Personalized AI Bot Learning User Traits for Autonomous Interactions
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Solution Overview
Problem
Existing technologies lack efficient systems for personalizing artificial intelligence bots to mimic user characteristics for decision-making and interaction protocols, limiting their effectiveness in performing tasks on behalf of individuals.
Innovation Solution
A personalized AI bot system that utilizes AI algorithms to learn user characteristics from internal and external data sources, enabling autonomous interaction with both internal and external bots to perform tasks aligned with user preferences and privacy settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If AI algorithms are used to mimic user characteristics for decision-making, then task performance efficiency is improved, but system complexity increases
Solution Approach 1:
The patent creates a personalized bot that copies and mimics user characteristics, decision-making patterns, and interaction styles. The bot learns from user data including communication preferences, decision-making protocols, and interaction patterns, then replicates these behaviors autonomously to perform tasks on behalf of the user, thereby improving productivity while managing complexity through pattern replication rather than complex real-time analysis
Solution Approach 2:
The system performs preliminary learning and analysis of user characteristics before actual task execution. During a learning phase, the bot accumulates data about user preferences, communication styles, and decision-making patterns. This preliminary action allows the bot to be pre-configured with user-specific behaviors, reducing the complexity of real-time decision-making during task execution
2Ease of operation
If personalized bot interacts autonomously with multiple bots, then user effort is reduced, but reliability of interactions decreases
Solution Approach 1:
The personalized bot incorporates feedback mechanisms to continuously monitor and adjust its interactions. The bot receives feedback from interaction outcomes, user corrections, and performance metrics, then uses this feedback to refine its decision-making protocols and communication patterns. This feedback loop enhances reliability by allowing the system to learn from mistakes and improve over time while maintaining autonomous operation
Solution Approach 2:
The bot's behavior and decision-making protocols are dynamic rather than static. The system continuously adapts its interaction patterns based on learned user preferences and feedback from interactions. This dynamic adaptation allows the bot to maintain reliability by adjusting to changing conditions and user needs while reducing user effort through autonomous operation
3Measurement precision
If user data is collected from multiple sources for personalization, then bot accuracy is improved, but privacy concerns increase
Solution Approach 1:
The patent applies different processing and protection levels to different types of user data. Sensitive personal information receives enhanced privacy protection and access controls, while less sensitive data used for pattern recognition can be processed more freely. This local quality approach allows the system to maintain bot accuracy through comprehensive data collection while addressing privacy concerns through differentiated data handling strategies
Data Source
AI summary
A personalized artificial intelligence (AI) bot system includes a computing system and one or more data sources. The one or more data sources are configured to provide data related to a user to the computing system. The system also includes a personalized bot generated by the computing system based at least upon the data related to the user and configured to navigate a network to perform interactions, wherein the personalized bot comprises AI algorithms configured to utilize the data related to the user to mimic characteristics of the user within decision making protocols to facilitate the interactions. Further, the system includes one or more additional bots configured to participate in the interactions with the personalized bot.