Systems and methods for providing performance feed-back and experiential learning systems

Abstract

A system for providing trusted performance feedback and experiential learning is disclosed. The system may include receiving, from a first user, feedback related to a second user's benefit regarding the second user's participation in an event. The system may assign information to avatars of the first user and the second user. To ensure that information of a user remains dedicated to the user, the avatar may be an anonymized virtual representation of the first user and the second user within a virtual social network. Based on analysis of the information, the system may generate conditional state data for the avatars of the first user and the second user, respectively. The conditional state data may be a time series variable representing a relationship of the avatar. Based on the conditional state data, the system may provide recommendations or reports to the second user for improving benefit of the second user in future events.

Description

(19) State Intellectual Property Office (12) Invention Patent Application (10) Application Publication Number (43) Application Publication Date (21) Application Number 202511382048.8 (22) Application Date 2020.08.07 (30) Priority Data 62 / 884,877 2019.08.09 US (62) Divisional Application Data 202080070254.4 2020.08.07 (71) Applicant Forward Impact Enterprises LLC Address USA (72) Inventors James K. Haji James Gibbons (74) Patent Agency Beijing Taiji Intellectual Property Agency Co., Ltd. 11355 Patent Attorney Shi Tong Lü Zijing (51) Int.Cl. G06F 16 / 9536 (2019.01) G09B 19 / 00 (2006.01) G09B 7 / 00(2006.01) G06F 16 / 9535(2019.01) G06Q 50 / 00(2024.01) G06F 16 / 9537(2019.01) (54) Title of Invention: System and Method for Providing Performance Feedback and Experiential Learning (57) Abstract: Discloses a system for providing credible performance feedback and experiential learning. The system may include receiving feedback from a first user related to the benefits of a second user's participation in an event. The system may assign information to avatars of the first user and the second user. To ensure that the user's information remains dedicated to the user, the avatar may be an anonymized virtual representation of the first user and the second user within a virtual social network. Based on the analysis of the information, the system may generate conditional state data for the avatars of the first user and the second user, respectively. The conditional state data may be time-series variables representing the relationships between the avatars. Based on the conditional state data, the system may provide recommendations or reports to the second user to improve the second user's benefits in future events. Claims 4 pages, Description 36 pages, Drawings 5 ​​pages, CN 121479065 A 2026.02.06 CN 1 21 47 90 65 A 1. A system, characterized in that it comprises: a memory storing instructions; and a processor executing the instructions to perform operations, the operations comprising: generating or identifying a first avatar, the first avatar having a mapping to a first identifier, wherein the first avatar is embodied as a first computer program in the system and acts as one of a plurality of nodes in a virtual social network of the system; receiving from a first device associated with the first avatar information regarding the first avatar's participation in a...Information related to the benefits of a first virtual event in which two avatars also participate, wherein at least a portion of the information is provided by at least one sensor or input device that measures task-related activity or interaction information associated with at least one task-related activity or interaction between the first avatar and the second avatar; the information is assigned to the first avatar mapped to the first identifier, and the information assigned to the first avatar mapped to the first identifier is encoded by using a secure mapping key, wherein the first avatar is a virtual representation of the node within the virtual social network of the system, the virtual social network including the second avatar mapped to the second identifier, wherein the first avatar includes the node of the virtual social network, and the second avatar is embodied as a second computer program and includes another node of the virtual social network; by mapping the first avatar to the first identifier, virtual task-related activities or interactions between the node of the first avatar and the other node of the second avatar in the virtual social network are assisted based on task-related activities or interactions between the first computer program and the second computer program; The system generates, identifies, and stores first conditional state data for the first avatar and second conditional state data for the second avatar by using an artificial intelligence system and based on the analysis of the information and the task-related activities or interactions. The first conditional state data for the first avatar is generated at least in part based on inputs associated with the first avatar generated by the second avatar and the virtual task-related activities or interactions between the node of the first avatar and the other node of the second avatar in the virtual social network. The system provides recommendations, media content, or a combination thereof to the first avatar by using the artificial intelligence system and based on the first conditional state data for the first avatar. These recommendations, media content, or combinations thereof are related to the likelihood of improving the first avatar's effectiveness regarding a first future event in which the second avatar participates, a second future event in which the second avatar does not participate, or a combination thereof. The recommendations, media content, first conditional state data, or combinations thereof are accessible to the first avatar using the secure mapping key. Based on the recommendations, media content, or combinations thereof, the system receives feedback from a user related to enhancing the effectiveness of the first avatar in at least one task-related activity or interaction in the first future event, the second future event, or a combination thereof. The artificial intelligence system is trained based on feedback from the user relating to the effectiveness of enhancing the first avatar's task-related activities or interactions in the first future event, the second future event, or a combination thereof; and new suggestions are provided to the first avatar by using the artificial intelligence system trained based on the feedback.1. A system according to claim 1, wherein the information associated with the benefits of the first avatar includes data collected through surveillance technology, data associated with transportation, logistics, operations, inventory management, or guidance systems, data associated with audio content, data associated with video content, data associated with text analysis, data associated with a global positioning system, data associated with a biometric dataset, or a combination thereof. 2. A system according to claim 1, wherein the operation further includes ensuring the information associated with the first avatar, wherein the privacy is ensured at least in part through confidential computing technology, a trusted execution environment, a system for protecting privacy, a mapping from the first avatar to the first identifier, or a combination thereof. 3. A system according to claim 1, wherein the user includes a program, a simulated robot, a robot, a drone, a wearable device, a function, a process, a device, or a combination thereof. 5. The system of claim 1, wherein the first virtual event is associated with a plurality of virtual events, or wherein the plurality of virtual events are organized into event types, projects, project types, organizations, organization types, or combinations thereof. 6. The system of claim 1, wherein the operation further includes providing the information to a third-party user, wherein the information and data are provided anonymously or non-anonymously. 7. The system of claim 6, wherein the third-party user is a subscriber to a plan, an account, or a combination thereof. 8. The system of claim 1, wherein the operation further includes maintaining the quality of data associated with the information, the quantity of data associated with the information, or a combination thereof, wherein the information is provided to or obtained from the first avatar, the second avatar, or a combination thereof. 9. The system of claim 1, wherein the operation further includes determining the quantity of feedback to determine the quantity of received feedback, the type of received feedback, or a combination thereof. 10. The system of claim 1, wherein the operation further includes summarizing the information and other data, wherein the summarized information and the other data are provided to a first user, a second user, a third user, or a combination thereof. 11. The system of claim 1, wherein the operation further comprises deleting the information from the mapping server used to assist in assigning the information to the first avatar after assigning the information to the first avatar mapped to the first identifier. 12. The system of claim 1, wherein the first conditional state data further comprises a self-assessment.The system may include, but is not limited to, estimated or self-developed data, a complete or partial history of all events, a representation of a portion of the network connections of the first avatar, the second avatar, and other avatars, avatar identifiers, tables of events and event reports, tables of connected avatar identifiers and task-related activities or interactions, or combinations thereof. 13. The system of claim 1, wherein the operation further comprises processing the first conditional state data as at least one input using the artificial intelligence system and projecting it onto a first conditional state type as at least one output to classify the needs of the first user, the interests of the first user, media content to be presented to the first user, connection options to be presented to the first user, or combinations thereof, and / or wherein the operation further comprises processing the second conditional state data as at least one input using the artificial intelligence system and projecting it onto a second conditional state type as at least one output to classify the needs of the second user, the interests of the second user, media content to be presented to the second user, or combinations thereof. 14. The system of claim 13, wherein the operation further comprises mapping the first conditional state type to a first interest state by using the artificial intelligence system, and / or wherein the operation further comprises mapping the second conditional state type to a second interest state. 15. The system of claim 14, wherein the first interest state, the second interest state, or a combination thereof comprises environmental state variables, organizational state variables, leadership activity variables, behavioral variables, task-related activity variables, interaction variables, relationship variables, social network variables, communication variables, attitude variables, emotional state variables, cognitive state variables, ability variables, knowledge variables, management activity variables, or a combination thereof. 16. The system of claim 1, wherein the operation further comprises using a first secure mapping key to protect the relationship between the first identifier and the first avatar, and wherein the operation further comprises using a second secure mapping key to protect the relationship between the second identifier and the second avatar. 17. A method, characterized in that it comprises: generating or identifying a first avatar, the first avatar having a mapping to a first identifier, wherein the first avatar is embodied as a first computer program in a system and acts as one of a plurality of nodes in a virtual social network of the system; transmitting a query to a first device associated with the first avatar, wherein the query request relates to information concerning the benefit of the first avatar's participation in a first virtual event in which a second avatar also participates; obtaining from the first device associated with the first avatar information concerning the first avatar's participation in...The information related to the benefits of the first virtual event in which the second avatar also participates, and the information assigned to the first avatar mapped to the first identifier by using a secure mapping key, wherein at least a portion of the information is provided by at least one sensor, the at least one sensor measuring task-related activity or interaction information associated with at least one task-related activity or interaction between the first avatar and the second avatar; associating the information with the first avatar mapped to the first identifier of the first avatar, wherein the first avatar is a virtual representation of the node in the system's virtual social network, the virtual social network including the second avatar mapped to the second identifier of the second avatar, wherein the first avatar includes the node of the virtual social network, and the second avatar is embodied as a second computer program and includes another node of the virtual social network; by mapping the first avatar to the first identifier, assisting the node of the first avatar and the other node of the second avatar in the virtual social network with virtual task-related activities or interactions in the virtual social network based on task-related activities or interactions between the first computer program and the second computer program; The system generates or identifies and stores first conditional state data for the first avatar and second conditional state data for the second avatar by using an artificial intelligence system and based on the analysis of the information and the task-related activities or interactions. The first conditional state data for the first avatar is generated at least in part based on inputs associated with the first avatar generated by the second avatar and the virtual task-related activities or interactions between the node of the first avatar and the other node of the second avatar in the virtual social network. The system provides recommendations, media content, or a combination thereof to the first avatar by using the artificial intelligence system and based on the first conditional state data for the first avatar, to improve the first avatar's benefit regarding a first future event in which the second avatar will participate, a second future event in which the second avatar is not present, or a combination thereof. The recommendations, media content, first conditional state data, or a combination thereof are accessed using the secure mapping key. Based on the recommendations, media content, or a combination thereof, the system receives feedback from a user related to enhancing the first avatar's benefit in at least one task-related activity or interaction in the first future event, the second future event, or a combination thereof. The artificial intelligence system is trained based on feedback from the user relating to enhancing the effectiveness of the first avatar's task-related activities or interactions in the first future event, the second future event, or a combination thereof; and new suggestions are provided to the first avatar by using the artificial intelligence system trained based on the feedback. (Claims 3 / 4 pages 4 CN)121479065 A Recommendation, new media content, or a combination thereof, for the purpose of enhancing the effectiveness of the first avatar in a third future event. 18. The method of claim 17, further comprising using a machine to determine relative weights for the information to be used in the analysis. 19. The method of claim 17, wherein the information related to the effectiveness of the first avatar includes preparation information, authenticity information, clarification information, evidence information, relevance information, respect information, public information, contribution information, participation information, credibility information, value information, any attribute information, any effectiveness information, or a combination thereof. 20. A non-transitory computer-readable device, characterized in that it includes instructions, which, when loaded by a processor and executed, cause the processor to perform operations including: generating or identifying a first avatar, the first avatar having a mapping to a first identifier, wherein the first avatar is embodied as a first computer program in a system and acts as one of a plurality of nodes in a virtual social network of the system; generating a query to a first device associated with the first avatar, wherein the query request relates to information concerning the benefit of the first avatar's participation in a first virtual event in which a second avatar also participates; receiving from the first device associated with the first avatar the information concerning the benefit of the first avatar's participation in the first virtual event in which the second avatar also participates, wherein at least a portion of the information is provided by at least one sensor, the at least one sensor measuring task-related activity or interaction information associated with at least one task-related activity or interaction between the first avatar and the second avatar; The information is associated with the first avatar mapped to the first identifier of the first avatar, and the information assigned to the first avatar mapped to the first identifier is encoded by using a secure mapping key, wherein the first avatar is a virtual representation of the node within the virtual social network of the system, the virtual social network including the second avatar mapped to the second identifier of the second avatar, wherein the first avatar includes the node of the virtual social network, and the second avatar is embodied as a second computer program and includes another node of the virtual social network; by mapping the first avatar to the first identifier, virtual task-related activities or interactions between the node of the first avatar and the other node of the second avatar in the virtual social network are assisted based on task-related activities or interactions between the first computer program and the second computer program; first conditional state data for the first avatar and second conditional state data for the second avatar are provided based on the analysis of the information and the task-related activity or interaction information;The AI ​​system generates recommendations, media content, or combinations thereof for the first avatar using an artificial intelligence system and at least based on the first conditional state data for the first avatar, to improve the first avatar's effectiveness in a first future event in which the second avatar will participate, a second future event in which the second avatar is not present, or a combination thereof, wherein the recommendations, media content, the first conditional state data, or the combination thereof are accessed using the secure mapping key; receives feedback from a user based on the recommendations, media content, or the combination thereof related to enhancing the effectiveness of the first avatar in at least one task-related activity or interaction in the first future event, the second future event, or the combination thereof; trains the AI ​​system based on the feedback from the user related to enhancing the effectiveness of the first avatar in at least one task-related activity or interaction in the first future event, the second future event, or the combination thereof; and provides new recommendations, new media content, or combinations thereof for the first avatar using the AI ​​system trained based on the feedback to improve the first avatar's effectiveness in a third future event. Claims 4 / 4 pages 5 CN 121479065 A System and method for providing performance feedback and experiential learning

[0001] This application is a divisional application of International Application No. PCT / US2020 / 045460, International Application Date: August 7, 2020, Entering China National Phase Date: April 7, 2022, National Application No. 202080070254.4, entitled "System and method for providing performance feedback and experiential learning". Cross-Reference to Related Applications

[0002] This application claims priority and benefit to U.S. Provisional Patent Application No. 62 / 884,877, filed August 9, 2019, which is hereby incorporated by reference. Technical Field

[0003] This application relates to data analysis and feedback technology, interactive communication technology, sensor technology, mobile device technology, distributed ledger technology, monitoring technology, organizational behavior technology, optimization technology, machine learning technology, and more specifically, to systems and methods for providing credible performance feedback and experiential learning while ensuring that user data remains dedicated to the user. Background Art

[0004] In today's society, effective team and multi-team system collaboration and interaction are essential to improve and maintain business outcomes, project goals, and countless other situations involving group interactions. In the current work environment, individuals, particularly but not limited to collaborators, employees, or contractors at work levels within an organization, often find it difficult to obtain objective, personalized, and timely feedback, guidance, and coaching, or to translate this into personal perceptions of their experiences following meetings, events, or other social interactions.The context-dependent, practically feasible insights into the level of contribution and participation are crucial for receiving and benefiting from academic and practical knowledge to improve management and self-monitoring skills. This is particularly evident in, but not limited to, interactions mediated or enhanced by technology. Furthermore, existing methods of providing and / or generating feedback are not situation-specific or based on all available relevant data and may be biased. Moreover, human interactions are increasingly mediated or enhanced by technology and occur at increasingly higher relative frequencies over long distances. This reduces the availability of social and emotional cohorts that can be used to build self-monitoring skills and emotional intelligence.

[0005] Current methods for obtaining feedback and improving business outcomes, project goals, etc., involve the use of periodically standardized survey tools or specific and sporadic personal feedback from managers. This problem has become more pronounced in recent years due to the increasing use of technology-mediated communication. One approach involves the use of typical human resources surveys, such as 360-degree feedback surveys. Such surveys are distributed only periodically, are general and lack situation-specific content, and personal feedback from said surveys is often delayed. Furthermore, because these surveys are often used for performance evaluations and compensation, they are susceptible to manipulation and self-serving biases. As another example, feedback from supervisors or mentors may be specific, often biased, and only occasionally received when managers meet with employees, perhaps as rarely as once a year, or sometimes even less. In these situations, managers typically have very little objective data beyond their own personal observations, which may be biased by the manager's personal history, and managers have little or no opportunity to conduct expert analysis on the limited amount of data available. In short, traditional surveys are too infrequent and too general to be feasible because the feedback is difficult to interpret. Similarly, one-on-one feedback is specific and based on limited personal observations, which may be biased. None of these existing methods address the problem of fostering timely self-awareness among individuals regarding the benefits of organized activities such as work or community activities such as meetings and events.

[0006] While current techniques and methods offer many benefits and advantages, they also have many drawbacks. Specifically, current versions of such techniques generally provide limited ways to process and analyze feedback in order to meaningfully improve individual performance over time. Furthermore, current techniques do not encourage or promote accurate and honest feedback from individuals. Furthermore, following meetings, projects, social gatherings, and / or other interactive situations, current technologies fail to provide timely feedback, guidance, and / or coaching regarding an individual's perceived contribution and level of engagement, thus hindering the improvement of an individual's management and self-monitoring skills. Therefore, current methods and technologies associated with improving interactions between and / or between individuals and / or devices can be modified and / or...Or enhancements, to provide enhanced and optimized feedback to such individuals and / or devices. Such enhancements and improvements to methods and techniques can provide improved team and multi-team system optimization and collaboration, increased privacy, increased adherence to team goals, reduced failure rates in team and / or social interactions, reduced costs, and increased ease of use. Summary of the Invention

[0007] A system and accompanying method are disclosed for providing technically supported, credible performance feedback, experiential learning for individuals, and organizational status data for management analysis and simulation. Specifically, the system and method provide a software platform to assist in obtaining high-quality feedback, which can be analyzed and enhanced to provide reports and / or recommendations to users to improve organizational performance and user performance in interactive scenarios, such as, but not limited to, team-based projects, multi-team systems, social interactions, workgroups at work, any other interactive scenarios, or combinations thereof. Notably, the system and method may include multiple components to provide technically supported, credible performance feedback and experiential learning. In some embodiments, the system and accompanying method may include multiple parts that provide functionality of the system and method. Specifically, the system and method may include components and subsystems for collecting feedback information from users regarding the performance and individual contributions of other users. Based on the collected performance and feedback information and / or data, the system and method may include components and subsystems for summarizing and analyzing contextual and / or feedback data in an anonymous and secure data environment. Based on the summarized and analyzed contextual and / or feedback data, the system and method may include components and subsystems that provide users with analyses and / or questions to assist them in reflective thinking, and / or, but not limited to, suggestions, guidance services, and / or coaching services from human experts, machine learning algorithms and systems, simulations, and / or artificial intelligence algorithms and / or systems.

