IP Library Granted Patent US 11,514,401
Granted Patent B2
US 11,514,401 · App. 15/813,018 · Granted Nov 29, 2022

Systems and methods for data-driven identification of talent

Inventors: Frida Polli (New York, NY); Julie Yoo (New York, NY)
Assignee: Pymetrics, Inc.
G06Q10/1053G06Q10/06398G06Q10/063112G09B7/02G09B7/06
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Quick Facts
Patent No.
US 11,514,401
App. No.
15/813,018
Granted
Nov 29, 2022
Kind
B2
Abstract

The present disclosure describes a talent-identification system that can be used by companies to assist in the recruitment process for new employees. Additionally, the system can be used by job seekers to determine ideal career fields and industries. The system employs an array of neuroscience-based tests to assess a user's career propensities, after which the system can provide career recommendations to the user or report on employment suitability of the user to a company.

Claims (65)

1. A computer program product comprising a non-transitory computer-readable medium having computer-executable code encoded therein, the computer-executable code adapted to be executed by a computing system having at least one processor and at least one memory to implement a method comprising:

a) providing a career identification system, wherein the career identification system comprises:

i) a task module;

ii) a measurement module;

iii) an assessment module;

iv) a model module;

v) an identification module;

vi) an output module; and

vii) a recommendation module;

b) providing, by the task module, performance-based games designed to measure a plurality of traits of a subject, the plurality of traits comprising emotional and cognitive traits, wherein the performance-based games are selected, by a processor of the computing system, based on a recognition of patterns and intelligent decisions based on input data from the subject;

c) measuring, by the measurement module, the input data from the subject to quantify, for each of the plurality of traits exhibited by the subject, interactions of the subject with the performance-based games when the subject individually interacts with the performance-based games;

d) assessing, by the assessment module, the plurality of traits of the subject based on the measured input data from the subject to extract measurements of the plurality of traits of the subject exhibited by the subject when the subject interacts with the performance-based games, wherein the measured input data comprises an indication of an effect of visual feedback provided during the performance-based games on a number, rate, or accuracy of interactions with a device, wherein the plurality of traits are used to measure an ability of the subject to learn from the visual feedback compared to that of a group of other subjects;

e) generating, by the model module, a reference model of the subject based on the assessment of the plurality of traits of the subject;

f) identifying, by the identification module, a plurality of career propensities based on the model of the subject, each career propensity based on a comparison of the subject to a composite of a plurality of test subjects in each of a plurality of career paths to determine how likely the subject will be to succeed in each career path;

g) generating, by the recommendation module, career recommendations of career paths based on the plurality of career propensities of the subject; and

h) outputting, by the output module, the generated career recommendations to the subject, the career recommendations indicating a likelihood of the subject to succeed in the career paths based on both emotional and cognitive traits of the subject.

2. The computer program product of claim 1 , wherein the career identification system further comprises a plurality of reference models corresponding to a plurality of traits possessed by workers in a plurality careers, and a comparison module, and wherein the method further comprises comparing by the comparison module the model of the subject and the plurality of reference models to determine a fit score for the subject in each of the plurality of careers.

3. The computer program product of claim 1 , wherein the career identification system further comprises a comparison module, and wherein the method further comprises comparing by the comparison module the model of the subject and a database of test subjects in a plurality of career fields to determine a fit score for the subject in each of the plurality of career fields.

4. The computer program product of claim 1 , wherein the method further comprises:

providing by the task module one or more of the performance-based games to a plurality of participants, wherein the plurality of participants are selected from workers in a plurality of career fields;

measuring by the measurement module a performance value demonstrated by each of the plurality of participants in their performance of the one or more performance-based games;

assessing by the assessment module a plurality of traits for each of the plurality of participants based on the measured performance value to extract measurements of the plurality of traits of the plurality of participants exhibited by the plurality of participants; and

generating by the model module a reference model for each of the plurality of career fields corresponding to a plurality of traits exhibited by the plurality of participants from each of the plurality of career fields,

wherein the reference model for each of the plurality of career fields is compared with the model of the subject in identifying the plurality of career propensities.

5. The computer program product of claim 1 wherein the career paths comprise a plurality of specific roles within a company.

6. The computer program product of claim 1 wherein the career paths comprise a plurality of career paths in different career fields.

7. A method, performed by a computing system having at least one processor and at least one memory, the method comprising:

a) providing, via a computing device, performance-based games designed to measure a plurality of traits of a subject, the plurality of traits comprising emotional and cognitive traits, wherein the performance-based games are selected, by a processor of the computing system, non-linearly based on input data from the subject;

b) measuring the input data from the subject to quantify, for each of the plurality of traits exhibited by the subject, interactions of the subject with the performance-based games when the subject individually interacts with the performance-based games;

c) assessing the plurality of traits of the subject based on the measured input data from the subject to extract at least one measurement for each of the plurality of traits of the subject exhibited by the subject when the subject individually interacts with the performance-based games, wherein the measured input data comprises an indication of an effect of visual feedback provided during the performance-based games on a number, rate, or accuracy of interactions with a device, wherein the plurality of traits are used to measure an ability of the subject to learn from the visual feedback compared to that of a group of other subjects;

d) generating a reference model of the subject based on the assessment of the plurality of traits of the subject;

e) identifying by a processor of the computing system a plurality of career propensities of the subject, each career propensity based on a comparison of the reference model of the subject with a database of a plurality of test subjects in each of a plurality of career paths to determine how likely the subject will be to succeed in each career path;

f) generating career recommendations of career paths based on the plurality of career propensities of the subject; and

g) outputting the generated career recommendations to the subject, each career recommendation indicating a likelihood of the subject to succeed in a career path based on both emotional and cognitive traits of the subject.

