Ai-driven workforce development
AssigneeVigilant IP Holdings LLC
InventorChristopher M. Nyhuis
Life of this patent
Estimating the term…
Abstract
The present disclosure describes systems and methods to enhance workforce development, employee efficiency, and training opportunities through AI/ML assistance during regular workforce tasks. The systems and methods support allows employers to effectively train employees without the added pressures of explicit skills testing. Employers can better understand the workforce while improving workforce skillsets and improving the operation of human-machine systems.
Claims20
A workforce development system, comprising:
- a processor;
- and
- a memory storing instructions whereby the processor is configured to perform the steps of:
- collecting performance data about a user;
- assisting the user based on the performance data;
- presenting one or more skill tests to the user such that the user is unaware of the testing;
- analyzing the performance data with an AI/ML engine;
- and
- optimizing the assistance to the user based on the analyzed performance data.
The system of claim , wherein the instructions further cause the processor to perform the step of generating a performance report based on the performance data.
The system of claim , wherein the AI/ML engine comprises a neural network.
The system of claim , wherein the inference pipeline comprises monitoring whether a statistical distribution of the performance data aligns with a statistical distribution of the training data.
The system of claim , wherein the inference pipeline comprises monitoring the analyzed performance data for performance, or operational, variance or drifts.
A method performed by a workforce development system for customizing and optimizing assistance, comprising the steps of:
- collecting performance data about a user;
- providing assistance to the user based on the performance data;
- presenting one or more skill tests to the user such that the user is unaware of the testing;
- analyzing the performance data with an AI/ML engine;
- and
- optimizing assistance based on the analysis of the performance data.
The method of claim , further comprising generating a performance report based on the performance data.
The method of claim , wherein the performance data comprises biometric data.
The method of claim , further comprising implementing a training pipeline and an inference pipeline, wherein:
- the training pipeline ingests training data and uses the ingested training data to train the AI/ML engine;
- the trained model is deployed from the training pipeline to the inference pipeline;
- and
- the analyzing step comprises the inference pipeline applying the deployed model to the performance data to yield the analyzed performance data.
The method of claim , wherein the AI/ML model comprises a neural network.
The method of claim , wherein the inference pipeline comprises monitoring whether a statistical distribution of the performance data aligns with a statistical distribution of the training data.
The method of claim , wherein the inference pipeline comprises monitoring the analyzed performance data for performance, or operational, variance or drifts.
A computer-implemented method for training a machine learning model for optimizing a workforce development system, the method comprising:
- obtaining a dataset of identified training outcomes;
- training the machine learning model using the dataset of identified training outcomes, thereby obtaining a trained machine learning model;
- storing the trained machine learning model;
- and
- applying the trained machine learning model to one or more inputs to yield workforce development suggestions.
The method of claim , further comprising training a machine learning model for optimizing identified training outcomes, wherein the training comprises;
- training the machine learning model using a dataset of one or more identified training outcomes, thereby obtaining a further trained machine learning model;
- and
- storing the further trained machine learning model.
The method of claim , wherein the one or more identified training outcomes comprise one or more of:
- user expertise level, suggested trainings, assistance prompts.
The method of claim , wherein the one or more inputs comprise one or more of:
- user performance data, task data, regulation data, task data.
The method of claim , wherein the one or more inputs comprise biometric data.
The method of claim , further comprising generating a performance report based on the workforce development suggestions.
Dependencies are inferred from the claim text.