[0008] Specifically, the system and method may include a feedforward subsystem (FFSS), which may be configured to, for example, collect contextual information from multiple users, including but not limited to self-assessment data, professional development data, personal or organizational values, goals or objectives, organizational status data, environmental status data, and / or social interaction network structure data. In some embodiments, FFSS may also be configured to collect social, emotional intelligence, and / or competence data related to dynamic social interactions and information influencing relationships between individuals before, during, or after meetings, conversations, and / or other events, as well as content- and situation-specific factors and conditions. In addition to FFSS, the system and method may also include a secure data aggregation and analysis subsystem (sDAASS), which in some embodiments may be configured to...Data is received from FFSS in an anonymous and secure manner. The sDAASS can be configured, but is not limited to, to evaluate various situations using various techniques in the case of stored or separately acquired data for a user interface (UI) or application programming interface (API), such as, but not limited to, human or machine simulation, virtual reality (VR), augmented reality (AR), and / or gamified environments (GE), such as, but not limited to, data analytics techniques (DAT), machine intelligence (e.g., but not limited to machine learning and artificial intelligence), and / or human expertise (HE) and intelligence.

[0009] In addition to FFSS 302 and sDAASS 306, the system and method may also include a guidance forwarding subsystem specification 2 / 36 pages 7 CN 121479065 A (CFSS), which can be configured to determine and recommend appropriate feedback for at least one user. In some embodiments, the feedback may include guidance or coaching suggestions to improve performance and may include, but is not limited to, the use of a technology interface, such as, but not limited to, smartphones, wearable technologies, laptops, and / or other computer or telecommunications devices. In some embodiments, the feedback may also involve face-to-face dialogue, the content of which may be provided by FFSS and / or sDAASS as discussed herein. The system and method may further include a secure mapping server (MS). Notably, to ensure confidentiality and to prevent and / or deter hacking, all data transmitted between various subsystems may be passed via secure connections and / or processed on the MS 304. In some embodiments, the MS may be isolated or otherwise secure; however, in other embodiments, the MS may not be isolated but may still be configured to be secure. In some embodiments, on the MS, each user in this data may be uniquely identified using a different avatar and encoded using a stored secure mapping key (e.g., by utilizing a blockchain, some other secure ledger, and / or other technologies) but not limited to using a secure encryption algorithm. The data contains the correlation of each user with multiple interactions with other users, including but not limited to historical or current interactions. In some embodiments, the allocation key between the user and the avatar can remain fully secure and anonymous, while also allowing for various types of data analysis performed by human and / or machine programs, as well as the ability to target media, content, or guidance recommendations identified as related to the avatar and therefore to the relevant real user, while maintaining the anonymity of each user to every other individual without the user's explicit authorization. System 100 and method may further include user interfaces and application programming interfaces that enable the system and method to also interact with and exchange data with third-party applications.

[0010] The system and method may also allow the following situations: before, after, or even during an event, the systemThe system recognizes that the event of interest is scheduled, ongoing, or has concluded. This can trigger the system to construct queries specific to each user who will participate in, is participating in, or has already participated in the event. The system then sends notifications via query links to users who will participate in the event (e.g., notifications may relate to self-assessment, goals, and / or expectations of the event), users who are participating in the event (e.g., notifications may relate to the relevance of agenda items associated with the event), and / or users who have already participated in the event. When a user responds to a query, the system collects feedback from each individual user regarding the contributions and participation of all other users in the event and their perceptions of the team, multi-team system, organization, and / or its leadership. The system may then encrypt, but not necessarily anonymize, the user's identity, and, for anonymity purposes, erase all user identification information associated with the user's feedback from the user's device. When and if there are sufficient responses to guarantee anonymity, the system aggregates this data, and may have additional relevant data from other sources (including its own database or user input during contextual analysis). The system then processes this data, analyzes the results to identify relevant patterns, and generates reports. These reports are relayed to managers, analysts, and / or experts—humans, machines, or other forms of artificial intelligence—to diagnose problems and propose interventions based on their expertise. The system then sends customized data, an analysis of his or her performance, to each individual user. The system may also provide guidance or coaching suggestions in the form of recommended articles or media to change behavior, communication, or emotions, or to recommend additional training or knowledge acquisition. This may include previously created and transcribed streaming media, text, photos, or videos identified as relevant to the situation. The system may also involve scheduling individual one-on-one sessions with a professional mentor (whether human or machine) and may be anonymous or not. All of these approaches can be used to improve management and self-monitoring skills.

[0011] It is noteworthy that the system and methods address problems associated with the prior art because individual-level data is collected before, during, and / or after some or many events (if not every event) and contains specific information about the content and circumstances of said events. All historical and situational data can be used for analysis to determine personalized feedback about a user's performance in an event shortly after each social interaction. Because this data is anonymous and secure (see page 3 / 36 of the specification, CN 121479065 A), there is no incentive to manipulate this data collection, as it can never be used for performance evaluation or compensation except at the group or organizational level. Furthermore, the stored data itself is a source of added value. The stored data provides a resource whose…Used to compare outcomes between organizational entities and to systematically learn which are effective and which are ineffective using state-of-the-art data analytics techniques. Over time, the system itself will learn how to provide effective guidance and coaching feedback in many situations. Furthermore, this dataset will provide resources for social science researchers, and the system provides possible experimental designs to further understand social interactions and organizational benefits.

[0012] In one embodiment, a system is provided for providing technically supported, credible performance feedback and experiential learning. The system may include a memory storing instructions and a processor executing the instructions to perform various operations of the system. The system is capable of performing operations including receiving information from a first user device associated with a first user related to the benefits of a second user's participation in an event in which the first user also participates. Additionally, the system is capable of performing operations including assigning information related to the benefits of the second user to a first avatar mapped to a first user identifier of the first user and / or a second avatar mapped to a second user identifier of the second user. In some embodiments, the first and second avatars may be anonymized virtual representations of the first and second users within the system's virtual social network. Furthermore, the system can perform operations including generating first conditional state data for a first avatar and second conditional state data for a second avatar based on analysis of the information. In some embodiments, the first and second conditional state data may be time-series variables for time instances or multiple time instances, the time-series variables may contain a representation of the relationship between the first and second avatars in the system's virtual social network. Furthermore, the system can perform operations including providing reports, recommendations, or a combination thereof to a second user based at least on the second conditional state data for the second avatar and / or the first conditional state data for the first avatar, for the purpose of improving the second user's benefit regarding their participation in future events.

[0013] In another embodiment, a method is provided for providing a technically supported, credible performance feedback and experiential learning system. The method may include utilizing a memory that stores instructions and a processor that executes the instructions to perform various functions of the method. The method may include transmitting a query to a first user device associated with a first user. In some embodiments, the query request relates to information for the second user regarding their benefit from participating in events in which the first user also participates. Additionally, the method may include obtaining information from a first user device associated with a first user that relates to the benefits of a second user's participation in an event in which the first user also participates. Furthermore, the method may include linking the information with a first avatar mapped to a first user identifier assigned to the first user and / or a second avatar mapped to the second user.A second avatar of a user identifier is associated. In some embodiments, the first and second avatars may be anonymized virtual representations of the first and second users within a virtual social network of the system supporting the functionality of the method. Furthermore, the method may include generating first conditional state data for the first avatar and second conditional state data for the second avatar based on analysis of the information. In some embodiments, the first and second conditional state data may be time-series variables for time instances or multiple time instances, the time-series variables representing the relationship between the first and second avatars in the virtual social network of the system. Furthermore, the method may include providing a report, recommendation, or a combination thereof to a second user based at least on the first conditional state data for the first avatar and / or the second conditional state data for the second avatar, to improve the second user's benefit regarding their participation in future events.

[0014] According to yet another embodiment, a computer-readable device is provided having instructions for providing a credible performance feedback and experiential learning system for technical support. When loaded and executed by a processor, computer instructions cause the processor to perform operations including: generating a query for a first user device associated with a first user, wherein the query request relates to information for a second user regarding the benefits of the second user's participation in an event in which the first user also participates; and retrieving information from page 4 / 36 of the specification (CN 121479065 A). A first user device associated with a user receives information related to the benefits of a second user's participation in an event in which the first user also participates; associates the information with a first avatar mapped to a first user identifier of the first user, wherein the first avatar is an anonymized virtual representation of the first user within a virtual social network of the system, the virtual social network containing second avatars mapped to a second user identifier of the second user; provides first conditional state data for the first avatar and second conditional state data for the second avatar based on analysis of the information, wherein the first and second conditional state data are time series variables for time instances or multiple time instances, the time series variables representing the relationship between the first and second avatars in the virtual social network of the system, etc.; and generates reports, recommendations, or combinations thereof for the second user, at least based on the second conditional state data for the second avatar, to improve the second user's benefits regarding their participation in future events.

[0015] These and other features of systems and methods for providing technically supported, credible performance feedback and experiential learning are described in the following detailed description and figures.

[0016] FIG1 is a schematic diagram of a system for providing credible performance feedback and experiential learning for technical support, according to an embodiment of the present disclosure.

[0017] Figure 2 is a schematic diagram illustrating additional components for supporting the functionality of the system of Figure 1 according to embodiments of the present disclosure.

[0018] Figure 3 is a schematic diagram illustrating various subsystems for supporting and providing the functionality of the system of Figure 1 according to embodiments of the present disclosure.

[0019] Figure 4 is a flowchart illustrating a sample method for providing technical support, credible performance feedback, and experiential learning according to embodiments of the present disclosure.

[0020] Figure 5 is a schematic diagram of a machine in the form of a computer system, within which an instruction set, when executed, causes the machine to perform any one or more methods or operations for the system and methods of technical support, credible performance feedback, and experiential learning. Detailed Description

[0021] A system 100 and accompanying methods for providing technical support, credible performance feedback, and experiential learning are disclosed. Specifically, System 100 and the method provide a software platform that assists in obtaining high-quality feedback, work context information, and / or self-assessment data, which can be analyzed and enhanced to provide reports and / or recommendations to users to improve their performance in interactive situations, such as, but not limited to, team-based projects, multi-team systems, social interactions, workgroups at work, any other interactive situations, or combinations thereof, whether physical, face-to-face, and / or virtual. Notably, System 100 and the method may include multiple components to provide technically supported, credible performance feedback and experiential learning. In some embodiments, System 100 and the accompanying method may include multiple parts that provide the functionality of System 100 and the method. Specifically, System 100 and the method may include components and subsystems for collecting feedback information from users regarding the performance and individual contributions of other users. Based on the collected performance and feedback information and / or data, System 100 and the method may include components and subsystems for summarizing and analyzing contextual and / or feedback data in an anonymous and secure data environment. In some embodiments, the system and method may, but not necessarily, include security protocols that can be used for purposes of management agencies, projects, teams, events, and organizations to separate user accounts, processing, charging, social and political network analysis, and data management functions related to aggregated data from user data records created and used to give and receive feedback, and how these records are stored and used to improve the individual contributions of the user in the interactive environment. Based on conditional states identified in the aggregated and analyzed context, self-assessment, and / or feedback data, and specifically matching said conditional states, system 100 and method may include components and subsystems that provide users with reports or analyses and / or questions to assist users in reflective thinking, and / or, but not limited to, from human experts, machine learning algorithms, and systems.The system 100 and method may include suggestions, guidance services, and / or coaching services from artificial intelligence algorithms and / or systems, all of which are matched with the personalized needs or interests of each specific user through algorithms or other means.

[0022] It is worth noting that the system 100 and method may include collecting, processing, and utilizing data on social, emotional intelligence, cognitive intelligence, facial expressions, voice or voice variations, personality, influence, breadth and depth of knowledge domains, and the ability to conduct social interactions between individuals and groups, which may or may not affect individual, team, and multi-team benefits. In some embodiments, the system 100 and method may include collecting data on content and situation-specific factors and conditions, and on individual and group performance, through system user interfaces, biometric interfaces, and / or application programming interfaces. The system 100 and method, for example by utilizing FFSS 302, may collect this data from multiple users during face-to-face or technology-mediated interactions (whether synchronous or asynchronous, such as, but not limited to, meetings, work activities, conversations, and other events) through, but not limited to, voting or ranking ballots, surveys, network usage data, surveillance technologies, wearable technologies, or other means. The collected data can be aggregated, processed, and used using technology-mediated communication and computer processing, including but not limited to software user interfaces, telecommunications and database hardware and software, computing and electronic storage. Subsequently, but not necessarily, the data can be anonymized and securely transmitted to sDAASS 306, which can be a secure and anonymous environment for processing, analyzing, simulating, or visualizing using data analytics, machine intelligence, or human expert intervention, or a combination thereof. The analysis performed by sDAASS 306 can then be used by instructors, researchers, organizational analysts, managers, artificial intelligence, or machine learning algorithms to identify and / or simulate potential performance problems and opportunities for improving the effectiveness and / or performance of users, teams, multi-team systems, or organizations.

[0023] In some embodiments, based on processing, system 100 and methods can use, but are not limited to, techniques such as artificial and machine intelligence, expert systems, social simulations, computer simulations or representations, or interactions with a group of human or machine experts, or combinations thereof, to select, construct, and / or additionally determine appropriate and relevant coaching and guidance content. System 100 and methods, for example by utilizing CFSS 308, can then select and deliver descriptions, models, and / or media offering suggestions for improving the performance of individuals, groups, and / or organizations, either personally or via telecommunications networks. In some embodiments, system 100 and methods enable users to provide feedback on the usefulness of this content to the user in their context. Notably, system 100 and methods provide functionality through multiple subsystems, which together: 1) receiveThe system 100 collects social, emotional intelligence, self-assessment, self-development, and competence data on interpersonal or organizational effectiveness, but not limited to: 2) identifying areas for improvement through expert analysis, data analysis, and artificial intelligence algorithms; and 3) providing users with personalized guidance content for specific situations through technical interfaces.

[0024] In some embodiments, based on processing, the system 100 and methods may assist, but are not limited to, assisting in the selection, construction, and / or otherwise determining user accounts, subscription services, system permissions, available functionality, user access, and other characteristics (including but not limited to the structure of activities and roles in organizations, industries, functions, departments, projects, teams, and events) of interactions using, but not limited to, artificial intelligence and machine intelligence, expert systems, social simulations, computer simulations, or representations of interactions with groups of human or machine experts, or combinations thereof. System 100 and method, for example by utilizing an Account and Planning Subsystem (“A&PSS”) 310, can then personally and / or via telecommunications networks select and deliver descriptions, models, and / or media that describe or propose roles, agencies, functions, structures, social network structures, projects, teams, individuals, events, or other structures or organizational activities. In some embodiments, system 100 and method can enable users to provide feedback on the benefits of these structures to the user in their situation. Notably, system 100 and method provide functionality through multiple subsystems that together: 1) collect social, emotional intelligence, self-assessment, self-development, and competence data regarding, but not limited to, interpersonal or organizational benefits; 2) identify areas for improvement through expert analysis, data analysis, and artificial intelligence algorithms; and 3) provide users with personalized guidance content for specific situations via a technical interface, which may, but is not limited to, where the function is performed within the organization, or who has specific responsibilities or authority. System 100 may include a security protocol that, for the purpose of managing projects and organizations, separates users of aggregated anonymized data for accounts, processing, network analysis, and data management from those users who use the data to receive feedback on their personal contributions in the interactive environment or to improve their personal contributions in the interactive environment; and 4) places these activities within the organization's institutions, projects, teams, and other structures.

[0025] As indicated elsewhere in this disclosure, system 100 and method may include multiple different subsystems that interact with each other to provide the functionality provided by system 100 and method. A first subsystem, FFSS 302, may include a multi-platform user experience (UX) that interfaces with users through smartphones, tablets, laptops, wearables, and a wider range of environmental experiences via the Internet of Things (IoT), for example, by using various types of surveillance technologies. In some embodiments, FFSS 302User engagement can be prompted and / or triggered by, but not limited to, queries such as survey questions, or by offering opportunities for "likes," comments, ranking systems, or audio / video captures, or by providing rewards, such as, but not limited to, units of value in cryptocurrencies that may or may not be based on underlying blockchain technology (which may or may not be application-specific). In some embodiments, a user can indicate that all participants in an event are helpful and that their engagement is effective from the user's perspective through a single interaction (e.g., clicking a digital interface). In some embodiments, user responses can be given directly from another application, such as, but not limited to, calendar applications, text messages, emails, wearable technology notifications, or a combination thereof. As another example, a user may be attending a conference or other event and may be listening to a presentation by a subject matter expert. While the speaker is presenting and / or browsing the accompanying media, at any given moment or in many moments, the user can swipe up on the user interface of their device (e.g., via a touchscreen) if the material is useful, and swipe down if the material is unclear or irrelevant. As another example, if the speaker is engaging, the user can swipe right, and if the presentation can be improved, the user can swipe left. In some embodiments, system 100 and the method may also provide opportunities for users to provide detailed comments that will improve the interaction. In some embodiments, system 100 may track who is speaking, expectations regarding the individual's role in the meeting or event, and the location of additional feedback during the presentation. The tracking information may then be transmitted to a second subsystem sDAASS 306 as feedback to the presenter and any other users who may be assigned responsibility for meetings, agenda items, presentations, reports, events, projects, or objectives associated with the event. The transmission of tracking information to sDAASS 306 may be carried out securely and anonymously, for example, but not limited to, by utilizing encryption at both ends. In some embodiments, information from A&PSS 310 may be integrated into sDAASS 306. In some embodiments, information from existing events may also be analyzed to provide users with pre-event briefings.