8. The method of claim 7 , wherein at least one of the performance-based games has an acceptable level of reliability as determined by a test-retest assessment.

9. The method of claim 7 , wherein the performance-based games have an acceptable level of reliability as determined by a split-half reliability assessment.

10. The method of claim 7 , wherein the plurality of assessed traits include at least one cognitive trait selected from the group of: processing speed, pattern recognition, continuous attention, ability to avoid distraction, impulsivity, cognitive control, working memory, planning, memory span, sequencing, cognitive flexibility, and learning.

11. The method of claim 7 , wherein the plurality of assessed traits include at least one emotional trait selected from the group of: trust, altruism, perseverance, risk profile, learning from feedback, learning from mistakes, creativity, tolerance for ambiguity, ability to delay gratification, reward sensitivity, emotional sensitivity, and emotional identification.

12. The method of claim 7 , further comprising:

providing one or more of the performance-based games to a plurality of participants, wherein the plurality of participants are selected from workers in a plurality of career fields;

measuring a performance value demonstrated by each of the plurality of participants in their performance of the one or more performance-based games;

assessing a plurality of traits for each of the plurality of participants based on the measured performance value to extract measurements of the plurality of traits of the plurality of participants exhibited by the plurality of participants; and

generating a reference model for each of the plurality of career fields corresponding to the plurality of traits exhibited by the plurality of participants from each career field,

wherein the reference model for each of the plurality of career fields is compared with the model of the subject in identifying the plurality of career propensities.

13. The method of claim 7 wherein the career paths comprise a plurality of specific roles within a company.

14. The method of claim 7 wherein the career paths comprise a plurality of career paths in different career fields.

15. The method of claim 7 , further comprising:

for each of a plurality of numbers of the performance-based games completed by subjects,

for each of a plurality of intervals,

storing an indication of how many subjects completed at least the number of the performance-based games completed by subjects during the interval.

16. The method of claim 7 , wherein the performance-based games include an analogical reasoning task configured to measure an ability of the subject to discern connections between concepts or events that are seemingly unrelated.

17. The method of claim 7 , wherein the performance-based games include a choice task configured to measure risk-taking inclinations of the subject.

18. The method of claim 7 , further comprising:

performing a reliability assessment to determine a precision of at least a portion of the measured input data from the subject, wherein performing the reliability assessment comprises measuring a correlation coefficient, wherein the correlation coefficient is a Pearson correlation coefficient.

19. A computing system, comprising:

at least one processor;

at least one memory;

a module configured to provide performance-based games designed to measure a plurality of traits of a subject, the plurality of traits comprising emotional and cognitive traits, wherein the performance-based games are selected, by a processor of the computing system, non-linearly based on input data from the subject;

a module configured to measure input data from the subject to quantify, for each of the plurality of traits exhibited by the subject, interactions of the subject with the performance-based games when the subject individually interacts with the performance based-games;

a module configured to assess the plurality of traits of the subject based on the measured input data from the subject to extract at least one measurement for each of the plurality of traits of the subject exhibited by the subject when the subject interacts with the performance-based games, wherein the measured input data comprises an indication of an effect of visual feedback provided during the performance-based games on a number, rate, or accuracy of interactions with a device, wherein the plurality of traits are used to measure an ability of the subject to learn from the visual feedback compared to that of a group of other subjects;

a module configured to generate a reference model of the subject based on the assessment of the plurality of traits of the subject; and

a module configured to output, to the subject, career recommendations of career paths generated based on a plurality of career propensities of the subject, each career recommendation indicating a likelihood of the subject to succeed in a career path based on both emotional and cognitive traits of the subject,

wherein each of the modules comprises computer-executable instructions stored in the at least one memory for execution by the computing system.

20. The computing system of claim 19 , wherein the emotional traits include trust, altruism, perseverance, risk profile, learning from feedback, learning from mistakes, creativity, tolerance for ambiguity, ability to delay gratification, reward sensitivity, emotional sensitivity, and emotional identification and wherein the cognitive traits include processing speed, pattern recognition, continuous attention, ability to avoid distraction, impulsivity, cognitive control, working memory, planning, memory span, sequencing, and cognitive flexibility.

21. The computing system of claim 19 , wherein the performance-based games are selected, by a processor of the computing system, non-linearly based intelligent decisions based on received data.

Assignments (4)
SECURITY INTEREST Recorded Aug 31, 2022
From: OUTMATCH, INC.; PYMETRICS, INC.
To: WELLS FARGO BANK, NATIONAL ASSOCIATION, AS AGENT
Reel/Frame 060949/0374 →
RELEASE OF SECURITY INTERESTS IN PATENTS Recorded Aug 30, 2022
From: HERCULES CAPITAL, INC.
To: PYMETRICS, INC.
Reel/Frame 061356/0566 →
INTELLECTUAL PROPERTY SECURITY AGREEMENT Recorded Sep 15, 2020
From: PYMETRICS, INC.
To: HERCULES CAPITAL, INC., AS AGENT
Reel/Frame 053786/0142 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 27, 2018
From: POLLI, FRIDA; YOO, JULIE
To: PYMETRICS, INC.
Reel/Frame 045055/0392 →
Continuity (5)
Continuation 15181322 · Jun 13, 2016
Continuation 14751943 · Jun 26, 2015
Provisional Application 62101524 · Jan 9, 2015
Provisional Application 62018459 · Jun 27, 2014
Related Publication 20180075416A1 · Mar 15, 2018
Cited By (1)
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