Ai platform with customizable content analysis control panel and methods for use therewith

Abstract

A system operates by: generating, via a machine that includes at least one processor and a non-transitory machine-readable storage medium and utilizing a graphical user interface, a content analysis control panel; receiving, via the machine, customization data that indicates a plurality of virtue scoring models, and presentation parameters associated with the plurality of virtue scoring models; receiving, via the machine, content data; generating, via the machine, predicted virtue score data associated with the content data for each of the plurality of virtue scoring models; and facilitating display, via the content analysis control panel and in accordance with the customization data, the predicted virtue score data associated with the content data for each of the plurality of virtue scoring models.

What is claimed is: 
     
         1 . A method comprising:
 generating, via a machine that includes at least one processor and a non-transitory machine-readable storage medium and utilizing a graphical user interface, a content analysis control panel;   receiving, via the machine, customization data that indicates a plurality of virtue scoring models, and presentation parameters associated with the plurality of virtue scoring models;   receiving, via the machine, content data;   generating, via the machine, predicted virtue score data associated with the content data for each of the plurality of virtue scoring models; and   facilitating display, via the content analysis control panel and in accordance with the customization data, the predicted virtue score data associated with the content data for each of the plurality of virtue scoring models.   
     
     
         2 . The method of  claim 1 , wherein the plurality of virtue scoring models include a plurality of artificial intelligence (AI) models that are each trained based on survey data to generate portions of the predicted virtue score data indicating a corresponding one of a plurality of scores. 
     
     
         3 . The method of  claim 2 , wherein the plurality of AI models includes a responsibility model and the plurality of scores includes a responsibility score that is based on an amount the content data addresses legal or ethical principles. 
     
     
         4 . The method of  claim 2 , wherein the plurality of AI models includes an equitability model and the plurality of scores includes an equitability score that is based on an amount of bias in the content data. 
     
     
         5 . The method of  claim 2 , wherein the plurality of AI models includes a reliability model and the plurality of scores includes a reliability score that indicates variations in others of the plurality of scores. 
     
     
         6 . The method of  claim 2 , wherein the plurality of AI models includes an explainability model and the plurality of scores includes an explainability score associated with the content data. 
     
     
         7 . The method of  claim 2 , wherein the plurality of AI models includes a morality model and the plurality of scores includes a morality score associated with the content data. 
     
     
         8 . The method of  claim 2 , further comprising:
 generating improvement data associated with at least one of the plurality of scores.   
     
     
         9 . The method of  claim 1 , wherein the content data is an Artificial Intelligence (AI) model. 
     
     
         10 . The method of  claim 1 , wherein the presentation parameters includes a customized selection of at least one of: at least one statistic, at least one chart, or at least one graph. 
     
     
         11 . The method of  claim 1 , further comprising:
 displaying, via the content analysis control panel and in accordance with the customization data, of at least one of: at least one protected attribute, or at least one key performance indicator.   
     
     
         12 . The method of  claim 1 , further comprising:
 facilitating selection of the content data from at least one of: an AI model, or a content source.   
     
     
         13 . The method of  claim 1 , further comprising:
 generating, based on user input, survey data corresponding to a survey;   collecting survey results data in response to the survey; and   facilitating generation of a custom virtue scoring model of the plurality of virtue scoring models.   
     
     
         14 . A system comprises:
 a network interface configured to communicate via a network;   at least one processor;   a non-transitory machine-readable storage medium that stores operational instructions that, when executed by the at least one processor, cause the at least one processor to perform operations that include:
 generating, via the at least one processor and utilizing a graphical user interface, a content analysis control panel; 
 receiving, via the at least one processor, customization data that indicates a plurality of virtue scoring models, and presentation parameters associated with the plurality of virtue scoring models; 
 receiving, via the at least one processor, content data; 
 generating, via the at least one processor, predicted virtue score data associated with the content data for each of the plurality of virtue scoring models; and 
 facilitating display, via the content analysis control panel and in accordance with the customization data, the predicted virtue score data associated with the content data for each of the plurality of virtue scoring models. 
   
     
     
         15 . The system of  claim 14 , wherein the plurality of virtue scoring models include a plurality of artificial intelligence (AI) models that are each trained based on survey data to generate portions of the predicted virtue score data indicating a corresponding one of a plurality of scores. 
     
     
         16 . The system of  claim 15 , wherein the plurality of AI models includes a responsibility model and the plurality of scores includes a responsibility score that is based on an amount the content data addresses legal or ethical principles. 
     
     
         17 . The system of  claim 15 , wherein the plurality of AI models includes an equitability model and the plurality of scores includes an equitability score that is based on an amount of bias in the content data. 
     
     
         18 . The system of  claim 15 , wherein the plurality of AI models includes a reliability model and the plurality of scores includes a reliability score that indicates variations in others of the plurality of scores. 
     
     
         19 . The system of  claim 15 , wherein the plurality of AI models includes an explainability model and the plurality of scores includes an explainability score associated with the content data. 
     
     
         20 . The system of  claim 15 , wherein the plurality of AI models includes a morality model and the plurality of scores includes a morality score associated with the content data.