AI Multitasking Notification for Communication Sessions
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Solution Overview
Problem
Users of digital communication platforms face challenges in determining which activities they can perform during a communication session due to the lack of accurate prediction of multitasking options based on their unique behaviors and preferences.
Innovation Solution
A system utilizing an AI model analyzes user behavioral profiles and past event data to provide intelligent notifications of multitasking options, considering factors such as recurring meetings, participation levels, and user preferences, allowing users to engage in activities like walking or exercising during events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users attend multiple scheduled events throughout the day, then productivity and collaboration are improved, but the ability to perform personal activities during events deteriorates
Solution Approach 1:
The system performs preliminary analysis of user behavioral profiles and event characteristics before the event occurs. It predicts suitable multitasking activities in advance and provides notifications to users, allowing them to prepare and execute activities during the event without interfering with communication participation.
Solution Approach 2:
The system automatically analyzes user behavior patterns, event metadata, and communication protocols to generate personalized multitasking recommendations without requiring manual input from users. The AI model continuously learns from user behavior to improve prediction accuracy over time.
2Reliability
If users dedicate full attention to each meeting, then communication quality is improved, but availability for other activities deteriorates
Solution Approach 1:
The system enables users to participate partially in meetings by allowing them to engage in multitasking activities while maintaining communication connection. Users can listen to audio, view shared content, and respond when needed without requiring full undivided attention, thus reducing time loss while maintaining adequate participation.
Solution Approach 2:
The system continuously monitors user engagement levels and communication activity during events. It provides real-time feedback to users about their participation status and adjusts multitasking recommendations accordingly, ensuring that users maintain sufficient engagement while pursuing personal activities.
3Adaptability or versatility
If the system provides comprehensive multitasking recommendations, then user flexibility is improved, but system complexity deteriorates
Solution Approach 1:
The system generates personalized multitasking recommendations tailored to each user's specific behavioral profile, event type, and communication patterns. Rather than providing generic recommendations, it analyzes local characteristics of each event and user combination to deliver relevant activity suggestions, improving flexibility without requiring overly complex universal systems.
Solution Approach 2:
The AI model analyzes multiple parameters including user behavior history, event duration, communication intensity, and activity intensity levels to determine suitable multitasking options. By dynamically adjusting recommendations based on these parameter changes, the system provides comprehensive options while maintaining manageable complexity through structured analysis frameworks.
Data Source
AI summary
Methods and systems provide for intelligent notification of multitasking options during a communication session. The system receives information associated with a number of past requested events associated with a user of a communication platform, and a user behavioral profile associated with the user. The system receives notification of a requested event for the user. The system then deploys an AI model to analyze the user behavioral profile with respect to the requested event and the one or more past events, and generate, based on the analysis, prediction classification scores for one or more multitasking activities which can be performed by the user concurrently to attending the requested event. Finally, the system provides, based on the prediction classification scores, notification of at least a subset of the one or more multitasking activities which can be performed by the user concurrently to attending the requested event.