[0026] In some embodiments, to ensure confidentiality and prevent or deter hacking, all data related to interactions with any particular user and to other users in FFSS 306 can first be anonymously transmitted via a secure connection to a separate, secure MS 304, where each user identified in the data associated with interactions with other users is uniquely identified using a different avatar. This user identification to the avatar can be encoded using securely stored secure mapping keys and / or security tokens (e.g., by utilizing a blockchain or some other secure ledger). In some embodiments, the allocation key can be used to associate analytics and content associated with the avatar back to the real user. This can allow another third subsystem, CFSS, to be used.308 Accesses specific tutoring media and resources at a given point in time that are relevant to the needs and interests of a given user, and this can be done securely. In some embodiments, information from A&PSS 310 can be securely integrated into CFSS 308 to access specific tutoring media and resources at a given point in time that are relevant to the needs and interests of a given user. Specification 7 / 36 pages 12 CN 121479065 A

[0027] It is worth noting that sDAASS 306 can be used as the analysis and cognition core of system 100 and method. As a standalone system, sDAASS 306 is both secure and completely anonymous in some embodiments. In system 100 and method, all users can be securely represented as avatars. Avatars in sDAASS 306 can be associated with each other and with events, meetings, projects, multi-team systems, goals and organizations, which is equivalent to a dynamic virtual representation of the interactive world of all users of system 100 and method. Each avatar (and therefore, each real user via a secure index) can have a secure and unique window into the virtual social network world, as the interactive network influences the user. A time-series tensor variable called a conditional state can be assigned to each avatar, representing the avatar's world as experienced from the perspective of each unique avatar. Feedback from the user can be securely transmitted to the virtual world and aggregated within the avatar's context to ensure anonymity, and such data can be compiled and analyzed to provide specific and targeted feedback to each user through each user's avatar. For analytical purposes, conditional states can be projected onto a smaller space of conditional state types and / or categories. In some embodiments, feedback is developed for each conditional state type, and each avatar assigned a specific conditional state type receives similar feedback. In some embodiments, feedback can be sent to a CFSS 308 indexed by this conditional state type, which may, but does not necessarily, contain status or reputation ranking data regarding other people in the virtual network of the focused avatar. Thus, system 100 and the method allow each user secure access to secure virtual and additionally anonymous representations of their personal social, knowledge, and resource networks, as well as historical events and actions for the purpose of exploring and simulating scenarios. Independently, the conditional state type or category of a given avatar can be sent to CFSS 308 and then securely mapped to the user as a user's interest state and / or code. In some embodiments, information from A&PSS 310 can be securely integrated into CFSS 308 to access specific guidance media and resources at a given point in time that are relevant to the needs and interests of a given user, and this can be done securely. In some embodiments, personal or demographic identification information about the user is not included in sDAASS 306.

[0028] In some embodiments, the conditional state of the first avatar may, but is not necessarily, be calculated using data from self-assessment and self-development activities, organizational and environmental states, as well as survey responses and information collected through other avatars (reflecting other users) regarding the first avatar, considering both individual and overall scenarios with similar characteristics, to investigate questions about a specific event, event series, event type, item, or set of items, or the role played by the first avatar is any of the above. This conditional state may, but is not necessarily, be combined with other conditional states, and can then be mapped to a conditional state type by an algorithm that associates different conditional states with statistically or otherwise similar data characteristics to equivalent categories for the purpose of simplifying analysis. The foregoing results in assigning a conditional state type to the first avatar for each conditional state used in the calculation. In some embodiments, an avatar may have many conditional state types.

[0029] In some embodiments, the purpose of CFSS 308 may be to generate messages and resource feeds for users that are personalized to include multiple types of contextual background. For example, contextual background may include feedback from others regarding personal benefits during recent and historical events, enabling reflection and fostering self-awareness of one's personal situation and benefits, and establishing personal development goals when necessary. As another example, contextual background may include upcoming events previously identified to system 100 to prepare the user as effectively as possible by providing relevant information and context about the social interactions, relative impacts, and subject-specific expertise of various participants. As yet another example, contextual background may include progress toward the user's personalized long-term goals. In some embodiments, content available to the user may include: various types of articles and media; background and personal interaction history of individuals the user will interact with during the upcoming event; targeted training opportunities (e.g., tutorials); interactive instructor-led experiences; simulations involving virtual reality and / or augmented reality environments; gamified interactive tools; holograms; and one-on-one mentoring opportunities involving machine or human experts, or a combination of both. In some embodiments, a user may receive a report reflecting responses from other users. This report, as described on page 8 / 36 of CN 121479065 A, may include, but is not limited to, summary data, historical data, comparative data, statistical data, or data compiled from compiled text comments.

[0030] In some embodiments, the content available to the user may, but is not necessarily, be identified internally or externally (e.g., but not limited to, on the Internet) in the form of summaries, translations of technical or academic articles or publications, pre-published other references or links, training program materials, training course materials, training evaluation materials, open access, or other previously available information.Curation. In some embodiments, this material may be part of, but not limited to, a certification program, such as, but not limited to, a CFA (Certified Financial Analyst) certificate, an accredited degree program, such as, but not limited to, a Master of Business Administration (MBA) program, or a professional licensing program, such as, but not limited to, a licensed real estate agent, electrician, investment advisor, etc. In some embodiments, the content may be exclusive to one or more specific accounts and available only to users with appropriate permissions. Curation may involve, but is not limited to, perceptual analysis of free-form comments or other information collected from other users anonymized through artificial intelligence and machine learning algorithms. The curation may involve, but is not limited to, randomly selected or otherwise collected human experts, machine experts, algorithms, machine learning, artificial intelligence, voting systems, user likes, or ranking systems. In some embodiments, holograms or other representation techniques may be used to present the results.

[0031] In some embodiments, the contextual backgrounds that a first user may experience may be categorized into user interests, and each of these contextual backgrounds may be assigned a user interest code. For example, this may include, but is not limited to, motivation for self-improvement in a particular aspect of professional development identified in a self-assessment survey or from a user's professional development plan, or it may involve, but is not limited to, a user recognizing from feedback that the user needs to improve, for example, public speaking skills. In some embodiments, a professional development plan may include, but is not limited to, a combination of skills, behaviors, or abilities that an individual progressively develops, such as, but not limited to: those that may be represented as one or more categories of expert contributors, flexible contributors, organizational contributors, or genuine contributors, or combinations thereof; but is not limited to, one or more of autonomous contributors or collaborative contributors, or combinations thereof; and a single combination that may be referred to as, but is not limited to, transitional contributors. In some embodiments, user interest codes may be inferred by System 100, experts, through artificial intelligence or through machine learning algorithms, and assigned to a first user for identifying guidance or media content or translations of academic or practical research or materials, which are then pushed to the user by the system. In some embodiments, the pushed content may include comparisons with, but is not limited to, benchmarks, other team scores, other individual scores, and, but is not necessarily, rewards, accommodations, points, or other rewards (whether monetary or otherwise). In some embodiments, these may be determined for the first user in a secure manner by mapping the conditional state type of the user's associated avatar to the user interest code and assigning it to the first user. In some embodiments, augmented reality or holographic technology can be used to bring experts to individuals for virtual guided lessons. In some user embodiments, users receiving feedback can interact with the system to thank those who anonymously or personally provided feedback to individuals or all participants, or not necessarily as feedback comments.

[0032] In some embodiments, content pushed to users via CFSS 308 can be selected based on encoded messages.The encoded message describes the user's timestamped conditional state, which, in the case of CFSS 308, can be referred to as the user's "state of interest at time t". Once content is accessed and pushed to the user, the value of the user's state of interest at time t can be encrypted and stored in CFSS 308 along with the content access history, which is only available to the user if the user chooses to access it. [Note: In some embodiments, all conditional state information can only be retained anonymously in sDAASS 306 as part of the virtual history of the user's securely and uniquely assigned avatar. For example, this can be used to notify future analytics and conditional state assignments.] To ensure confidentiality and prevent hacking, the conditional state in sDAASS 306 for a specific avatar can be anonymously transmitted via a secure connection from sDAASS 306 to a separate secure MS 304, where the user associated with the avatar can be identified and assigned a state of interest at time t (i.e., the conditional state of their avatar at time t). The user's state of interest at time t can then be appended to a user identifier and securely sent to CFSS 308. This key can be sent to access guidance media and resources related to the user's interest state at time t. Specification 9 / 36 pages 14 CN 121479065 A

[0033] In some embodiments, content or media already pushed to the user based on the user's interest code can be pushed to the user in the context of augmented reality (AR) or virtual reality (VR) technology or holographic technology, perhaps but not necessarily as: tactile signals, such as but not limited to vibrations; audio signals, such as but not limited to pitch, pitch series, or combinations of pitches; olfactory signals, such as but not limited to tastes or odors; or as visual signals, such as colors or images, color or image series, or combinations of colors and images, including but not limited to computer-generated images, such as but not limited to finite vector graphics rendered images commonly found in online games; or any combination of these, communicated by but not limited to wearable technologies, such that it can be delivered in training exercises, simulated exercises, or real-world situations or events. This may occur, but is not limited to, real-world situations or events being calculated as conditions corresponding to the type of conditional state that causes the system to recognize the user avatar of the first user's interest code. This can be provided by the system as an alert, trigger, or warning signal regarding the occurrence of a situation or the execution of recommended activities or behaviors, to prevent the recurrence of undesirable conditional state types or to promote the occurrence of ideal conditional state types. In some embodiments, the system may receive direct or aggregated feedback from individuals to identify operational problems or opportunities, such as, but not limited to, delays in project deliverables or unresolved conflicts within a team that may or may not need to be resolved by an individual, a subset of individuals, a team, or an organization. In some embodiments, feedback from A&PSS...Information from 310 can be securely integrated into CFSS 308 to access specific guidance media and resources that are relevant to a given user’s needs and interests at a given point in time.

[0034] As shown in Figure 1, a system 100 is disclosed for providing credible performance feedback for technical support. System 100 may be configured to support, but is not limited to, project collaboration services, event scheduling services, project or event staffing services, role assignment services, role or office election, deliverable distribution services, team and multi-team system organization services, interaction services, project optimization services, feedback services, self-assessment services, professional or other self-development services, content delivery services, monitoring and surveillance services, cloud computing services, satellite services, telephone services, Voice over Internet Protocol (VoIP) services, Software as a Service (SaaS) applications, Platform as a Service (PaaS) applications, gaming applications and services, social media applications and services, operations management applications and services, productivity applications and services, mobile applications and services, and any other computing applications and services. It is worth noting that system 100 may include a first user 101 who may utilize a first user device 102 to access data, content, and services, or perform various other tasks and functions. For example, the first user 101 may utilize the first user device 102 to transmit signals to access various online services and content, such as online services and content available on the Internet, other devices, and / or various computing systems. In some embodiments, the first user 101 may be an individual who can interact with other people (e.g., a second user 110) in an event or activity, such as, but not limited to, social gatherings, work meetings, political campaigns or experiences, team or multi-team system projects, performance activities (e.g., sports, performances, exercises, and / or any type of activity), social network gatherings, any type of social interaction activity, or any combination thereof. In some embodiments, the first user 101 may be a robot, computer, program, process, robotic simulator, animal, any type of user, or any combination thereof. The first user device 102 may include a memory 103 and a processor 104, the memory containing instructions, the processor executing the instructions from the memory 103 to perform various operations performed by the first user device 102. In some embodiments, the processor 104 may be hardware, software, or a combination thereof. The first user device 102 may also include an interface 105 (e.g., a screen, monitor, graphical user interface, etc.) that enables the first user 101 to interact with various applications running on the first user device 102 and with the system 100. In some embodiments, the first user device 102 may be and / or may include a computer, any type of sensor, a laptop computer, a set-top box, a tablet device, a tablet phone, etc.Servers, mobile devices, smartphones, smartwatches, and / or any other type of computing device. Illustratively, the first user device 102 is shown as the smartphone device in FIG1. ​​

[0035] In addition to using the first user device 102, the first user 101 may also utilize and / or access additional user devices. Specification 10 / 36 pages 15 CN 121479065 A As with the first user device 102, the first user 101 may utilize additional user devices to transmit signals to access various online services and content. The additional user device may include memory and a processor, the memory containing instructions, the processor executing instructions from the memory to perform various operations performed by the additional user device. In some embodiments, the processor of the additional user device may be hardware, software, or a combination thereof. The additional user device may also include an interface that enables the first user 101 to interact with various applications running on the additional user device and with the system 100. In some embodiments, the additional user device may be and / or may include a computer, any type of sensor, a laptop computer, a set-top box, a tablet device, a tablet phone, a server, a mobile device, a smartphone, a smartwatch, and / or any other type of computing device (whether wearable, implantable, or otherwise) and / or any combination thereof.

[0036] The first user device 102 and / or the additional user device may belong to and / or form a communication network. In some embodiments, the communication network may be a local network, mesh network, or other network that implements and / or facilitates various aspects of the functionality of system 100. In some embodiments, the communication network may be formed between the first user device 102 and the additional user device using any type of wireless or other protocols and / or technologies. For example, user devices may communicate with each other in the communication network using Bluetooth Low Energy (BLE), traditional Bluetooth, Wi-Fi, cellular, NFC, Wi-Fi, Z-Wave, ANT+, IEEE 802.15.4, IEEE 802.22, infrared, RFID, wireless HD, wireless USB, any other protocols and / or wireless technologies, satellite, fiber optic, or any combination thereof. It is worth noting that the communication network can be configured to communicatively link and / or communicate with system 100 and / or any other network outside system 100.

[0037] In some embodiments, a first user device 102 and additional user devices belonging to the communication network can share and exchange data with each other through the communication network. For example, user devices can share information about various components of the user device, information identifying the location of the user device, information indicating the type of sensors contained in and / or on the user device, information indicating biometric information for identifying any user associated with user device 110, and information indicating the connection with the same user device.Information associated with any user's authentication information, information identifying the type of connection used by the user device, information identifying the application used on the user device, information identifying how the user uses the user device, information identifying whether the user device is on the move, information identifying the orientation of the user device, information identifying which user is logged in and / or using the user device, information identifying the user profile of the user used for the user device, information identifying the device profile of the user device, information identifying the number of devices in the communication network, information identifying devices added to or removed from the communication network, any other information, or any combination thereof.

[0038] Information obtained from the sensors of the user device may include, but is not limited to, biometric information from any biometric sensor (or other sensor) of the user device, heart rate information from the heart sensor of the user device, temperature readings from the temperature sensor of the user device, ambient light measurements from the light sensor of the user device, sound measurements from the sound sensor of the user device, global positioning information from the global positioning device of the user device, proximity information from the proximity sensor of the user device, motion information from the motion sensor of the user device, presence information from the presence sensor of the user device, orientation information from the gyroscope of the user device, orientation information from the orientation sensor of the user device, acceleration information from the accelerometer of the user device, information from any other sensor, or any combination thereof. In some embodiments, information from the sensors of the first user device 102, the additional user device, and / or the second user device 111 may be transmitted to each other and to the components of the system 100 via one or more signals.

[0039] In addition to the first user 101, the system 100 may also include a second user 110, which may utilize the second user device 111 to perform a variety of functions. For example, the second user device 111 may be used by the second user 110 to transmit signals to request various types of content, services, and data from content and service providers associated with the communication network 135 or any other network in the system 100. In some embodiments, the second user 110 may be an individual who may interact with other persons in an event (e.g., the first user 101), such as, but not limited to, social gatherings, work meetings, team projects, event performances, social network gatherings, any type of social interaction activity, or any combination thereof. In some embodiments, the second user 110 may be a manager, administrator, and / or other individual who can monitor and / or supervise the interactions made by the first user 101 during various events. In other embodiments, the second user 110 may be a robot, computer, program, process, or simulated machine.Humans, animals, any type of user, or any combination thereof. The second user device 111 may include a memory 112 and a processor 113, the memory containing instructions, the processor executing the instructions from the memory 112 to perform various operations performed by the second user device 111. In some embodiments, the processor 113 may be hardware, software, or a combination thereof. The second user device 111 may also include an interface 114 (e.g., a screen, monitor, graphical user interface, etc.) that enables the second user 110 to interact with various applications running on the second user device 111 and with the system 100. In some embodiments, the second user device 111 may be a computer, laptop computer, set-top box, tablet device, tablet phone, server, mobile device, smartphone, smartwatch, and / or any other type of computing device, whether wearable, implantable, or otherwise. Illustratively, the second user device 111 is shown as a smartphone device in FIG. 1.

[0040] The system 100 may also include a third user device 115, which may be utilized by a user of the system 100. The third user device 115 may include a memory and a processor, the memory containing instructions that the processor executes from the memory to perform various operations performed by the third user device 115. In some embodiments, the processor may be hardware, software, or a combination thereof. The third user device 115 may also include an interface (e.g., a screen, monitor, graphical user interface, etc.) that enables the third user device 115 to interact with various applications running on the third user device 115 and with the system 100. In some embodiments, the third user device 115 may be a computer, laptop computer, set-top box, tablet device, tablet phone, server, mobile device, smartphone, smartwatch, and / or any other type of computing device, whether wearable, implantable, or otherwise. Illustratively, the third user device 115 is shown as a wearable device in FIG. 2. The system 100 may also include a computing device 120, which may be used, for example, to monitor a user during an event. The computing device 120 may include a memory and a processor, the memory containing instructions that the processor executes from the memory to perform various operations performed by the computing device 120. In some embodiments, the processor may be hardware, software, or a combination thereof. The computing device 120 may also include an interface (e.g., a screen, monitor, graphical user interface, etc.) that enables the computing device 120 to interact with various applications running on the computing device 120 and with the system 100. In some embodiments, the computing device 120 may be a computer, a monitoring device, a camera, a motion detector, any type of sensor, a laptop computer, a set-top box, a tablet device, a tablet phone, a server, a mobile device, a smartphone, a smartwatch, and / or any other type of computing device, regardless of...Whether it is wearable, implantable, or otherwise. Illustratively, computing device 120 is shown as the monitoring device in Figure 2. It is worth noting that any of the user devices in system 100 may include an operating system, telecommunications capabilities (SMS, calling, etc.), security and encryption functionality for protecting data, email functionality, browser functionality, and / or any other functionality. System 100 may also include firewall 125, which may be designed to block unauthorized access to data of system 100, devices of system 100, programs of system 100, or any combination thereof. Firewall 125 may also allow devices and / or programs of system 100 to communicate securely with external network 165. In some embodiments, firewall 125 may be configured to provide security for data and programs performed by system 100 and / or to encrypt data and / or information traversing various components, devices, and / or programs of system 100.

[0041] In some embodiments, the first user device 102, the additional user device, and / or the second user device 111 (and / or the third user device 115 and / or the computing device 120) may have any number of software applications and / or application services stored thereon and / or accessible thereon. For example, the first user device 102, the additional user device, and / or the second user device 111 may include feedback applications, collaborative work applications, voting applications, interactive social media applications, biometric applications, cloud-based applications, VoIP applications, other types of mobile-based applications, product ordering applications, business applications, e-commerce applications, media streaming applications, content-based applications, media editing applications, database applications, game applications, internet-based applications, browser applications, mobile applications, service-based applications, productivity applications, video applications, music applications, social media applications, any other type of application, any type of application service, or combinations thereof. In some embodiments, the software applications may support the functionality provided by the system 100 and methods described in this disclosure. In some embodiments, the software application and service may include one or more graphical user interfaces to enable the first user 101 and the second user 110 to easily interact with the software application. The software application and service may also be used by the first user 101 and the second user 110 to interact with any device in system 100, any network in system 100, or any combination thereof. In some embodiments, the first user device 102, additional user devices, and / or the second user device 111 may include an associated telephone number, device identifier, or any other identifier to uniquely identify the first user device 102.Additional user devices and / or a second user device 111.

