Abstract: A system and method are provided of minimizing network bandwidth used from an external network by client peers in a local network. The method can include the operation of organizing a plurality of clients each having media streamlets and a client parent in a structure within the local network. Mapping information propagates through the structure. The mapping information represents local streamlet locations as stored by the plurality of clients. Another operation is retrieving a local streamlet from a client identified in the mapping information as having the local streamlet for the requesting client.

Abstract: A system and method are provided of minimizing network bandwidth used from an external network by client peers in a local network. The method can include the operation of organizing a plurality of clients each having media streamlets and a client parent in a structure within the local network. Mapping information propagates through the structure. The mapping information represents local streamlet locations as stored by the plurality of clients. Another operation is retrieving a local streamlet from a client identified in the mapping information as having the local streamlet for the requesting client.

Abstract: A system and method are provided of minimizing network bandwidth used from an external network by client peers in a local network. The method can include the operation of organizing a plurality of clients each having media streamlets and a client parent in a structure within the local network. Mapping information propagates through the structure. The mapping information represents local streamlet locations as stored by the plurality of clients. Another operation is retrieving a local streamlet from a client identified in the mapping information as having the local streamlet for the requesting client.

Abstract: A system and method are provided of minimizing network bandwidth used from an external network by client peers in a local network. The method can include the operation of organizing a plurality of clients each having media streamlets and a client parent in a structure within the local network. Mapping information propagates through the structure. The mapping information represents local streamlet locations as stored by the plurality of clients. Another operation is retrieving a local streamlet from a client identified in the mapping information as having the local streamlet for the requesting client.

Abstract: A processing device is to: identify, using digital interview data of interviewees captured during interviews, a subset of the interviewees that have a disability; label a first group of the interviewees as disabled and a second group of the interviewees as not disabled with reference to the disability; identify features from the digital interview data for the first group that correlate with the disability; formulate a digital fingerprint of the features that identifies how the first group differs from the second group with reference to the disability; map the digital fingerprint of the features onto a dataset of an interviewee belonging to the second group of the interviewees, to generate a mapped dataset; and determine, from the mapped dataset, effects of the digital fingerprint on a job performance score for the interviewee.

Abstract: A system and method are provided of minimizing network bandwidth used from an external network by client peers in a local network. The method can include the operation of organizing a plurality of clients each having media streamlets and a client parent in a structure within the local network. Mapping information propagates through the structure. The mapping information represents local streamlet locations as stored by the plurality of clients. Another operation is retrieving a local streamlet from a client identified in the mapping information as having the local streamlet for the requesting client.

Abstract: A computing system includes a processing device to execute instructions to: store a trained modeling function that embodies a correlation between historical ratings and historical evaluation results of recorded responses that were responsive to prompts presented to a set of persons; receive a request to initiate a digital evaluation process for a second person; receive recorded responses of the second person that are responsive to the prompts; generate, by applying the trained modeling function to the recorded responses of the second person, a reviewing sequence by which to view the recorded responses of the second person. The reviewing sequence orders the recorded responses from a most predictive prompt to a least predictive prompt to reduce a time required to efficiently determine an evaluation result. The system further transmits data that causes display of a list of the recorded responses of the second person in the reviewing sequence.

Abstract: A processing device is to: receive a request to create a tiered evaluation comprising a plurality of tiers to group candidates by competency; generate a first tier of the plurality of tiers with a first criteria comprising a first range of assessment scores; send a first candidate assessment; receive first assessment data of the first candidate profile captured during the first candidate assessment; generate a first assessment score associated with the first candidate profile from the first assessment data; determine that the first candidate profile satisfies the first criteria by at least determining that the first range of assessment scores comprises the first assessment score; responsive to determining that the first candidate profile satisfies the first criteria, place the first candidate profile in the first tier; and send tiered assessment data comprising the first tier with the first candidate profile.

Abstract: A method for detecting bias in an evaluation process is provided. The method includes operations of receiving evaluation data from a candidate evaluation system. The evaluation data is provided by a set of evaluators based on digital interview data collected from evaluation candidates. The operations of the method further include extracting indicators of characteristics of the evaluation candidates from the digital interview data, classifying the evaluation candidates based on the indicators extracted from the digital interview data, and determining whether the evaluation data indicates a bias of one or more evaluators with respect to a classification of the evaluation candidates.

Abstract: Described are methods and systems for interview competency and question validation and analysis to improve the effectiveness of evaluation campaigns. In one method, processing logic of an interview design program, hosted by a digital evaluation platform, receives a request from a first device to create a digital interview for a position. The interview design program sends a list of competencies associated with the position and receives a selection of a set of desired competencies. The interview design program determines a list of questions that differentiate candidates within the desired competencies, ranks the list of questions by importance, and sends the list of questions and the ranking information to the first device and receives a selection of a set of desired questions. The interview design program creates the digital interview with the set of desired questions. The digital evaluation platform presents the digital interview to a candidate on a second device.

Abstract: A computing system includes a processing device to execute instructions to: store a trained modeling function that embodies a correlation between historical ratings and historical evaluation results of recorded responses that were responsive to prompts presented to a set of persons; receive a request to initiate a digital evaluation process for a second person; receive recorded responses of the second person that are responsive to the prompts; generate, by applying the trained modeling function to the recorded responses of the second person, a reviewing sequence by which to view the recorded responses of the second person. The reviewing sequence orders the recorded responses from a most predictive prompt to a least predictive prompt to reduce a time required to efficiently determine an evaluation result. The system further transmits data that causes display of a list of the recorded responses of the second person in the reviewing sequence.

