approach 1:
The task facilitation service acts as a mediator that handles task generation, recommendation, and delegation while maintaining quality control. The system uses multiple data sources and processing models to generate reliable task recommendations, which users then review before approval. This distributes the cognitive workload to the intermediary system while preserving users' ability to ensure quality through final approval, thus resolving the contradiction between reliability and cognitive load.
3Measurement precision
If the system collects data from multiple external sources, then task recommendations become more accurate and personalized, but system complexity increases
Solution Approach 1:
The task facilitation service implements a universal data collection framework that interfaces with multiple external sources (user profiles, third-party applications, browser data) through standardized mechanisms. This multi-functional approach allows the system to gather diverse data types through a unified architecture, improving recommendation accuracy while managing complexity through standardized data processing pipelines and integration protocols.
Data Source
AI summary
A computer-implemented method for generating tasks in a task facilitation service based on website data includes receiving website data for a website from a browser executed on a user computing device associated with a user. The method also includes processing the website data to generate a task recommendation for a task of the user and transmitting an indication corresponding to the task recommendation. When the indication is received by a computing device, the computing device is enabled to approve the task recommendation to generate a task corresponding to the task recommendation in the task facilitation service.