[0042] System 100 may also include a communication network 135. The communication network 135 may be under the control of a service provider, a first user 101, a second user 110, any other designated user, a computer, another network, or a combination thereof. The communication network 135 of system 100 may be configured to link each of the devices in system 100 to each other. For example, the communication network 135 may be used by the first user device 102 to connect to other devices within or outside the communication network 135. In addition, the communication network 135 may be configured to transmit, generate, and receive any information and data traversing system 100. In some embodiments, the communication network 135 may include any number of servers, databases, or other components. The communication network 135 may also include and be connected to a mesh network, local network, cloud computing network, IMS network, VoIP network, secure network, VoLTE network, wireless network, Ethernet network, satellite network, broadband network, cellular network, private network, cable network, Internet, Internet Protocol network, MPLS network, service distribution network, any network, or any combination thereof. Illustratively, servers 140, 145, and 150 are shown as being included within the communication network 135. In some embodiments, the communication network 135 may be part of a single autonomous system located in a specific geographic area, or part of multiple autonomous systems spanning several geographic areas.

[0043] It is noteworthy that the functionality of system 100 can be supported and performed by using any combination of servers 140, 145, 150, and 160. Servers 140, 145, and 150 may reside within the communication network 135; however, in some embodiments, servers 140, 145, and 150 may reside outside the communication network 135. Servers 140, 145, and 150 can provide and act as server services performing various operations and functions provided by system 100. In some embodiments, server 140 may include memory 141 and processor 142, the memory containing instructions, the processor executing instructions from memory 141 to perform various operations performed by server 140. Processor 142 may be hardware, software, or a combination thereof. Similarly, server 145 may include memory 146 and processor 147, the memory containing instructions, the processor executing instructions from memory 146 to perform various operations performed by server 145. Furthermore, server 150 may include memory 151 and processor 152, the memory containing instructions, the processor executing instructions from memory 151 to perform various operations performed by server 150. In some embodiments, servers 140, 145, 150, and 160 may be network servers, routers, gateways, switches, media distribution hubs, signaling points, service control points, service switching points, firewalls, routers, edge devices, etc.Devices, nodes, computers, mobile devices, or any other suitable computing devices or any combination thereof. In some embodiments, servers 140, 145, 150 may be communicatively linked to communication network 135, any network, any device in system 100, or any combination thereof.

[0044] Database 155 of system 100 may be used to store and relay information traversing system 100, cache content traversing system 100, store data about each of the devices in system 100, and perform any other typical functions of a database. In some embodiments, database 155 may be connected to or reside within communication network 135, any other network, or a combination thereof. In some embodiments, database 155 may act as a central repository for any information associated with any of the devices and information associated with system 100. Furthermore, database 155 may include or be connected to processor and memory to perform various operations associated with database 155. In some embodiments, database 155 may be connected to firewall 125, servers 140, 145, 150, 160, first user device 102, second user device 111, additional user device, third user device 115, computing device 120, any device in system 100, any process of system 100, any program of system 100, any other device, any network, or any combination thereof.

[0045] Database 155 may also store information and metadata obtained from system 100, metadata and other information associated with the first user 101 and the second user 110, user profiles associated with the first user 101 and the second user 110, device profiles associated with any device in system 100, communications traversing system 100, user preferences, information associated with any device or signal in system 100, information related to usage patterns of user devices 102, 111, 115 and / or computing device 120, any information obtained from any network in system 100, any biometric information obtained from any sensor in system 100, and biometric and / or other information. Or digital credentials, storing historical data associated with the first user 101 and the second user 110, storage device characteristics, storing information about any device associated with the first user 101 and the second user 110, storing any information associated with the computing device 120, storing authentication information, storing information associated with the communication network 135, storing any information generated and / or processed by the system 100, storing any publicly available information for operation and for the functions publicly available in the system 100.Any one of the following may be used to store any information traversing system 100, or any combination thereof. Furthermore, database 155 may be configured to process queries sent to it by any device in system 100.

[0046] System 100 may also include an external network 165. External network 165 may be under the control of a service provider, any designated user, a computer, another network, or a combination thereof, other than communication network 135. External network 165 of system 100 may be configured to communicate with communication network 135. For example, communication network 135 may be used to communicate with first user device 102 and connect to other devices within or outside external network 165. Additionally, external network 165 may be configured to transmit, generate, and receive any information and data traversing system 100. In some embodiments, external network 165 may include any number of servers, databases, or other components. External network 165 may also include and be connected to mesh networks, local networks, cloud computing networks, IMS networks, VoIP networks, secure networks, VoLTE networks, wireless networks, Ethernet networks, satellite networks, broadband networks, cellular networks, private networks, cable networks, the Internet, Internet Protocol networks, MPLS networks, service distribution networks, any network, or any combination thereof. In some embodiments, external network 165 may be part of a single autonomous system located in a specific geographic area, or part of multiple autonomous systems spanning several geographic areas.

[0047] Notably, in some embodiments and as shown in FIG3, system 100 may include FFSS 302. FFSS 302 may be a subsystem of system 100 for a technology-enabled user experience and interaction platform, which enables users to provide and receive feedback on perceived capabilities, benefits, and / or performance of others with whom they interact, for example, during events. In some embodiments, FFSS 302 may include software, hardware, or a combination of software and hardware. In some embodiments, FFSS 302 may reside on a first user device 102 and / or a second user device 111, a third user device 115, servers 140, 150, 160, a communication network 135, a computing device 120, an external network 165, any other device, system, and / or location, or a combination thereof. In some embodiments, FFSS 302 may include any number of servers, interfaces, sensors, devices, programs, modules, or combinations thereof to enhance the performance and functionality of FFSS 302. In some embodiments, FFSS 302 may be configured to schedule events and meetings for any number of users. Social interactions and emotional responses occurring within each event may form the basis for responses to system queries. In some embodiments, FFSS 302 may collect information about the status of an institution and / or organization (e.g., users' information about their work).The data collected includes information about the state of the environment (e.g., the state of the location where the event is taking place). In some embodiments, this data may be obtained through interfaces with other entities, including but not limited to application programming interfaces (APIs), messages, notifications, signals, calendar entries, emails, tokens, or any combination thereof, such as, but not limited to, systems, applications, or Software as a Service (SaaS) or other platforms. Such interfacing entities may include, but are not limited to, Microsoft Teams, SharePoint, MS Project, Google Docs, Google Calendar, Twilio, Zoom, Webex, Slack, Trello, LiquidPlanner, Asana, Adobe, IBM, WorkDay, or Zulip. In some embodiments, FFSS 302 may process all or some user data, all or some user input, or all or some of the displayed, processed, or reviewed information in a Trusted Execution Environment (TEE), regardless of whether the confidential computing technology used is software- or hardware-enabled. The collected data may be securely passed to MS 304 for anonymous forwarding to sDAASS 306.

[0048] In some embodiments, FFSS 302 may be configured to provide a self-assessment service to the user, which queries the user for information about, but not limited to, the following: self-perception, self-performance reflection, preferences, personality traits, learning patterns, knowledge level in various content areas, prior education and training, cognitive abilities, social and emotional skills, knowledge about organizations, departmental projects, events (including but not limited to goals, tasks, deliverables, contingencies, schedules, leadership, management, other team members, deliverables of other teams and their members, handover and objectives), whether in multi-team systems or otherwise, or in terms of individuals, teams, multi-team systems or organizations, or careers, goals or aspirations.

[0049] In some embodiments, FFSS 302 may configure professional or other self-development planning services for the user, which queries the user for information about, but not limited to, the following: the user's learning purpose, goals, expectations and preferences, learning patterns, knowledge level in various content areas, prior and expected education and training, cognitive abilities, course preferences, knowledge level, social and emotional skills, and knowledge about organizations, departmental projects, and events (including but not limited to goals, tasks, deliverables, contingencies, schedules, leadership, management, other team members, deliverables of other teams and their members, handover, and goals), whether in a multi-team system or otherwise.

[0050] As indicated above, system 100 may also include another subsystem, sDAASS 306. sDAASS 306 may be composed of...A data storage and analysis platform supported by machine learning, artificial intelligence, expert systems, human expert panels, or a combination thereof. In some embodiments, sDAASS 306 may comprise software, hardware, or a combination of software and hardware. In some embodiments, sDAASS 306 may reside on a first user device 102 and / or a second user device 111, a third user device 115, servers 140, 150, 160, a communication network 135, a computing device 120, an external network 165, any other device, system, and / or location, or a combination thereof. In some embodiments, sDAASS 306 may comprise any number of servers, interfaces, sensors, devices, programs, modules, or combinations thereof to enhance the performance and functionality of sDAASS 306. The processing performed by sDAASS 306 includes, but is not limited to, data mining, project or vote counting, individual or decision ranking, dynamic system processing, statistical analysis, and scientific research, such as, but not limited to, theory-based hypothesis testing, which can be used to analyze user and system data related to, but not limited to, user interactions, organizational status information, or environmental data. The processing performed by sDAASS 306 may also include, but is not limited to, performing and executing various scenarios and simulations. These analyses may together serve as input to user reports, feedback, and recommendations generated by system 100. Data generated and / or analyzed by sDAASS 306 may be securely transmitted to MS 304 for forwarding to CFSS 308. In some embodiments, CFSS 308, further described below, may process all or some system-generated or user data, all or some user input, or all or some displayed, processed, or reviewed information in a Trusted Execution Environment (TEE), regardless of whether the confidential computing technology used is software and / or hardware enabled.

[0051] In addition to CFSS 302 and sDAASS 306, system 100 may also include MS 304, which may be a secure firewall-protected processing platform that encrypts and stores a two-way mapping between the real user identity and the avatar identity. The former allows users to provide and access data about other people in a secure and anonymous technical setting. The latter allows users to receive security feedback privately and anonymously, without the need for other humans to access it without user permissions (as determined by selections in the user's profile). In some embodiments, MS 304 may comprise software, hardware, or a combination of software and hardware. In some embodiments, MS 304 may reside on a first user device 102 and / or a second user device 111, a third user device 115, servers 140, 150, 160, a communication network 135, a computing device 120, an external network 165, any other device, system, and / or location, or a combination thereof. In some embodiments, MS304 may include any number of servers, interfaces, sensors, devices, programs, modules, or combinations thereof to enhance the performance and functionality of MS 304. In some embodiments, firewall 125 may be integrated into and / or communicatively linked to MS 304.

[0052] As indicated above, data is securely transferred from sDAASS 306 to MS 304, which then forwards the protected data to CFSS 308, which may be another subsystem of system 100. In some embodiments, CFSS 308 may be a technology-enabled user experience and interaction platform that enables users to receive feedback on their perceived ability, relative level, contribution, participation, or performance during events and interactions anonymously described by others with whom they interact. In some embodiments, CFSS 308 may generate output reports, analyses, and / or recommendations. CFSS 308 may transmit and / or additionally provide reports, analyses, guidance techniques, micro-lessons on various topics, behavioral signals or triggers, encoded haptic, electromagnetic or acoustic, or olfactory sensing patterns that may or may not promote learned cognitive activity to a user, for example, by transmitting reports, analyses, and / or recommendations to a first user device 102 and / or a second user device 111. CFSS 308 may provide access to a customized interest-indexed streaming content database (e.g., database 155), which can be used to enhance analysis and support tutoring or guidance recommendations aimed at improving the user's future performance. In some embodiments, CFSS 308 may reside on a first user device 102 and / or a second user device 111, a third user device 115, servers 140, 150, 160, a communication network 135, a computing device 120, an external network 165, any other device, system, and / or location, or a combination thereof. In some embodiments, CFSS 308 may include any number of servers, interfaces, sensors, devices, programs, modules, or combinations thereof to enhance the performance and functionality of CFSS 308. In some embodiments, CFSS 308 may process all or some system-generated or user data, all or some user input, or all or some displayed, processed, or reviewed information in a Trusted Execution Environment (TEE), regardless of whether the confidential computing technology used is software- or hardware-enabled.

[0053] Various subsystems may interact with and be related to each other. For example, FFSS 302 and MS 304 may communicate and interact with each other regularly in a secure and dynamic manner to ensure that the data acquisition process (obtaining feedback and / or other relevant data) is secure and provides complete anonymity to all users. Once user-inputted data is successfully transferred from FFSS 302 to MS 304, the source data on FFSS 302 may be erased from FFSS 302. Once MSThe user data received on MS 304 (i.e., received from FFSS 302) has been encoded and assigned to a corresponding avatar identifier and possibly, but not limited to, organizational and environmental codes (numerical or other types of codes) to become anonymized data, which can be erased from MS 304. In some embodiments, this erasure may be necessary, but not required, before anonymized data regarding any individual user's input, evaluation, and interactions with FFSS 302 is securely transmitted to sDAASS 306. In some embodiments, information from A&PSS 310 may be integrated into information from FFSS 302 before being securely transmitted to sDAASS 306. Upon first use, MS 304 can create a unique avatar for a given user. This avatar can be anonymously embedded in virtual organizations and virtual social networks comprised of all other users of System 100.

[0054] MS 304 can then transfer all data that has been securely and anonymously assigned by MS 304 to the corresponding uniquely defined avatar to sDAASS 306 for further processing. sDAASS 306 can transfer conditional state data for all avatars, securely assigned to each real user, to MS 304 for processing. Additionally, MS 304 can continuously and dynamically and securely interact with CFSS 308 to ensure that the reporting, guidance, and recommendation processes are secure and remain anonymous to all users. Once MS 304 securely receives the conditional state report and recommendation package for a given avatar from sDAASS 306, MS 304 (page 16 / 36 of specification, 21 CN 121479065 A) can access its protected firewall (possibly protected by blockchain and / or distributed ledger technology), user-to-avatar mapping index file, and assign the avatar's conditional state report to its user and the user's state of interest at time t. Once this assignment is verified, the avatar conditional state record can be erased from MS 304. In some embodiments, erasure can be performed before MS 304 securely transmits the user's "interest state at time t" to CFSS 308. In some embodiments, information from A&PSS 310 can be securely integrated into CFSS 308 to access specific guidance media and resources relevant to the needs and interests of a given user at a given point in time.

[0055] Operationally, system 100 is operable and / or performs the functionality described in the methods of this disclosure and the following use case scenarios. In a first use case scenario, a user can interact with their smartphone and other technologies to enhance their social interaction in events such as meetings and presentations. This can occur in two situations. First, during and after meetings and events, the application queries the user about their situation in the event itself relative to each other participant and with the group itself.The experience. Secondly, each user receives targeted tutoring and feedback tailored to the user based on specific feedback and near real-time data analysis, based on the historical experiences of all other system 100 users and the latest research findings in social sciences. To support these uses, system 100 utilizes big data technology, artificial intelligence, expert systems and computational modeling simulations, as well as human experts.

[0056] In some embodiments, use cases may include the use of software applications for, but not limited to, smartphones (e.g., the first user device 102). The software application may have any of the functionalities and features described for the system 100 and / or methods described in this disclosure. The application enables the user to give or query the user to provide feedback on other people for the benefit of the other person’s personal development and self-awareness. This input of feedback may be asked of each user before, during or after an event of at least one other person (who is also a user) (e.g., through an application executed on each user’s device), and the focus user interacts with the at least one other person (even if not only by listening) for a period of time during the event, meeting, experience or activity. Data analytics techniques, as well as machine and human intelligence and expertise, can then be used to compile and process this data. Feedback can be provided privately and anonymously to individual users through personal interactions with coaches, mentors, and / or supervisors via their smartphones or in person to help users improve their management, interaction, presentation, or self-monitoring skills, thereby enhancing future performance. This data can be anonymously aggregated for use by larger organizations.

[0057] In some embodiments, self-assessment can be performed by constructing survey tools or other queries that may or may not use data, surveys, or other queries that are, but are not necessarily, about the context, learning, or expected situation of a first or second user, or a combination thereof, and may but not necessarily request a response. The information used by system 100 to construct this tool may but not necessarily be associated with a conceptual model that considers one or more attributes, behaviors, or other observable measures, first-, second-, third-, or other levels of latent variables or factors in the case of their assumed statistical relationships, some or all of which may or may not be empirically verifiable. In some embodiments, the observed attributes, behaviors, other observable metrics, or latent variables used for, but not limited to, building tools, reporting, or identifying user interest codes can be one or a combination of the following: accountability, proactive listening, management activities, adaptability, flexibility, accessibility, authenticity, empowerment, autonomy, autonomous contribution, consistency, contribution, balanced decision-making, balanced processing, collaborative contribution, community building, and capabilities in areas such as, but not limited to, industry, technology, functionality, culture, information and communication technologies, and information presentation.Innovative, creative, or physical fitness metrics; civic behavior; commitment; confidence; clarity (clear communication); clear thinking; camaraderie; consideration; convergence; curiosity; divergence; followers; emotional intelligence; empathy; empowerment; participation; evidence; generative activities; humor; initiative; innovation; intellectual stimulation; leadership; mental resilience; clear values ​​or moral compass; atmosphere; open-mindedness; organization; performance metrics; predictability; readiness; proactivity; psychological safety; self-awareness; relationship transparency; relevance; respect; self-awareness; self-regulation; support; team norm strength; transparency of transformational contributions; trust; universality; trust; personalized trust; or workplace atmosphere.

[0058] As indicated above, the functionality provided by system 100 can be incorporated into a software application. The application can interact with the controller software and database 155 of system 100 via a telecommunications network. In use cases, the application may optionally notify the user that it is time for the user to give feedback and / or, but not necessarily, time for the user to receive feedback. If it is time to provide feedback, the user can be queried through a subsystem of the application to provide specific feedback on their impressions of another person with whom they had a meaningful interaction during the event or meeting. This can happen when the user interacts with the application locally, for example on a first user device 102 of the first user 101. When the user clicks “Submit,” this data can be transmitted from the first user device 102 to a server on the network (e.g., server 140), which contains controller software for storing these databases 155. In some embodiments, optional notification features may also be utilized, wherein system 100 sends a notification to the user to provide feedback when the device calendar application indicates that a scheduled event has started or is about to end.

