AI Recommender System for HR Compatibility Assessment
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Solution Overview
Problem
Current human resources management methods are time-consuming and inconsistent, relying on human assessment that can be influenced by cognitive bias, making it challenging to accurately match resources with the right teams and managers within an organization.
Innovation Solution
A computer-implemented system using an AI recommender system that retrieves and processes attribute entries, job entries, and organization entries to generate competencies scores, strengths, and challenges of resource-manager duos, providing recommendations and action items, and is trained using both synthetic and field datasets to mitigate bias.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If human assessment methods are used to evaluate resource compatibility, then personalized insights can be provided, but the process becomes time-consuming and inconsistent
Solution Approach 1:
The patent replaces the mechanical human assessment system with an automated computer-based assessment system that uses algorithms and data processing to evaluate resource compatibility. This substitution eliminates human variability and time constraints while maintaining assessment quality through systematic data analysis.
Solution Approach 2:
The system enables self-service assessment where the computer automatically collects data, processes information, and generates compatibility evaluations without requiring human intervention for each assessment. This automation resolves the contradiction by making the process both fast and consistent.
2Reliability
If human psychologists and HR managers conduct assessments, then contextual understanding can be applied, but cognitive bias affects assessment reliability
Solution Approach 1:
The patent replaces the human judgment system with an automated computer-based system that processes assessment data objectively. This substitution eliminates cognitive bias and personal prejudices while maintaining system complexity through structured algorithms and data processing mechanisms.
Solution Approach 2:
The system introduces an intermediary computer-based assessment mechanism that stands between the resource and the final compatibility determination. This intermediary processes data through standardized algorithms, ensuring objective evaluation while managing complexity through systematic data handling procedures.
3Productivity
If automated AI systems are used for assessment, then consistency and speed improve, but the system requires complex training data preparation
Solution Approach 1:
The patent applies preliminary action by preparing training datasets in advance, including synthetic data generation and field data collection, before deploying the AI system. This upfront data preparation work, while complex, enables the system to operate efficiently and consistently once deployed, resolving the productivity-complexity contradiction.
Solution Approach 2:
The system uses multi-functional training data that serves multiple purposes: training the AI model, validating performance, and establishing baseline metrics. This universal approach to data preparation reduces overall complexity while enabling high productivity through a single comprehensive dataset strategy.
Data Source
AI summary
A computer-implemented method for assessing compatibility of resources within organizations is disclosed. The method comprises retrieving, from a profile dataset, attribute entries associated with a given resource and a manager, job entries associated with a job profiles, and organization entries associated with the organization; inputting in an AI recommender system the attribute entries, the job entries and the organization entries, generating by the AI recommender system competencies scores of the given resource and the manager, an indication of strengths and challenges of a duo formed by the given resource and the manager, for a given job profile within the organization; and recommendations and action items based on the indication of the strengths and challenges of the duo; and displaying, in a user interface, the competencies scores of the given resource and the manager, the strengths and the challenges of the duo and the recommendations and actions items for the duo.