Generative AI Task Extraction From Virtual Communication Data
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Solution Overview
Problem
Users face challenges in efficiently tracking and managing tasks arising from virtual communications, such as voicemail messages, emails, and chat messages, which can be time-consuming and difficult to organize across different channels.
Innovation Solution
A communication platform employs a pre-trained generative AI model to automatically generate and aggregate task items from virtual communication data, including voicemail messages, text messages, and emails, with customizable instructions for task generation and content moderation to ensure appropriateness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If users manually review virtual communication data to track tasks, then task accuracy can be maintained, but time consumption increases significantly
Solution Approach 1:
The system enables self-service by allowing the communication platform to automatically generate and aggregate task items from virtual communication data without requiring user intervention. The AI model processes voicemail messages, emails, and chat messages autonomously, extracting actionable tasks and presenting them in organized lists, thereby eliminating the need for users to manually review communication data.
Solution Approach 2:
The patent replaces the mechanical manual review process with an AI-based automated system. Instead of users manually reading and processing communication data, a pre-trained generative AI model analyzes the data, identifies tasks, and generates structured task items, substituting human cognitive processing with automated intelligent systems.
2Productivity
If users manually organize tasks from different communication channels, then task organization quality improves, but productivity decreases
Solution Approach 1:
The system merges tasks from multiple communication channels (voicemail messages, emails, chat messages) into a unified task list. The AI model aggregates information across different sources and formats, consolidating分散的 tasks into an organized presentation that users can access in a single location, thereby improving productivity while maintaining ease of operation.
Solution Approach 2:
The task generation system serves multiple functions simultaneously: it processes different communication channel formats, extracts actionable information, organizes tasks by priority and category, and presents them in a user-friendly interface. This multi-functionality eliminates the need for users to manually switch between different organization methods, enhancing both productivity and ease of operation.
3Productivity
If AI models process virtual communication data for task generation, then task generation speed increases, but data privacy concerns arise
Solution Approach 1:
The patent introduces content moderation as an intermediary layer between the AI model and the output. This moderation system reviews and filters the generated task items to ensure they meet safety and appropriateness standards before being presented to users. This intermediary mechanism allows the AI to process data efficiently while maintaining privacy and safety through customizable moderation rules.
Solution Approach 2:
The system allows users to customize AI features and moderation parameters according to their specific privacy and safety requirements. Users can adjust the level of automation, select which communication channels are processed, and configure content moderation thresholds, enabling them to control the balance between task generation speed and privacy protection based on their individual needs.
Data Source
AI summary
Example methods and systems for automatic task generation is provided. A communication platform receives an instruction to generate one or more task items associated with a virtual communication session related to a user. The communication platform accesses virtual communication data associated with the virtual communication session. The communication platform generates a task item based on the virtual communication data using a generative artificial intelligence (AI) model. The communication platform provides the task item to the user.