[0059] In some embodiments, survey tools or other queries for obtaining feedback from a second user about a user and for a user may, but are not necessarily, constructed or assembled using data, surveys, or other queries about the context, learning or expected situation, or a combination thereof, of the first or second user, and may, but are not necessarily, request a response. The information used by System 100 to construct this tool may, but is not necessarily, associated with a conceptual model that considers one or more attributes, behaviors, or other observable measures, or first-, second-, third-, or other latent variables or factors in the context of their assumed statistical relationships, some or all of which may, but are not necessarily, empirically verifiable. In one embodiment, the observed attributes, behaviors, other observable measures, or latent variables used for, but not limited to, constructing tools, reporting, or identifying user interest codes may be one or a combination of: accountability, proactive listening, management activities, adaptability, and flexibility.Sexuality, alignment, accessibility, authenticity, empowerment, autonomy, autonomous contribution, empowerment, consistency, contribution, balanced decision-making, balanced handling, collaborative contribution, connection, community building, such as but not limited to industry, technology, function, culture, information and communication technology, ability, information presentation, innovation, or physical, civic behavior, commitment, confidence, clarity (clear communication), clear thinking, camaraderie, consideration, contribution, convergence, innovation, curiosity, divergence, followers, emotional intelligence, empathy, empowerment, participation, evidence, generative activities, humor, initiative, innovation, intellectual stimulation, leadership, mental resilience, clear values ​​or moral guidelines, atmosphere, open-mindedness, organization, performance, predictability, preparedness, proactivity, psychological safety, relational social sensitivity, transparency, relevance, reinforcement learning, respect, self-awareness, self-regulation, support, team norm strength, transformational contribution transparency, trust, universality, trust, personalized trust, valence, generality, valence, or workplace atmosphere.

[0060] In some embodiments, when it is time for the user to receive feedback, the software on the user device presents the feedback to the user in the form of raw data summarizing the user's performance in recent events. The user can then use this information to change their behavior in future events. In an optional notification scenario, when the user device software receives a message from the controller software, the software on the user device can send a notification to its user to receive feedback, the message containing the recommendation package. It is this recommendation package that can be presented to the user by the software on the user's personal device. The controller software can receive and store data from the user (functionality may be provided by the subsystem). The controller software can also run a program for each completed event by aggregating data among its users to analyze the results and prepare a recommendation package for the user. When the recommendation package is ready for the user, it can be sent to the user's smartphone or other device. In some embodiments, the software on the user's device then sends a notification to the user to receive feedback.

[0061] In another embodiment, system 100 also intends and has other more complex features, functions, and attributes. In this more complex embodiment, an application on a smartphone (or other suitable device) informs the user that it is now time for them to provide feedback on a recent event (page 18 / 36, 23 CN 121479065 A) or to obtain feedback on a recent event related to at least one future event. If it is time to provide feedback, the application identifies this situation from its database 155 or its interactions with other applications of system 100. This is achieved by the smartphone application requesting the user to provide specific impressions of each other individual with whom they had meaningful interactions during the identified event or meeting.Feedback triggers a query from the user. The application also accesses specific information about the event to determine the questions contained in the user's query and when to compile reports and recommendations. If the notification signals to the user that it is time to receive feedback, then options may be presented to the user, including the event for which feedback is available and the type of individual feedback they can view, including but not limited to anonymous raw data, aggregated data compared to other data, data presented in historical context, analysis of this data, automated guidance based on this data, human expert advice based on this data, streaming content that the system identifies as needed, or real interaction with a human tutor or expert.

[0062] In another embodiment, the controller software may combine the application and database 155 to manage encryption / decryption and network security processes to ensure the anonymity and security of each user. The processor of system 100 is capable of performing operations and executing instructions to implement this embodiment of system 100. In another embodiment, the secure database 155 contains secure and anonymous copies of all data collected through the application, as well as organizational and contextual data collected from other sources, and maintains a complete history of all data and all recommendations for future analysis. In another embodiment, this data will be compiled and processed using proprietary data analytics techniques, and copyrighted feedback will be provided to each individual user to help them improve their performance, for example, during future events, projects, and / or meetings. Data about other individuals is collected at the individual level via, for example but not limited to, smartphones; all data about an individual's performance or interactions, or the performance of a team or multiple teams, is aggregated and analyzed using a computer processor, and transmitted back to the user as aggregated feedback about how others perceive the user during the event. In another embodiment, the collected data may be aggregated using wearable technology (e.g., device 115) or from surveillance (e.g., device 120) or other devices (e.g., associated with the Internet of Things or personal assistant devices (e.g., Amazon Alexa, etc.)), and similarly, recommendations may be delivered in real time via wearable devices, personal assistants (e.g., Amazon Alexa), and / or other technologies and / or even via third parties.

[0063] In use case scenarios, system 100 may be used to create and / or support a virtual, enhanced social network for the user. Initially, for example, a first user 101 may download an application providing the functionality of system 100 and methods to a first user device 102. The application may be downloaded, for example, from one or more components of system 100. If the first user 101 is not yet a registered user of system 100, then the first user 101 may be prompted to register with the application, for example, through the application itself. During the registration process, system 100 communicates with a secure MS 304 via a secure, encrypted network.On 304, a user identifier (User_ID) is assigned and mapped to a unique, newly created virtual identifier (Virtual_ID), referred to as Avatar_Node_ID. Avatar_Node_ID is a node in one or more virtual social networks used to enhance the real-world human social network of System 100 users. This mapping may, but does not necessarily, use blockchain and / or distributed ledger technology and / or similar coding, algorithms, or processing. The mapping from User_ID to Avatar_Node_ID is a secure and anonymous way for a user to interact with other System 100 users (e.g., second user 110) through their secure Avatar_Node_ID using their unique User_ID.

[0064] In this use case scenario, first user 101 may be allowed to join networks, projects, or organizations of other users, such as second user 110. Once registered as a user in the system and in the application, first user 101 may have been, or may be, requested by other users (e.g., second user 110) to participate in those other users' trusted networks. In some embodiments, this can occur when the first user 101 is included in an event of another user (e.g., the second user 110). From the perspective of system 100, the assignment of participants to an event can be anonymous. This assignment can occur on the MS 304 security specification page 19 / 36, 24 CN 121479065 A, behind firewall 125 on the main virtual network system processing server. On the main system server (e.g., server 140, server 150, and / or server 160), the Avatar_Node_ID of the actual focus user (e.g., the first user 101 in this case) is added to the virtual event by the Avatar_Node_ID of another user. This virtual event also contains the Avatar_Node_IDs of other participants in the event. Once the event is established behind firewall 125 in the main system 100, the event can be relayed back via MS 304, where the Virtual_Event is used to create a Real_Event with real users for data collection. This Real_Event record includes, but is not limited to, its event identifier (Event_ID), event type (Event_Type), start date (Start_Date), project (Project_Type), project type (Project_Type), institution (Institution), institution type (Institution_Type), start time (Start_Time), end date (End_Date), end time (End_Time), event location, and usage.The Real_Event is created by mapping each Avatar_Node_ID to its User_ID (as identified in a secure mapping with Avatar_Node_ID), the actual User_ID of the user to whom the data applies (as identified in a secure mapping with Avatar_Node_ID), each person's role or engagement type, each user's research request (Study_ID), the query or survey to be sent to each user (Survey_ID), and the response given by each user (By_User_Response). This Real_Event is created by mapping each Avatar_Node_ID to its User_ID (including the User_ID of the user in focus). This mapping may, but does not necessarily, use blockchain or similar encoding, algorithm, or processing to secure the mapping. In some embodiments, users may accept or reject the event based on their preferences. In some embodiments, under commercial licensing, they may be expected to accept invitations from their work teams, at least through regulatory pressure.

[0065] Feedback can be provided during real-world events via various technologies, including but not limited to surveys, queries, screen swipes, audio, video, writing or other media, surveillance technologies, wearable technologies, biometrics, thermal tracking, or geolocation technologies, through system 100. In a preferred embodiment, a survey can be presented to a first user 101 on a first user device 102, such as a smartphone, tablet, or other computer interface. For example, when the first user 101 is asked to provide feedback to another user (e.g., a second user 110) in response to a query, such as a survey about their contribution and participation in a recent event, this request will proceed through the following steps: (1) In a virtual social network comprised of Avatar_Node_IDs, the event is identified as scheduled. This may or may not occur because real-world users establish real-world events. As described herein, this can be securely implemented via the user_ID of the user mapped to the Avatar_Node_ID in the virtual social network for implementation in system 100 as described herein. (2) The Avatar_Node_ID arranged to participate in the event in its virtual social network, along with its different roles (which need to be determined which studies will be conducted), is the case where a specific Avatar_Node_ID participates in the virtual event as an avatar of the focus user (first user 101) participating in the real event. The virtual event effectively reflects the real event that occurs in the physical space in system 100. (3) For each of these virtual participants, MS 304 performs a reverse mapping to create an event for each user that includes the User_ID of those participants and their roles in the event. (4) System 100 then creates a unique event for each user.The event_protocol is implemented when a real-world user or calendar or algorithm-suggested feedback interval has begun. The reporting period for a given event remains open until the calendar indicates the end of the reporting interval. (5) For each user, the event_protocol includes: i) the User_ID to be queried; ii) the names of other participants (although their User_IDs will be queried for feedback); iii) the questions that the participants in this event will answer. (6) Once the reporting interval ends, the system 100 generates a series of reports available to each user. In some embodiments, these reports are generated only when there is sufficient data to remain anonymous or according to some other criterion. (7) Information from these reports is processed, and an anonymous summary event_report is temporarily associated with the User_ID and transmitted to the mapping server along with the User_ID. (i) The event_report contains event data, feedback received from each study, and a vector of directed weights describing the user_ID with whom the focus user_ID interacted during the event. (8) On MS 304, the event_report is securely transferred from the local User_ID to the Avatar_ID on the virtual social network. For security reasons, the event_report on system 100 can then be deleted from system 100, so that only the focus user can securely access the report through the secure MS 304 mapping.

[0066] User Experience (UX) Perspective: Based on this processing, an isolated real-world event is presented to the focus user (i.e., the first user 101), and the focus user is asked to join the event and provide anonymous feedback to other participants. From the user's perspective, interaction with the event is transactional, but it also occurs in the context of real-world relationships with other real-world participants. Enhanced Social Network Perspective: Each Virtual_Event is stored together with secure and anonymous data captured in the event in the context of the virtual social network maintained in system 100. It is associated with the relevant virtual entities and activities, including but not limited to: 1. the various Avatar_Node_IDs involved. 2. the research to which the data is applicable and its research parameters, including but not limited to the personality traits or other attributes of the individual users associated with the Avatar_Node_ID. 3. Any relevant formal or informal teams, multi-team systems, relationships, affiliations, identity groups, or special interest groups, or other social structures that users, other users, or systems can identify through machine learning, artificial intelligence, or interfacing with human experts or researchers. 4. Organizational state variables, such as, but not limited to: internal projects, multi-team systems, initiatives, departments, budget items.(5) Items, activity types, location within the organizational structure, subject areas, functions, event categories, or other items that may be associated with the event, (a) Examples of these may be, but are not limited to, the level of employee engagement factors in an organization, location, department, or work group, which may be calculated by the administrator based on offline HR research input or by the system based on existing research conducted by System 100. (b) Another example may be the financial level or other performance metrics of an organization, location, department, or work group, which may be calculated by the administrator based on offline HR research or by the system based on existing research conducted by System 100. (5) Environmental state variables, such as, but not limited to: market segmentation, location, technology, economic situation, political situation, government project supplier contracts, customer contracts, sales activities or contracts, logistics or distribution activities or contracts, external projects, initiatives, departments, or other items that may be associated with the event, (a) Examples of these may be, but are not limited to, the level of customer satisfaction factors of the customers, partners, or suppliers involved, and the organization, location, department, or work group, which may be collected or calculated by the administrator based on offline marketing research input or by the system based on existing research conducted by System 100. (b) Another instance may be the size of a client or other contract, or the type of a particular government agency or involved agency, which is identified and entered by the administrator, or collected or calculated by the system based on existing research conducted by the system. (6) Leadership activity variables, such as, but not limited to: town hall meetings, status meetings, project meetings, strategic discussions or initiatives, consulting contracts or other projects that may be associated with the event, (a) instances of these may be, but not limited to, the level of collective, shared, hierarchical, urgent, generative, administrative or community-building leadership activities observed over time in an organization, location, department or work group, and the assignment of roles to individuals, which may be entered by the administrator based on offline leadership research or calculated by the system based on existing research conducted by the system, (b) another instance may be the level of various factors associated with transformational, transactional, charismatic, authentic or other leadership styles in an organization, location, department or work group, which may be entered by the administrator based on offline human resources leadership research or calculated by the system based on existing research conducted by the system.

[0067] Users can create virtual events in a virtual network: In the application, users can decide to create virtual events in conjunction with real-life events. In addition to providing and receiving professional feedback for improvement through the application, establishing virtual events helps the system virtually enhance interactions within the user's real-life social networks in future interactions. For example, before a meeting, users can be reminded of social interaction dynamics that occurred during previous meetings of this type with some or all of the same participants, and these users can provide guidance to achieve greater benefits. Users can, however...To add a virtual event (related to a real-life event), you can perform the following actions on the application's user interface: 1. Select the "Create Event" function; 2. Select the event type; 3. Enter one of the following: date, start time, end time, or other data (see page 21 / 36 of the manual, 26 CN 121479065 A); 4. Specify one or more studies to be conducted before, during, or after the event; otherwise, the system may, but not necessarily, assign a default study; 5. Select a team or otherwise identify participants; 6. Optionally, select the project to which the event belongs; 7. Optionally, the user can assign roles to individual participants. Once the event is created on the user interface side of the Security Mapping Service (MS 304) and Firewall 125, the user's event_record is securely passed to MS 304. On MS 304, the user ID is mapped and replaced with its corresponding Avatar_Node_ID. Similarly, all event data is passed through MS 304 to create Virtual_Events that correspond to but are not directly linked to real-life events. It is initiated solely by its User_ID link via a reverse link from the user's Avatar_Node_ID.

[0068] User's Virtual Augmented Social Network (V-ASN): By regularly using this system 100, users interacting with their real-world social networks have the opportunity to receive and receive feedback, understand frank reactions, and gain emotional support through the system on a future-oriented basis, with security and confidentiality support for their own dynamic personal augmented reality network version. The system 100 may feature individual users creating and maintaining their own personal virtual networks by initiating projects or activities that connect to other people participating in events, presentations, etc., providing feedback back and forth, and evaluating the performance of others for maintenance and storage of the information for future use. However, the system 100 may store this network information in a completely anonymous, large-scale virtual network that may eventually contain millions of users. It is noteworthy that an administrator with access to part or even the entire virtual social network may not know which Avatar_Node_ID in the network is associated with any given user. Furthermore, they cannot alter or interfere with the virtual network in any way. However, it can be replicated and modified for simulation, research, and training purposes.

[0069] In some embodiments, Condition_State is an attribute of each Avatar_Node_ID: each Avatar_Node_ID in the virtual network can have a condition_state. The condition_state is a tensor matrix that is a time-series snapshot of how the relationship between the avatar node and each person in its network changes over time. In some embodimentsIn this context, through secure mapping, this state is a view of the individual user states for each of the 100 system pairs, but the identity of the user is unknown to the administrator. The view from Avatar_Node_ID to the virtual network will only be visible to the specific user securely mapped to the Avatar_ID. Therefore, from a given user's subjective perspective, "I can trust" "my network" is visible to "me" as the user, but only to myself. This personalized view will contain information about others in my social network, my evaluation of others, and anonymized feedback from other member users regarding past interactions in various events. When accessed by a user, this view is constructed in real time by securely mapping from the Avatar_Node_ID to the virtual network and back to the user. This data related to other real-life users is erased from the user's device immediately after the user accesses it. It can be reconstructed if needed again. In some embodiments, Condition_State may contain a complete history of all events and a representation of all network connections between each focused Avatar_Node_ID and other Avatar_Node_IDs. Condition_State can include the following: (1) Avatar_Node_ID; (2) a table linking Avatar_Node_ID and interaction events; (3) a table of events and Event_Reports.

[0070] In some embodiments, Condition_State_Type is a type of Condition_State: during batch processing, on a virtual network server (which may be implemented on any of servers 140, 150, 160), for each Avatar_Node_ID, a Condition_State containing a complete history of all interactions with other Avatar_Node_IDs, Event_Reports, and potential situational data (e.g., Environmental_State_Variable, Organizational_State_Variable, or Leadership_Activity) can be processed and projected onto a limited number of Condition_State_Types that may be limited by the administrator for the purpose of classifying user needs and interests and for identifying media to be presented to the user associated with the Avatar_Node_ID. Each user may have one or more Interest_States: Each Condition_State_Type for Avatar_Node_ID can be mapped to its corresponding specification page 22 / 36 27 CN 121479065 AUser_ID, as the Interest_State assigned to the real user. Interest_State may also contain data for the following specific situations: (1) Environmental_State_Variable may include, but is not limited to: government or regulatory issues; economic or political conditions; supplier and logistical considerations; customer or buyer needs; industry macro conditions and competition; threats of new entrants and threats of substitutes; etc. (2) Organizational_State_Variable may include, but is not limited to: formal organizational structure; workgroup, department or organizational goals; organizational policies, budgets, financial status; etc. (3) Leadership_Activity_Variable may include, but is not limited to: hierarchy of management activities, individuals assigned to roles, generative or adaptive activities, visionary or empowering activities.

[0071] In another use case scenario, system 100 may be used in the context of virtual and / or augmented social networks, blockchain and / or distributed ledger technologies. Specifically, system 100 may generate and establish augmented social networks and / or communicatively link with augmented social networks for each user and / or group of users. Once established, the user's enhanced social network can be activated via contingent protocols and contracts using blockchain technology and associated proprietary cryptocurrencies. In some embodiments, each user of system 100 can have a storage of cryptocurrency points. For example, in some embodiments, a user can accumulate cryptocurrency points (e.g., digital points) from system 100 for use in providing feedback and guidance to other users of system 100. In some embodiments, a user can also accumulate cryptocurrency through transactions with other users, such as, but not limited to, payments for project work. In some embodiments, these cryptocurrency transactions can, but do not necessarily, be tracked via blockchain or other similar technologies.

[0072] In some embodiments, each user can be configured to view and / or access only their own individual network within the virtual social network and be invisible to other networks associated with other users. This can be achieved by assigning each user a virtual identifier (e.g., numbers, letters, symbols, and / or any other type of identifier) ​​and a virtual avatar (collectively referred to as Virtual_Node_ID). All information can be transmitted to these secure and anonymous Avatar_Node_IDs. In some embodiments, portions of the virtual network may be visible to administrators and other levels, but only in a completely anonymous manner. In other words, a first user 101 can view the virtual_network and identify highly connected or centralized virtual_nodes to understand the organization's internal social network structure, including factors such as subject-specific expertise, contributions, engagement, and trust.The directional strength of various connections across all dimensions. However, the user cannot see through the structure to identify which real users are associated with which Avatar_Node_IDs, or which virtual interactions exist between which real users. In some embodiments, the user may be able to infer some reflections of reality into the virtual_network; however, the system 100 does not and cannot verify this information.

