AI Digital Humans for Cross-Platform Career Profiling
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Solution Overview
Problem
Existing professional development networks fail to capture and utilize comprehensive user data from multiple platforms, limiting businesses' ability to provide accurate representations of their client base for career growth and employment opportunities.
Innovation Solution
A system utilizing digital humans powered by AI and machine learning to collect and analyze user data across various platforms, creating dynamic user profiles and stories that integrate lived experiences, learning activities, and professional development, offering personalized strategies and mentorship.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If digital humans powered by AI and machine learning are used to collect and analyze user data across various platforms, then user profiling accuracy and career guidance quality are improved, but system complexity and data processing requirements increase
Solution Approach 1:
The patent introduces digital humans as intermediary entities that collect, process, and analyze user data across multiple platforms. These digital humans serve as mediators between raw data sources and the career guidance system, transforming unstructured data from social media, professional networks, and learning platforms into structured user profiles. This intermediary layer improves measurement precision while managing system complexity by encapsulating complex data processing logic within the digital human framework.
Solution Approach 2:
The digital humans are designed with multi-functionality, serving multiple purposes: data collection from various platforms, user profile creation, career path analysis, and personalized guidance generation. This universal approach allows a single system component to handle diverse data types and processing tasks, improving profiling accuracy without proportionally increasing overall system complexity through functional consolidation.
2Adaptability or versatility
If comprehensive user data from multiple platforms is integrated, then personalized learning pathways and career opportunities are improved, but data privacy and security risks increase
Solution Approach 1:
The patent implements local quality by allowing different levels of data integration and processing for different users based on their privacy preferences and platform permissions. Rather than uniformly collecting all possible data, the system adapts data collection scope to individual user settings, enabling personalized guidance while respecting varying privacy requirements. This granular approach to data handling balances personalization capability with privacy protection.
3Productivity
If dynamic stories are generated using artificial intelligence based on user information, then user engagement and motivation are improved, but computational resources and processing time increase
Solution Approach 1:
The system applies partial action by generating dynamic stories selectively rather than continuously for all users. AI-powered story generation is triggered based on user milestones, profile updates, or specific interaction events, rather than operating continuously. This approach maintains high user engagement through personalized narratives while reducing computational resource consumption by limiting generation to necessary moments.
Data Source
AI summary
In an approach for monitoring and tracking professional development activities to empower end-users to obtain better employment opportunities, based on networking with those within the field and receiving training based on job related skills associated with various professions. A processor receives user information to create a user profile, wherein the user information includes natural language input. A processor creates the user profile for a user, wherein the user profile is based on the user information. A processor generates a dynamic story using artificial intelligence, wherein the dynamic story is based on the user information. A processor displays the dynamic story.