Abstract: Technology for training a predictive model is described. A processing device collects digital interview data including features identified from candidate interviews. A model training tool selects a data set of the digital interview data. The data set includes a predicted performance outcome and an actual performance outcome for each of a plurality of candidates. The model training tool determines an error metric for each of the plurality of candidates. The error metric includes a relationship between the predicted performance outcome and the actual performance outcome for each candidate. The model training tool determines a number of candidates whose digital interview data includes a feature corresponding to a protected class. The model training tool normalizes an effect of each candidate on the error metric based on the corresponding protected class and applies the normalized error metric to reduce bias in the predictive model with respect to the protected class.

Abstract: A method for facilitating the evaluation of candidates in an evaluation process is provided. The method includes operations of selecting a first data set including ratings of recorded responses of a set of evaluated persons and of selecting a second data set including additional recorded responses of a person under evaluation. The recorded responses are responsive to multiple prompts presented to each of the set evaluated persons in a recording sequence. The first data set further includes an evaluation result of each evaluated person in the evaluation. The additional recorded responses are responsive to the plurality of prompts and ordered in a first order corresponding to a recording sequence. The method includes analyzing the first data set to calculate a reviewing sequence and presenting the additional recorded responses in a second order corresponding to the reviewing sequence. Associated systems and other methods are also provided.

Abstract: Described herein are methods and systems for interview question or prompt recommendation and analysis to improve the quality and efficacy of subsequent evaluation campaigns by combining data sets are described herein. In one method, processing logic selects a first prompt from a first data set of a first candidate evaluation campaign and a second prompt from a second data set of a second candidate evaluation campaign. The processing logic determines whether a degree of similarity between the first prompt and the second prompt exceeds a threshold and combines data from the first data set with data from the second data set to create a combined data set associated with the first prompt and with the second prompt based on the determination.

Abstract: A processing device is to: identify, using digital interview data of interviewees captured during interviews, a subset of the interviewees that have a disability; label a first group of the interviewees as disabled and a second group of the interviewees as not disabled with reference to the disability; identify features from the digital interview data for the first group that correlate with the disability; formulate a digital fingerprint of the features that identifies how the first group differs from the second group with reference to the disability; map the digital fingerprint of the features onto a dataset of an interviewee belonging to the second group of the interviewees, to generate a mapped dataset; and determine, from the mapped dataset, effects of the digital fingerprint on a job performance score for the interviewee.

Abstract: Described herein are methods and systems for interview question or prompt recommendation and analysis to improve the quality and efficacy of subsequent evaluation campaigns by combining data sets are described herein. In one method, processing logic selects a first prompt from a first data set of a first candidate evaluation campaign and a second prompt from a second data set of a second candidate evaluation campaign. The processing logic determines whether a degree of similarity between the first prompt and the second prompt exceeds a threshold and combines data from the first data set with data from the second data set to create a combined data set associated with the first prompt and with the second prompt based on the determination.

Abstract: Technology for training a predictive model is described. A processing device collects digital interview data including features identified from candidate interviews. A model training tool selects a data set of the digital interview data. The data set includes a predicted performance outcome and an actual performance outcome for each of a plurality of candidates. The model training tool determines an error metric for each of the plurality of candidates. The error metric includes a relationship between the predicted performance outcome and the actual performance outcome for each candidate. The model training tool determines a number of candidates whose digital interview data includes a feature corresponding to a protected class. The model training tool normalizes an effect of each candidate on the error metric based on the corresponding protected class and applies the normalized error metric to reduce bias in the predictive model with respect to the protected class.

Abstract: A method for facilitating the evaluation of candidates in an evaluation process is provided. The method includes operations of selecting a first data set including ratings of recorded responses of a set of evaluated persons and of selecting a second data set including additional recorded responses of a person under evaluation. The recorded responses are responsive to multiple prompts presented to each of the set evaluated persons in a recording sequence. The first data set further includes an evaluation result of each evaluated person in the evaluation. The additional recorded responses are responsive to the plurality of prompts and ordered in a first order corresponding to a recording sequence. The method includes analyzing the first data set to calculate a reviewing sequence and presenting the additional recorded responses in a second order corresponding to the reviewing sequence. Associated systems and other methods are also provided.

Abstract: A method for detecting bias in an evaluation process is provided. The method includes operations of receiving evaluation data from a candidate evaluation system. The evaluation data is provided by a set of evaluators based on digital interview data collected from evaluation candidates. The operations of the method further include extracting indicators of characteristics of the evaluation candidates from the digital interview data, classifying the evaluation candidates based on the indicators extracted from the digital interview data, and determining whether the evaluation data indicates a bias of one or more evaluators with respect to a classification of the evaluation candidates.

Abstract: A method for facilitating the evaluation of candidates in an evaluation process is provided. The method includes operations of selecting a first data set including ratings of recorded responses of a set of evaluated persons and of selecting a second data set including additional recorded responses of a person under evaluation. The recorded responses are responsive to multiple prompts presented to each of the set evaluated persons in a recording sequence. The first data set further includes an evaluation result of each evaluated person in the evaluation. The additional recorded responses are responsive to the plurality of prompts and ordered in a first order corresponding to a recording sequence. The method includes analyzing the first data set to calculate a reviewing sequence and presenting the additional recorded responses in a second order corresponding to the reviewing sequence. Associated systems and other methods are also provided.