[0073] Additionally, in some embodiments, information that the user inputs to or receives from the system 100 at the individual level will never be directly available to these managed users. In some embodiments, only aggregated data is available for inspection and access. In summary: if a person is a level_one user, the user creates items; the user interacts with his / her trusted network; the user enters into service contracts with others and / or transfers cryptocurrency points to others; the user provides feedback to all network members of all users, and the user also receives feedback from individuals in his / her network about what the user is doing and how well the user is doing it. The user is able to communicate anonymously with other real-life users, and the feedback the user receives may be based on real-life experience, allowing the user to process and understand the feedback as appropriate. The user may not know exactly who is providing what feedback. Furthermore, as an option and in some embodiments, the user can select individual users in their personal network and choose to have system 100 discard the user's feedback, so that feedback from people the user may not respect or trust will not be part of the user's "trusted feedback" signal. This can be based on one or more User_Interest_States, which are assigned to the user based on the Condition_State_Type assigned to my Avatar_Node in the network. Specification 23 / 36 pages 28 CN 121479065 A

[0074] In another use case, system 100 can be used to create research scenarios. In some embodiments, Level 1 users of system 100 typically use system 100 simply to respond to events and provide feedback that will help other users and receive feedback about their own participation and contribution to various events they are involved in. These user interactions with real-life events, when reflected and amplified in the system, occur in scenarios the system calls "research". In System 100, studies can be selected by Level 2 users and designed and conducted by Level 2 and higher users according to the scope of the study. Each study may include a data collection protocol, which involves: 1. a description of the event, including but not limited to self-assessments to be sampled; 2. information about the event to be collected; and 3. methods for collecting this data using various technologies, including but not limited to surveys, sensing devices, and surveillance.Devices, media analytics, wearable technology, geolocation devices, etc.; 4. Data aggregation, classification, and segmentation protocols; 5. Analysis protocols; 6. Intervention possibilities for different categories of results; 7. Reporting protocols, such as presentations and scheduling; and 8. Collecting feedback on the usefulness of reports to users. For example, when a Level 1 user accepts participation in an event, the user becomes part of a study identified by a Level 2 user of the event.

[0075] In some embodiments, the study can be used as a default for new users. Under the default status of a Level 1 user, level 1_Default_Study can be operated. This can be done as follows: 1. Each user receives a query that requests feedback about other people who participate in the event in various ways. The user's name is not included in the query because no feedback is provided to themselves. 2. The user selects Participant_1 (listed by the real name given in the account). 3. If the role of Participant_1 is defined as "participant", then the user is asked to rate the user on certain survey items (i.e., questions), such as, but not limited to, "level of participation" and "level of contribution". 4. If Participant_l's role is defined as "Presenter," then users are asked to rate the user on other items, such as, but not limited to, "Preparation" and "Relevance." This complements the query associated with becoming a participant. 5. If participant_l has the role of Subject Matter Expert (SME), then users are asked to rate the SME on other items, such as, but not limited to, "Clarity in answering questions" and "Willingness to participate in the questioner's understanding." This complements the query associated with becoming a participant. 6. Other roles can be defined, and additional questions can be defined for each role by users at level 2 or higher with appropriate permissions. 7. Input can be a scale from 1 to 100, but the actual format of the data collection can be customized. For example, respondents might be asked to choose one of five smiley faces ranging from deep frown (0) to neutral (50) to extreme smile (100). As another example, respondents may be asked to indicate the participant's level of preparedness, or some other attribute such as the relevance, authenticity, clarity, respectfulness, or whether "worked for me" was "below expectations" or "even more is better," where the system rates responses on a scale ranging from -1 to 0 to +1, with 0 being ideal. However, in some or all of these situations, it is assumed that data is identified as scores along a continuous scale from 1 to 100. 8. Users may be asked questions about the state of the entire team or multi-team system and / or its performance in the event. This can be done using a tool with scales that measure one or more aspects of the team, multi-team system, or organization's performance. 9. Once information about the event is gathered from all participants...Once all other participants' data or events have concluded (first come, first served), the system will identify users with sufficient data from the responses of other users to maintain anonymity for each individual, and reports will be prepared for those who can receive anonymous feedback. 10. Send a notification to each user that feedback is ready. 11. Those users who receive feedback may be presented with a range of reports defined by the study. For example, they may choose to view a simple report on their average score in the previous event, a report comparing the results of several recent events, or a report on the overall team score.

[0076] Regarding the default status of Level 2 users, level2_Default_Study can be operated. This can be done as follows: 1. Each user receives a query that requests feedback on others who participated in the event in various ways. The user's name is not included in the query because no feedback was provided to them. 2. The user selects Participant_1 (listed by the real name given in the account on page 24 / 36 of the manual, CN 121479065 A). 3. If Participant_l's role is defined as "Participant," then users are required to rate the user on certain items, such as, but not limited to, "level of participation," "level of contribution," "level of subject matter expertise," "level of opinions valued by others," and "level of role experience." 4. If Participant_l's role is defined as "Presenter," then users are required to rate the user on certain items, such as, but not limited to, "level of preparation" and "level of relevance." 5. Other roles can be defined, and additional questions can be defined for each role by users at level 2 or higher with appropriate permissions. 6. Input can be a scale from 1 to 100, but the actual format of the data collection can be customized. For example, respondents might be asked to choose one of five smiley faces ranging from deep frown (0) to neutral (50) to extreme smile (100). As another example, respondents may be asked to indicate the participant's level of preparedness, or some other attribute such as the relevance, authenticity, clarity, respectfulness, whether "worked for me" was "below expectations" or "even more is better," where the system rates responses on a scale ranging from -1 to 0 to +1, where 0 is ideal. However, in some or all cases, it is assumed that data is identified as scores along a continuous scale from 1 to 100. 7. Users may also be asked to use similar scales to answer questions about the performance of the entire team or multi-team system in the event, including, but not limited to, identifying the members who contributed the most to the event or project. 8. Once all data about all other participants in the event has been collected from all participants, or the event ends (first come, first served), the system 100 identifies users with sufficient data from the responses of other users.To maintain anonymity for each individual, and the reports are prepared for those who can receive anonymous feedback. 9. Additionally, team and multi-team level reports are produced for Level 2 and above users to view. 10. A notification is sent to each user that feedback is ready for them, for example, to the first user device 102 and / or the second user device 111. 11. A range of various reports defined by the study are presented to those users who receive feedback. For example, they may choose to view a simple report on the average score of their role in the previous event, a report comparing the results of several recent events, or a report on the overall team or multi-team system score.

[0077] In some embodiments, Level 6_Default_Study can be operated in the default state for Level 6 BOD users. This can be done as follows: 1. Each user receives a query that requests feedback on other people who participated in the event in various ways. The user's name is not included in the query because no feedback was provided to them. 2. The user selects Participant_1 (listed by the real name given in the account). 3. If Participant_l's role is defined as "Participant," then users are required to rate the user on certain items, such as, but not limited to, "level of participation," "level of contribution," "level of subject matter expertise," "level of opinions valued by others," and "level of role experience." 4. If Participant_l's role is defined as "Presenter," then users are required to rate the user on certain items, such as, but not limited to, "level of preparation" and "level of relevance." 5. Other roles can be defined, and additional questions can be defined for each role by users at level 2 or higher with appropriate permissions. 6. Input can be a scale from 1 to 100, but the actual format of the data collection can be customized. For example, respondents might be asked to choose one of five smiley faces ranging from deep frown (0) to neutral (50) to extreme smile (100). As another example, respondents may be asked to indicate the participant's level of preparedness, or some other attribute such as the relevance, authenticity, clarity, respectfulness, whether "worked for me" was "below expectations" or "even more is better," where the system rates the response on a scale ranging from -1 to 0 to +1, where 0 is ideal. However, in some or all cases, it is assumed that the data is identified as scores along a continuous scale from 1 to 100. 7. Users may, but are not necessarily required to, use a similar scale to respond to questions about the performance of the entire BOD team in the event. 8. Once all data about all other participants in the event has been collected from all participants or the event has ended (first come, first served), the system 100 will identify users with sufficient data from the responses of other users to maintain anonymity for each individual.The report is prepared for those who can receive anonymous feedback. 9. Additionally, BOD-level reports are produced for Level 6 BOD users to view. 10. A notification is sent to each user that feedback is ready for them. 11. A range of various reports defined by the research are presented to those users who receive feedback. For example, the user may choose to view a simple report on the average score of their role in the previous event, a report comparing the results of several recent events, or a report on the scores of components of the entire team or multi-team system.

[0078] In some embodiments, various types of research may be available for use in System 100. It is worth noting that research may involve the collection, classification, processing, and reporting of information about individuals, groups of individuals, interactions, organizations, and institutions. Research is designed and operated by Level 2 or higher users according to their permissions. Additionally, surveys may also be used in conjunction with System 100. Surveys may be tools for collecting data from target individuals at a certain point in time. In some embodiments, several types of research may be available for use in System 100. Research may include, but is not limited to: 1. Pilot studies: collecting data for a group, organization, or institution at a point in time in a test or prototype environment for the purpose of developing empirical measurement tools that can be used in other studies. (a) An example of this is a pilot study with 20 surveys that have empirical scales for measuring hypothetical factors, such as “innovator.” The pilot study will collect data to perform validation analyses and tests to determine whether the surveys provide a valid and consistent measure of the hypothetical factors. 2. Transaction studies: collecting data at a point in time associated with a specific transaction, such as an event involving a group, organization, or institution. (a) An example of this is a two-part survey that has an empirical scale for measuring “customer satisfaction” associated with a customer event. The survey will be conducted at a point in time with the aim of understanding the customer satisfaction dimension of the Environment_State_Variable for that specific event. 3. A cross-sectional study collects data across a group, organization, institution, or community at a point in time, including but not limited to individual rankings. (a) An example of this is a five-item survey with an empirical scale for measuring “employee engagement,” conducted at a point in time with the aim of understanding this dimension of the Organization_State_Variable. 4. A longitudinal study collects data from a group, organization, or institution over a period of time in an effort to understand trends or changes in the subject matter. (a) An example of this is a five-item survey with an empirical scale for measuring “employee engagement,” conducted at several points in time with the aim of understanding this dimension of the Organization_State_Variable.5. A comparative study collects data at a point in time from two or more instances of a type of workgroup, organization, or institution. (a) One example of this is a five-item survey with an empirical scale for measuring “employee engagement,” conducted at a point in time with each person in five different hospitals to compare these goals along this dimension of the Organization_State_Variable. 6. A predictive study collects data at a point in time or over time on multiple factors aggregated from multiple instances of an individual, workgroup, organization, or institution of a target type. These studies are called predictive because the values ​​of one or more of these factors are considered to predict the values ​​of other measurable factors. The study analyzes this data with the aim of predicting other measurable outcomes. (a) One example of this is a five-item survey with an empirical scale for measuring “employee engagement,” conducted at a point in time with each person in five different hospitals to compare these goals along this dimension of the Organization_State_Variable. 7. Simulation studies collect data on multiple factors at a point in time or over time, which are aggregated from multiple instances of individuals, workgroups, organizations, or institutions of a particular target type. These studies use this data, combined with theoretical and empirical findings from predictive studies, to model the values ​​of other variables (e.g., but not limited to Organization_State_Variable, Environmental_State_Variable, and Leadership_Activities_Variable) at a future point in time. These studies analyze numerical data with the aim of identifying possible interventions to improve the outcomes measured by these variables. (a) An example of this is a five-item survey with an empirical scale for measuring “customer excitement,” conducted on participants in a customer meeting (Environmental_State_Variable). The results are used in a numerical model running on a computer to simulate the probability distribution of potential sales for various products in the next quarter (Organization_State_Variable), allowing for adjustments to production based on the most probable outcome.

[0079] In some embodiments, Level 2 or higher users may be allowed to select and / or create studies for System 100.For example, a user with appropriate permissions can establish a study by taking the following steps: 1. Establish a new study and create a Study_ID. 2. Select or create a survey. 3. Select an event or event type. 4. Schedule data collection. 5. Add participants to the meeting or event and assign roles. 6. Select and schedule analysis and reporting. Data from all studies can be stored as individual response records and indexed by some (but not limited to) User_ID, date and time of the event, date and time of the response, event, Event_Type, project, Project_Type, institution, Institution_Type, team, Team_Type, and organization code, so that all of the above can be accessed and analyzed in future studies.

[0080] In another use case, system 100 can be used to generate and maintain intelligent, personalized, and curated messaging. In addition to transaction- or event-based feedback, in some embodiments, system 100 may also have, but is not limited to, the following options: providing personalized stored media for guidance and coaching, and connecting to live or peer-to-peer guidance sessions, whether live-streamed, recorded, computer-generated, or via video, audio, holograms, or animation. In some embodiments, this may include information provided by an organization relating to individual contributors. This allows organizations to utilize the system to translate guidance tips and insights, academic and practical articles. Some or all of these may be selected based on a user’s unique history and User_Interest_State as a deterministic machine and human learning and intelligence. In some embodiments, curated media is sent to users at regular intervals throughout the day via the application; however, particularly relevant media identified may overshadow the normal schedule. In some embodiments, specific media presented to each user is uniquely selected based on a topic matrix determined by system 100, machine learning and artificial intelligence algorithms, or human expert curators. This may be done as follows: 1. When media is created or identified from other sources, its copyright and distribution rights may be determined by system 100. Media created on System 100 by other System 100 users may, but not necessarily, be allocated Cryptocurrency (CCC) points as described herein, based on a one-time license or usage. 2. Items available for distribution on System 100 are screened, and any CCC rights or payments are written to the blockchain described in the usage scenarios described herein. 3. Using machine learning, artificial intelligence algorithms, or human experts, media content is tagged with a topic matrix containing vectors from various topic areas, such as, but not limited to, impact skills, verbal communication skills, team leadership, motivation, projects, management, etc., which includes relevant situational dimensions, such as industry, management level, geographical perspective, etc. 4. For each user, based on5. Select and score media based on the matching of User_Interest_State with topic_matrix for each content item. 6. Build a messaging service for each user based on the relative scores of various media content and send it to the user's messaging queue. 7. Send a notification from the messaging queue to the user, and present the messaging options to the user while using the application. In some embodiments, it should be noted that User_Interest_State is assigned to each user by system 100 based on Condition_State_Type assigned to the secure Avatar_Node_ID of the user in the Virtual Augmented Social Network (V-ASN).

[0081] In some embodiments, Condition_State_Type may be a category of conditional state. During batch processing, on the virtual network server, for each Avatar_Node_ID, its Condition_State may, but not necessarily, be processed using machine learning and artificial intelligence techniques (e.g., but not limited to cluster analysis) to project relevant and / or closely related groups of Condition_State onto a finite number of Condition_State_Types (CST). In some embodiments, it should be noted that Condition_State includes, but is not limited to, a complete history of all interactions with other Avatar_Node_IDs, Event_Reports, and possible situational data, such as, but not limited to, Environmental_State_Variable, Organizational_State_Variable, or Leadership_Activity, and, but not limited to, other personality, cognitive, biometric, or physical metrics associated with the Avatar_Node_ID. These Condition_States can be defined by an administrator based on, for example, but not limited to, algorithms, machine learning, artificial intelligence, or human experts, to classify conditional states into a limited space of user interest regions for social learning. In some embodiments, Condition_State_Type is used to identify relevant media to be presented to a unique user associated with the Avatar_Node_ID. In some embodiments, each user has one or more Interest_States. Each Condition_State_Type for a given Avatar_Node_ID can be mapped to its corresponding User_ID as its User_Interest_State at that point in time. Interest_State can also be...Data may not include, but is not limited to, the following specific situations: 1. Environmental_State_Variable may include, but is not limited to: government or regulatory issues, economic or political conditions, supplier and logistical considerations, customer or buyer needs, industry macro conditions and competition, threats of new entrants and substitutes, etc. 2. Organizational_State_Variable may include, but is not limited to: formal organizational structure; multi-team systems, workgroups, departments or organizational goals; organizational policies, budgets, financial status; etc. 3. Leadership_Activity_Variable may include, but is not limited to: hierarchy of management activities, generative or adaptive activities, vision or empowering activities.

[0082] In another use case, System 100 can be used in the context of the audience-centric Credible Feedback PACER scale. The PACER scale is a system and method for using electronic devices, computers, software and memory to sense and collect distributed data on the interpersonal benefits of a focus individual in human interactions, human-computer interactions and machine-to-machine interactions. For the purposes of this use case and other use cases, an individual may be defined as human or machine, such as, but not limited to, a robot, robot agent, software agent, artificial intelligence system, or any system combining human and machine learning algorithms, whether implemented in hardware, software, or both, and whether or not integrated with human activities. The collected and processed data may be analyzed and formatted to provide credible feedback to a focus individual (e.g., first user 101 and / or second user 110) via electronic media to help the focus individual better understand his or her benefit in interactions with their individual colleagues or with a personal audience. This feedback may be based on the reactions of each colleague or audience member who collectively records their personal reactions to the value of the focus individual's interactions with them, as experienced from their individual personal vantage point. In some embodiments, this concept deviates from feedback systems where people simply rate the actions and behaviors of the feedback recipient on arbitrary scales (e.g., a Likert scale with five choices) based on the feedback provider's perception of the focus individual, ranging from "strongly agree" to "strongly disagree." In contrast, the PACER indicator records the reactions of "others" to opinions that are valid for the individual, taking into account their responsibility, knowledge, emotional state, other states, or combinations thereof.

[0083] In some embodiments, the PACER scale can provide feedback recipients with opinions that are "valid" for the feedback provider. This is a quantifiable approach that allows feedback recipients to consider various perspectives from different members of the audience.The degree of engagement, including but not limited to their perceived perspective on participation or contribution to the monitored event, measures content that plays a role across several attributes. Other attributes may include, but are not limited to, preparation, respect, support, use of evidence, clarity of thought, clarity of communication, personal hygiene, authenticity, active listening, emotional intelligence, leadership, facilitation skills, social skills, organizational citizenship behavior, decisiveness, creativity, usability, attention, focus, and competence across various dimensions, including but not limited to digital technology, other technical fields, industry knowledge, market knowledge, organizational knowledge, management, leadership, or functional areas such as, but not limited to, marketing, finance, operations, human resources, and / or research and development. One difference from other methods is that the value of the event, content, or more generally, is also implicit in the response. For example, a well-expressed argument supporting an unrelated topic might score lower. Feedback recipients may receive “what works for me” feedback from each member of the audience, which relates to a range of specific contribution attributes, which may be individual or aggregated, and the feedback recipients may or may not be anonymous. In an unrestricted embodiment, the scale may be as follows: If the feedback recipient's presentation or a specific contribution attribute works effectively for the audience member (see page 28 / 36 of CN 121479065 A), then the audience member will indicate on the system that this will be rated 0 (zero) by the system. A score of 0.5 tells the feedback recipient that more of the specific contribution attribute would be more effective for the audience member. A score of 1 tells the feedback recipient that more of the specific contribution attribute would be more effective. A score of -0.5 tells the feedback recipient that, from the audience member's perspective, the specific feedback attribute is "slightly below expectations." A score of -1 tells the feedback recipient that, from the audience member's perspective, the specific feedback attribute is "significantly below expectations." A score of 0 tells the recipient that their participation "worked for me," i.e., the responding user. In another embodiment, system 100 may present the first user with attributes such as, but not limited to, "contribution," and a list of names of users present at the event. One of the users present may be a second user. To provide feedback to the second user, the first user can simply click on the name indicating "works for me," or the user can slowly swipe right to indicate "a little more would be better," or quickly indicate "a little more would be better." As an option, the user can slowly swipe left to indicate "somewhat unsuitable for me" or quickly swipe to indicate "really unsuitable for me." In another embodiment, the user can simply say the text indicated in the quotation marks above.

[0084] In some embodiments, for this use case or other suitable use case scenarios, specific measurable contribution attributes may be, but are not limited to, relevance, authenticity, energy, evidence, preparation, and clarity. In a preferred embodiment,Each contribution attribute can be prompted to the feedback provider via, but is not limited to, their electronic device, and they will simply: tap on the user interface screen of the first user device 102 to get an index 0 (thank goodness, it works for me). Slowly swipe right (e.g., on the user interface screen) to get an index 0.5 (a higher index would be more effective for me). Quickly swipe right to get an index 1 (a higher index would be more effective for me). Slowly swipe left to get an index 0.5 (slightly below expected). Quickly swipe left to get an index -1 (far below expected). Scales such as, but not limited to, Likert scales can be used to measure participation and contribution values ​​for the same event, allowing the PACER scale to be calibrated based on participation and contribution results to determine the correlation between a particular contribution attribute and participation and contribution. In some embodiments, a single user interaction can provide feedback to all users.

[0085] An exemplary use case involving the PACER scale might be as follows: conducting meetings and / or events. This is a meeting to discuss the progress of the XYZ project. Team leader Sally organizes the meeting, manages logistics, and sets the agenda. The meeting begins at time 0, and Sally announces the start of the meeting. There are three presenters and five additional participants, for a total of nine team members. Each team member will have the opportunity to provide their PACER feedback to each of the other eight team members based on their specific reactions to the engagement and contributions of the other team members. During or after the event, each team member will be able to simply click or swipe on each of the other team members' names or avatars displayed on their device. Six specific contribution attributes will be continuously displayed on the screen for event participants to click or swipe on based on their reactions to the contributions or engagement of the other meeting participants.

[0086] For example, event participant Joe, while listening to event presenter Tina, will be able to identify what works for him based on Tina's presentation. He can click on relevance, which will indicate that Tina's presentation is appreciated and "works for him." He might think the evidence in her presentation "works for him," but if he thinks more evidence would be more effective, he will slowly swipe to the right. Because it involves her authenticity, Joe might think Tina is somewhat unauthentic and might slowly swipe to the left. Regarding preparation, Joe considers Tina's preparation "effective for him" and will click the "Ready" button again. In terms of clarity, Joe thinks Tina's presentation is very clear, and therefore he will click the "Clarity" button, "Thanks and effective for me," resulting in a 0 PACER index. Ultimately, even though Joe considers Tina's presentation clear, relevant, well-documented, and that she came prepared, he thinks her energy level is low, so he slowly swipes left, letting Tina know that "it's slightly below expectations for me." Therefore, forIn this event, Tina's Jack PACER vector feedback will be recorded as: MTina(Relevance, Authenticity, Energy, Evidence, Preparation, Clarity) = (0, -0.5, -0.5, 0.5, 0.5, 0, 0). The other seven meeting participants will provide their inputs to Tina, and Tina will be able to receive aggregated PACER metrics for this event Y. Tina will also receive perceived data from team members regarding engagement and contribution, allowing her to understand which areas are effective for her audience, where she did well, and where she could do better. PACER data can be sorted in various ways: by event, by time, by most important audience, etc., providing each meeting participant with various avenues to discover which of their contributions had the greatest impact on their team members / audience. It is worth noting that any other use case scenarios can also be used with System 100 and the methodology.

[0087] It is worth noting that, as shown in FIG1, system 100 can perform any of the operational functions disclosed herein by utilizing the processing power of server 160, the storage capacity of database 155, or any other component of system 100. Server 160 may include one or more processors 162, which may be configured to process any of the various functions of system 100. Processor 162 may be software, hardware, or a combination of hardware and software. In addition, server 160 may also include memory 161 storing instructions that processor 162 can execute to perform various operations of system 100. For example, server 160 may assist in handling loads handled by various devices in system 100, such as, but not limited to, transmitting queries to users and / or devices to request information and / or feedback associated with other users and / or devices in system 100; obtaining requested information from users and / or devices; associating the obtained information with one or more avatars in the virtual social network of system 100; creating avatars in system 100; generating conditional state data for avatars; determining interest state data for users and / or devices in system 100; generating reports and / or recommendations for users and / or devices to assist users and / or devices in improving their performance in future events; transmitting reports and / or recommendations to users and / or devices; performing machine learning in system 100; and performing any other suitable operations performed in system 100 or otherwise. In one embodiment, multiple servers 160 may be used to process the functions of system 100. Server 160 and other devices in system 100 may utilize database 155 for storing data about devices in system 100 or related to the system.Any other information associated with 100. In one embodiment, multiple databases 155 may be used to store data in system 100. In some embodiments, server 160 may contain any number of program modules, which may contain software for performing various operations performed by server 160.

[0088] Although Figures 1 to 5 illustrate specific instance configurations of various components of system 100, system 100 may include any configuration of components, which may include more or fewer components. For example, system 100 is illustrated as including a first user device 102, a second user device 111, a third user device 115, a computing device 120, a firewall 125, FFSS 302, a mapping server 304, sDAASS 306, CFSS 308, A&PSS 310, a communication network 135, servers 140, 145, 150, 160, and database 155. However, system 100 may include multiple first user devices 102, multiple second user devices 111, multiple third user devices 115, multiple computing devices 120, multiple firewalls 125, multiple FFSS 302, multiple mapping servers 304, multiple sDAASS 306, multiple CFSS 308, multiple A&PSS 310, multiple communication networks 135, multiple servers 140, multiple servers 145, multiple servers 150, multiple servers 160, multiple databases 155, or any number of other components internal or external to system 100. Furthermore, in some embodiments, a significant portion of the functionality and operation of system 100 may be performed by other networks and systems connectable to system 100.

[0089] It is noteworthy that system 100 may perform and / or conduct the functionality described in the following methods. As shown in FIG4, an exemplary method 400 for technical support, credible performance feedback, and experiential learning is schematically illustrated. Method 400 may include steps for obtaining feedback information about users participating in an event and for generating reports and / or recommendations to be provided to users to enhance their performance in future events. At step 402, method 400 may include transmitting a query to a first user device 102 associated with a first user (e.g., first user 101) to request information related to a second user (e.g., second user 110) regarding the benefits of the second user's participation in an event in which the first user also participates. In some embodiments described on pages 30 / 36 of CN 121479065 A, this can be achieved by utilizing the second user device 111, wearable device 115, computing device 120, FFSS 302, mapping server 304, sDAASS 306, A&PSS 310, server 140, server 145, server 150, server 160, and communication network.135, external network 165, any combination thereof, or by utilizing any other suitable program, network, system, or device to perform and / or facilitate the transmission of the query.

[0090] At step 404, method 400 may include obtaining information from the first user device 102 relating to the benefits of the second user's participation in the event and / or relating to any content of interest relevant to the second user. In some embodiments, obtaining information relating to the benefits of the second user may be performed and / or facilitated by utilizing the first user device 102, wearable device 115, computing device 120, FFSS 302, mapping server 304, sDAASS 306, A&PSS 310, server 140, server 145, server 150, server 160, communication network 135, external network 165, any combination thereof, or by utilizing any other suitable program, network, system, or device. At step 406, method 400 may include associating the obtained information with a first incarnation of a first user identifier mapped to the first user. In some embodiments, step 406 may include assigning a rating or ranking of abilities acquired by the first user to the first avatar. This may include, but is not limited to, abilities such as: transformational contributor, autonomous contributor, collaborative contributor, expert contributor, flexible contributor, organizational contributor, true contributor, transformational leader, transactional leader, innovative leader, creative leader, flexible leader, team leader, true leader, servant leader, manager, director, executive, etc. In some embodiments, the first avatar may be an anonymized virtual representation of the first user, for example, within a virtual network (e.g., a virtual social network) of system 100. System 100 may also include a second avatar mapped to a second user identifier (e.g., second user 110). In some embodiments, the association of obtaining information can be performed and / or facilitated by utilizing a first user device 102, a wearable device 115, a computing device 120, an FFSS 302, a mapping server 304, an sDAASS 306, an A&PSS 310, a server 140, a server 145, a server 150, a server 160, a communication network 135, an external network 165, any combination thereof, or by utilizing any other suitable program, network, system, or device.

[0091] At step 408, method 400 may include generating first conditional state data for a first avatar of a first user and second conditional state data for a second avatar of a second user. In some embodiments, the first conditional state data for the first avatar and the second conditional state data for the second avatar may be generated for one or more time instances, the first conditional state data and the second conditional state data representing a virtual network of system 100 (e.g., virtualThe relationship between the first and second avatars in a social network. In some embodiments, the generation of first and second conditional state data for the first and / or second avatars can be performed and / or facilitated by utilizing a first user device 102, wearable device 115, computing device 120, FFSS 302, mapping server 304, sDAASS 306, A&PSS 310, server 140, server 145, server 150, server 160, communication network 135, external network 165, any combination thereof, or by utilizing any other suitable program, network, system, or device. Once the first and second conditional state data are generated, method 400 may include generating a report, recommendation, or a combination thereof for the second user at step 410. The report, recommendation, or combination thereof may include guidance and / or information that enables and / or promotes the second user to improve their benefit regarding future events. In some embodiments, the generation of the report, recommendation, or combination thereof may be performed and facilitated by utilizing a first user device 102, wearable device 115, computing device 120, FFSS 302, mapping server 304, sDAASS 306, A&PSS 310, server 140, server 145, server 150, server 160, communication network 135, external network 165, any combination thereof, or by utilizing any other suitable program, network, system, or device. Once the report, recommendation, or combination thereof is generated, method 400 may include providing the report, recommendation, or combination thereof to a second user at step 412 to assist the user in improving the second user's benefit regarding future events in which the second user will participate. For example, the report, recommendation, or combination thereof may be transmitted from one or more devices of system 100 to the second user device 111 of the second user 110. In some embodiments, the provision of reports, recommendations, or combinations thereof may be performed and facilitated by utilizing a first user device 102, wearable device 115, computing device 120, FFSS 302, mapping server 304, sDAASS 306, A&PSS 310, server 140, server 145, server 150, server 160, communication network 135, external network 165, any combination thereof, or by utilizing any other suitable program, network, system, or device. It is noteworthy that method 400 may further include any of the features and functionalities described for system 100, any other methods disclosed herein or otherwise described herein. In some embodiments, the report or recommendation may include, but is not limited to, specific assessments related to the notification to the first or second user of capabilities already achieved by the user.Information on grades or levels may include, but is not limited to, information about how the user may be able to achieve one or more of a variety of capabilities, which may be, but are not limited to: transformational contributor, autonomous contributor, collaborative contributor, expert contributor, flexible contributor, organizational contributor, true contributor, transformational leader, transactional leader, innovative leader, creative leader, flexible leader, team leader, true leader, servant leader, manager, director, executive, etc.

[0092] In some embodiments, another exemplary method may be provided. In this method, the method may include the steps of having the user (e.g., first user 101) register with an application (e.g., FFSS 302) of system 100 and complete a user profile using the application, which provides a variety of functionalities and features provided by system 100. For example, the application may be executed on a first user device 102 of first user 101 and may be visually presented to the first user through an interface 105 of the first user device 102. Once a user registers with the application and completes his or her profile, the user may choose to remain logged into the application and keep the application open on the first user device 102. This allows the system 100 to continuously interact with other applications, such as, but not limited to, calendar applications like Google Calendar, Google Docs, and Office 365, and communication applications like Slack, data analytics and visualization applications like Excel, messaging systems, GPS mapping systems, and / or any other applications. In some embodiments, the application may provide screen overlay permissions and will allow notifications from the application to interrupt other user activities (e.g., on the first user device 102 or elsewhere) when feedback needs to be provided or received.

[0093] The method may further include transmitting notifications via the application that will remind the first user 101 to provide feedback about other people (e.g., a second user 110) for their learning. For example, the feedback may relate to the other user's effectiveness, performance, and / or ability in an upcoming event. The method may then include receiving feedback from the user via the application about one or more other users. In doing so, the first user 101 can answer queries about the event and about the second user 110 who participated in the event with the first user 101. Once the first user 101 inputs feedback and / or response to the query into the application, the first user 101 can press a submit button (e.g., via the application's graphical user interface) to securely transmit the data to various subsystems of system 100, such as sDAASS.306. In some embodiments, once the data has been securely transmitted to various subsystems of system 100 (e.g., FFSS 302, sDAASS 306, CFSS 308, A&PSS 310, etc.), the data can be erased from the first user device 102. Once the data is received at one or more of the various subsystems, the method may include having one or more of the subsystems aggregate and analyze the data for the first user 101, the second user 110, any other user, or a combination thereof. The method may then include having the subsystems generate and prepare reports for expert analysis.

[0094] In some embodiments, the method may then include having an expert human and / or machine (e.g., any component of system 100) analyze the report at a point in time and identify the individual's conditional state and determine appropriate guidance material to assist the user. The guidance material may, but is not necessarily, included in the recommendation package, which may be a digital file containing various information and content to assist the user in improving, for example, performance, effectiveness, and / or capabilities in future activities and / or events (see page 32 / 36 of the instruction manual, CN 121479065 A). Once a recommendation package is generated for the second user 110 (and / or other users), CFSS 308 may transmit the recommendation package to an application running on the second user device 111 of the second user 110 (or other users, as needed). The method may also include transmitting a notification of receiving feedback to the second user device 111 of the second user 110. The user may confirm that they want to receive feedback via the notification and may receive feedback or coaching based on existing events that have already occurred. In some embodiments, certain portions of the guidance material may include a usage deadline, which may, but may not, trigger a notification to the user, publisher, or other agent (whether human, machine, or a combination thereof) to update the material. Existing events may be aimed at raising the user's awareness or anticipation of upcoming events, and the expectation of helping the user perform better in upcoming events. By selecting which feedback and suggestions to receive, the method may include enabling a user to receive recommendations based on the user's specific experiences, such as feedback comments reflected in other people with whom the user has previously interacted, including users expected to appear in upcoming events. In some embodiments, the method may include enabling the user to store preferences about how the user would like to give and / or provide feedback, for example, through an application. The method may then include prompting the user to provide feedback on the suggestions they receive, including questions about whether the suggested intervention was formulated by the user and, if so, its usefulness to the user. It is worth noting that the features and functionality provided by the method may be combined with any of the other features of other methods and / or systems described in this disclosure.

[0095] The systems and methods disclosed herein may include additional functionality and features. In some embodiments, the systems and methods may be used in conjunction with any type of social media platform and / or system. For example, the functionality provided by the systems and methods may be integrated with and / or communicatively linked to social media applications such as Facebook®. In such embodiments, for example, a user may be able to receive anonymous feedback from a subset of trusted friends regarding posts the user has made on a social media application and / or events the user has participated in. In some embodiments, the systems and methods may be used in conjunction with online (or augmented reality) groups using gaming systems and / or applications. For example, the systems and methods may be used in large online multiplayer games such as World of Warcraft, where gamers (or other users) can receive anonymous feedback from a trusted subset of their friends regarding their gaming abilities. In some embodiments, the systems and methods may be used in conjunction with voting systems. In some embodiments, the systems and methods may be used in conjunction with academic projects. For example, students may use the systems and methods to comment on and provide feedback on the participation and effectiveness of other students during classroom projects and / or assignments. In other embodiments, the systems and methods may also be used in other ways. For example, the data collected and / or generated by the systems and methods can be used for social science research and the design of robotics or future machine learning and / or artificial intelligence systems. Additionally, the data aggregated through the systems and methods can be used to generate other products, services, devices, compositions, or other useful items. For example, the systems and methods can be used, but are not limited to, for training purposes in professional academic environments, or the data and systems can be used to develop simulation exercises for training purposes.

[0096] The systems and methods disclosed herein may include other functionalities and features. For example, the operational functions of system 100 and methods can be configured to execute on a dedicated processor specifically configured to perform the operations provided by system 100 and methods. Notably, the operational features and functionality provided by system 100 and methods can enhance the efficiency of computing devices used to facilitate the functionality provided by system 100 and various methods disclosed herein. For example, by training the system 100 over time based on feedback, data, and / or other information provided and / or generated within the system 100, the reduced amount of computer operations required by the devices in the system 100 using the system 100's processor and memory, compared to conventional methods, is achieved. In this case, less processing power is needed because the processor and memory are not dedicated to processing. Therefore, by utilizing the software, techniques, and algorithms provided in this disclosure, significant savings in the utilization of computer resources can be achieved. In some embodiments, various operational functionalities of the system 100 can be configured to...For execution on one or more graphics processing units (GPUs) and / or dedicated integrated processors (DIS). For example, operations associated with the operation of the avatar and / or media specification pages 33 / 36 38 CN 121479065 A content can be executed on a GPU, and in some embodiments, artificial intelligence and / or machine learning algorithms that facilitate such learning as the system 100 learns over time the various actions performed in the system 100 can also be executed on a GPU and / or a DIS.

[0097] It is worth noting that in some embodiments, various functions and features of the system 100 and methods can operate without any human intervention and can be performed entirely by computing devices. In some embodiments, for example, multiple computing devices can interact with the devices of the system 100 to provide functionality supported by the system 100. Additionally, in some embodiments, the computing devices of the system 100 can operate continuously and without human intervention to reduce the possibility of errors being introduced into the system 100. In some embodiments, the system 100 and methods can also provide efficient computing resource management by utilizing the features and functions described in this disclosure. For example, in some embodiments, upon receiving feedback and / or other data regarding the user's benefits in system 100, any device in system 100 may transmit signals to the computing device receiving or processing the feedback and / or other data indicating that only a specific amount of computer processor resources (e.g., processor clock cycles, processor speed, etc.) are available to process the feedback and / or other data, and / or any other operation performed by system 100, or any combination thereof. For example, the signals may indicate that multiple processor cycles of the processor are available to process the feedback, and / or specify any of the selected amounts of processing power generated or the operations performed by system 100 that can be dedicated to. In some embodiments, signals indicating a specific amount of computer processor resources or computer memory resources to be used to perform operations of system 100 may be transmitted from the first user device 102 and / or the second user device 111 to the various components of system 100.

[0098] In some embodiments, any device in system 100 may transmit signals to a memory device such that the memory device dedicates only a selected amount of memory resources to various operations of system 100. In some embodiments, system 100 and method may further include transmitting signals to a processor and memory to perform operational functions of system 100 and method only during time periods when the utilization rate of processing resources and / or memory resources in system 100 is at selected values. In some embodiments, system 100 and method may include transmitting signals to memory devices in system 100, the signals indicating which specific segments of the memory are used to store any of the data utilized or generated by system 100. It is worth noting that the transmission to...Signals from the processor and memory can be used to optimize the utilization of computing resources when performing operations by system 100. Therefore, such functionality provides significant operational benefits and improvements compared to existing technologies.

[0099] Referring now also to FIG5, at least a portion of the methods and techniques described with respect to exemplary embodiments of system 100 may include, for example but not limited to, a machine such as, computer system 500 or other computing devices, within which an instruction set, when executed, enables the machine to perform any one or more of the methods or functions discussed above. The machine may be configured to assist various operations performed by system 100. For example, the machine may be configured, but not limited to, to assist system 100 by providing processing power to assist in processing loads experienced in system 100, by providing storage capacity for storing instructions or data passing through system 100, or by assisting any other operations performed by or within system 100.

[0100] In some embodiments, the machine may be used as a stand-alone device. In some embodiments, the machine may (e.g., using communication network 135, another network, or a combination thereof) connect and assist operations performed by other machines and systems, such as, but not limited to, first user device 102, second user device 111, third user device 115, computing device 120, firewall 125, server 140, server 145, server 150, database 155, server 160, external network 165, FFSS 302, mapping server 304, sDAASS 306, CFSS 308, A&PSS 310, any other system, program, and / or device, or any combination thereof. The machine may connect to any one or more components of system 100. In a networked deployment, the machine may operate as a server or client user machine in a server-client user network environment, or as a peer-to-peer machine in a point-to-point (or distributed) network environment. The machine may include a server computer, client user computer, personal computer (PC), tablet PC, laptop computer, desktop computer, control system, network router, switch, or bridge, or any machine capable of executing (sequentially or otherwise) a set of instructions specifying actions to be taken by said machine. Furthermore, although a single machine is described, the term "machine" should also be considered to include any set of machines that individually or collectively execute a set (or multiple sets) of instructions to perform any or more of the methods discussed herein.

[0101] Computer system 500 may include a processor 502 (e.g., a central processing unit (CPU), a graphics processing unit (GPU), or both), main memory 504, and static memory 506, which communicate with each other via bus 508. Computer system 500The system may further include a video display unit 510, which may be, but is not limited to, a liquid crystal display (LCD), a flat panel, a solid-state display, or a cathode ray tube (CRT). The computer system 500 may include an input device 512, such as, but not limited to, a keyboard; a cursor control device 514, such as, but not limited to, a mouse; a disk drive unit 516; a signal generation device 518, such as, but not limited to, a speaker or remote control; and a network interface device 520.

[0102] The disk drive unit 516 may include a machine-readable medium 522 storing one or more sets of instructions 524, such as, but not limited to, software embodying any one or more of the methods or functions described herein, including those methods described above. During execution of the instructions by the computer system 500, the instructions 524 may also reside wholly or at least partially in main memory 504, static memory 506, or processor 502 or a combination thereof. Main memory 504 and processor 502 may also constitute machine-readable media.

[0103] Specialized hardware implementations, including but not limited to application-specific integrated circuits, programmable logic arrays, and other hardware devices, can similarly be configured to implement the methods described herein. Applications of devices and systems that may include various embodiments broadly encompass a wide range of electronic and computer systems. Some embodiments implement functionality in two or more specific interconnected hardware modules or have means for communicating related control and data signals between and through the modules, or are implemented as portions of an application-specific integrated circuit. Thus, example systems are applicable to software, firmware, and hardware implementations.

[0104] According to various embodiments of this disclosure, the methods described herein are contemplated for operation as software programs running on a computer processor. Furthermore, software implementations may include, but are not limited to, distributed processing or component / object distributed processing, parallel processing, or virtual machine processing, which may also be configured to implement the methods described herein.

[0105] This disclosure covers a machine-readable medium 522 containing instructions 524 such that means connected to a communication network 135, another network, or a combination thereof can transmit or receive voice, video, or data, and communicate via the communication network 135, another network, or a combination thereof using the instructions. The instructions 524 may further be transmitted or received via a network interface means 520 via the communication network 135, another network, or a combination thereof.

[0106] Although machine-readable media 522 is shown as a single medium in the exemplary embodiment, the term "machine-readable media" should be considered to include a single medium or multiple media (e.g., a centralized or distributed database and / or associated caches and servers) that store one or more sets of instructions. The term "machine-readable media" should also be considered to include any medium capable of storing, encoding, or carrying a set of instructions executable by a machine and causing the machine to perform any one or more of the methods of this disclosure.

[0107] The terms “machine-readable media,” “machine-readable device,” or “computer-readable device” are therefore to be considered to include, but are not limited to: memory devices, solid-state memory, such as memory cards or other packages containing one or more read-only (non-volatile) memories, random access memory, or other rewritable (volatile) memories; magneto-optical or optical media, such as magnetic disks or magnetic tapes; or other self-contained information archives or archive sets considered as equivalent to tangible storage media. “Machine-readable media,” “machine-readable device,” or “computer-readable device” may be non-transitory and, in some embodiments, may not contain a carrier or signal itself. Therefore, this disclosure is considered to include any one or more of the machine-readable media or distribution media listed herein, and includes art-recognized equivalents and successor media in which the software implementations described herein are stored. Specification 35 / 36 pages 40 CN 121479065 A

[0108] The description of the arrangements described herein is intended to provide a general understanding of the structure of various embodiments and is not intended to serve as a complete description of all elements and features of devices and systems that may utilize the structures described herein. Other arrangements may be utilized and derived from this document, allowing for structural and logical substitutions and variations without departing from the scope of this disclosure. The figures are representative only and may not be drawn to scale. Some scales may be enlarged, and others may be minimized. Therefore, the description and figures should be considered illustrative rather than restrictive.

[0109] Thus, although specific arrangements have been described and illustrated herein, it should be understood that any arrangement calculated to achieve the same purpose may replace the specific arrangement shown. This disclosure is intended to cover any and all adaptations or variations of various embodiments and arrangements of the invention. Combinations of the above arrangements and other arrangements not specifically described herein will be apparent to those skilled in the art upon review of the foregoing description. Therefore, this disclosure is not intended to be limited to the specific arrangements disclosed as the best mode for carrying out the invention, but the invention will encompass all embodiments and arrangements falling within the scope of the appended claims.

[0110] The foregoing has been provided for the purpose of illustrating, explaining, and describing embodiments of the invention. Modifications and adaptations to these embodiments will be apparent to those skilled in the art and may be made without departing from the scope or spirit of the invention. After reviewing the foregoing embodiments, it will be apparent to those skilled in the art that modifications, reductions, or enhancements can be made to the embodiments without departing from the scope and spirit of the claims described below. Specification 36 / 36 pages 41 CN 121479065 A Figure 1 Specification Drawings 1 / 5 pages 42 CN 121479065 A Figure 2 Specification Drawings 2 / 5 pages 43 CN 121479065 AFigure 3 Description Drawings Page 3 of 5 44 CN 121479065 A Figure 4 Description Drawings Page 4 of 5 45 CN 121479065 A Figure 5 Description Drawings Page 5 of 5 46 CN 121479065 A Disclosed is a system for providing trusted performance feedback and experiential learning. The system may include receiving, from a first user, feedback related to the effectiveness of a second user in connection with the second user's participation in an event. The system may assign the information to avatars of the first user and the second user. To ensure that a user's information remains private to that user, the avatars may be anonymized virtual representations of the first user and the second user within a virtual social network. Based on an analysis of the information, the system may generate condition state data for the avatars of the first user and the second user respectively. The condition state data may be time series variables that represent a relationship between the avatars. Based on the condition state data, the system may provide a recommendation or report to the second user for improving the seconduser's effectiveness at a future event. Abstract

Claims

1. A system, characterized in that, It includes: Memory, which stores instructions; as well as A processor that executes the instructions to perform operations, the operations including: Generate or identify a first avatar, the first avatar having a mapping to a first identifier, wherein the first avatar is embodied as a first computer program in the system and acts as one of a plurality of nodes in the system’s virtual social network; Information related to the benefits of the first avatar's participation in a first virtual event in which the second avatar also participates is received from a first device associated with the first avatar, wherein at least a portion of the information is provided by at least one sensor or input device that measures task-related activity or interaction information associated with at least one task-related activity or interaction between the first avatar and the second avatar; The information is assigned to the first avatar mapped to the first identifier, and the information assigned to the first avatar mapped to the first identifier is encoded by using a secure mapping key, wherein the first avatar is a virtual representation of the node within the virtual social network of the system, the virtual social network including the second avatar mapped to the second identifier, wherein the first avatar includes the node of the virtual social network, and the second avatar is embodied as a second computer program and includes another node of the virtual social network; By mapping the first avatar to the first identifier, the node of the first avatar is assisted in virtual task-related activities or interactions with the other node of the second avatar in the virtual social network based on task-related activities or interactions between the first computer program and the second computer program; By using an artificial intelligence system and based on the analysis of the information and the task-related activities or interactions, first conditional state data for the first avatar and second conditional state data for the second avatar are generated or identified and stored, wherein the first conditional state data for the first avatar is generated at least in part based on inputs generated by the second avatar that are associated with the first avatar and the virtual task-related activities or interactions between the node of the first avatar and the other node of the second avatar in the virtual social network; By using the artificial intelligence system and based on the first conditional state data for the first avatar, recommendations, media content, or a combination thereof are provided to the first avatar, the recommendations, media content, or a combination thereof being related to the likelihood of improving the first avatar's benefit with respect to a first future event in which the second avatar participates, a second future event in which the second avatar does not participate, or a combination thereof, wherein the recommendations, media content, the first conditional state data, or a combination thereof can be accessed by the first avatar using the secure mapping key; Based on the recommendations, media content, or a combination thereof, feedback is received from a user that relates to enhancing the effectiveness of the first avatar in at least one task-related activity or interaction in the first future event, the second future event, or a combination thereof; The artificial intelligence system is trained based on feedback from the user relating to the effectiveness of enhancing the first avatar's task-related activities or interactions in the first future event, the second future event, or a combination thereof; and By using the artificial intelligence system trained based on the feedback, new recommendations, new media content, or combinations thereof are provided to the first avatar to improve the effectiveness of the first avatar in a third future event.

2. The system according to claim 1, characterized in that, The information related to the benefits of the first avatar includes data collected through surveillance technology, data associated with transportation, logistics, operations, inventory management, or guidance systems, data associated with audio content, data associated with video content, data associated with text analysis, data associated with a global positioning system, data associated with a set of biometric data, or a combination thereof.

3. The system according to claim 1, characterized in that, The operation further includes ensuring the information associated with the first avatar, wherein the privacy is ensured at least in part through confidential computing techniques, trusted execution environments, systems for protecting privacy, mapping of the first avatar to the first identifier, or a combination thereof.

4. The system according to claim 1, characterized in that, The user includes programs, simulation robots, robots, drones, wearable devices, functions, processes, devices, or combinations thereof.

5. The system according to claim 1, characterized in that, The first virtual event is associated with multiple virtual events, or the multiple virtual events are organized into event types, projects, project types, organizations, organization types, or combinations thereof.

6. The system according to claim 1, characterized in that, The operation further includes providing the information to a third-party user, wherein the information and data are provided anonymously or non-anonymously.

7. The system according to claim 6, characterized in that, The third-party user is a subscriber to a plan, account, or a combination thereof.

8. The system according to claim 1, characterized in that, The operation further includes maintaining the quality of data associated with the information, the quantity of data associated with the information, or a combination thereof, wherein the information is provided to or obtained from the first avatar, the second avatar, or a combination thereof.

9. The system according to claim 1, characterized in that, The operation further includes determining the amount of feedback to determine the number of received feedbacks, the type of received feedbacks, or a combination thereof.

10. The system according to claim 1, characterized in that, The operation further includes summarizing the information and other data, wherein the summarized information and other data are provided to a first user, a second user, a third user, or a combination thereof.

11. The system according to claim 1, characterized in that, The operation further includes deleting the information from the mapping server used to assist in assigning the information to the first avatar after the information has been assigned to the first avatar mapped to the first identifier.

12. The system according to claim 1, characterized in that, The first conditional state data further includes self-assessment or self-development data, a complete or partial history of all events, a representation of a portion of the network connections among the first avatar, the second avatar, and other avatars, avatar identifiers, tables of events and event reports, tables of connected avatar identifiers and task-related activities or interaction events, or combinations thereof.

13. The system according to claim 1, characterized in that, The operation further includes processing the first conditional state data as at least one input using the artificial intelligence system and projecting it onto a first conditional state type as at least one output to classify the needs of the first user, the interests of the first user, the media content to be presented to the first user, the connection options to be presented to the first user, or a combination thereof, and / or wherein the operation further includes processing the second conditional state data as at least one input using the artificial intelligence system and projecting it onto a second conditional state type as at least one output to classify the needs of the second user, the interests of the second user, the media content to be presented to the second user, or a combination thereof.

14. The system according to claim 13, characterized in that, The operation further includes mapping the first conditional state type to a first interest state by using the artificial intelligence system, and / or wherein the operation further includes mapping the second conditional state type to a second interest state.

15. The system according to claim 14, characterized in that, The first interest state, the second interest state, or a combination thereof includes environmental state variables, organizational state variables, leadership activity variables, behavioral variables, task-related activity variables, interaction variables, relationship variables, social network variables, communication variables, attitude variables, emotional state variables, cognitive state variables, ability variables, knowledge variables, management activity variables, or a combination thereof.

16. The system according to claim 1, characterized in that, The operation further includes using a first secure mapping key to protect the relationship between the first identifier and the first avatar, and the operation further includes using a second secure mapping key to protect the relationship between the second identifier and the second avatar.

17. A method, characterized in that, It includes: A first avatar is generated or identified, the first avatar having a mapping to a first identifier, wherein the first avatar is embodied as a first computer program in the system and acts as one of a plurality of nodes in the system’s virtual social network; The query is transmitted to a first device associated with the first avatar, wherein the query request relates to information about the benefits of the first avatar's participation in a first virtual event in which the second avatar also participates; Information related to the benefits of the first avatar in relation to the first avatar's participation in the first virtual event in which the second avatar also participates is obtained from the first device associated with the first avatar, and the information is encoded by using a secure mapping key and assigned to the first avatar mapped to the first identifier, wherein at least a portion of the information is provided by at least one sensor that measures task-related activity or interaction information associated with at least one task-related activity or interaction between the first avatar and the second avatar; The information is associated with the first avatar mapped to the first identifier of the first avatar, wherein the first avatar is a virtual representation of the node within the system's virtual social network, the virtual social network containing the second avatar mapped to the second identifier of the second avatar, wherein the first avatar contains the node of the virtual social network, and the second avatar is embodied as a second computer program and contains another node of the virtual social network; By mapping the first avatar to the first identifier, the node of the first avatar is assisted in virtual task-related activities or interactions with the other node of the second avatar in the virtual social network based on task-related activities or interactions between the first computer program and the second computer program; By using an artificial intelligence system and based on the analysis of the information and the task-related activities or interactions, first conditional state data for the first avatar and second conditional state data for the second avatar are generated or identified and stored, wherein the first conditional state data for the first avatar is generated at least in part based on inputs generated by the second avatar that are associated with the first avatar and the virtual task-related activities or interactions between the node of the first avatar and the other node of the second avatar in the virtual social network; By using the artificial intelligence system and based on the first conditional state data for the first avatar, recommendations, media content, or a combination thereof are provided to the first avatar to improve the first avatar's benefit regarding a first future event in which the second avatar will participate, a second future event in which the second avatar is not present, or a combination thereof, wherein the recommendations, media content, the first conditional state data, or a combination thereof are accessed by using the secure mapping key; Based on the recommendations, media content, or a combination thereof, feedback is received from a user that relates to enhancing the effectiveness of the first avatar in at least one task-related activity or interaction in the first future event, the second future event, or a combination thereof; The artificial intelligence system is trained based on feedback from the user relating to the effectiveness of enhancing the first avatar's task-related activities or interactions in the first future event, the second future event, or a combination thereof; and By using the artificial intelligence system trained based on the feedback, new recommendations, new media content, or combinations thereof are provided to the first avatar to improve the effectiveness of the first avatar in a third future event.

18. The method according to claim 17, characterized in that, It further includes using machines to determine relative weights for the information to be used in the analysis.

19. The method according to claim 17, characterized in that, The information relating to the benefits of the first avatar includes preparation information, authenticity information, clarification information, evidence information, relevance information, respect information, public information, contribution information, participation information, credibility information, value information, any attribute information, any benefit information, or a combination thereof.

20. A non-transitory computer-readable device, characterized in that, It includes instructions that, when loaded and executed by the processor, cause the processor to perform operations including: A first avatar is generated or identified, the first avatar having a mapping to a first identifier, wherein the first avatar is embodied as a first computer program in the system and acts as one of a plurality of nodes in the system’s virtual social network; Generate a query for a first device associated with the first avatar, wherein the query request relates to information about the benefits of the first avatar in participating in a first virtual event in which the second avatar also participates; Receive information from the first device associated with the first avatar related to the benefits of the first avatar's participation in the first virtual event in which the second avatar also participates, wherein at least a portion of the information is provided by at least one sensor that measures task-related activity or interaction information associated with at least one task-related activity or interaction between the first avatar and the second avatar; The information is associated with the first avatar mapped to the first identifier of the first avatar, and the information assigned to the first avatar mapped to the first identifier is encoded by using a secure mapping key, wherein the first avatar is a virtual representation of the node within the virtual social network of the system, the virtual social network including the second avatar mapped to the second identifier of the second avatar, wherein the first avatar includes the node of the virtual social network, and the second avatar is embodied as a second computer program and includes another node of the virtual social network; By mapping the first avatar to the first identifier, the node of the first avatar is assisted in virtual task-related activities or interactions with the other node of the second avatar in the virtual social network based on task-related activities or interactions between the first computer program and the second computer program; Based on the analysis of the information and the task-related activities or interaction information, first conditional state data for the first avatar and second conditional state data for the second avatar are provided; The first incarnation is generated by using an artificial intelligence system and at least based on the first conditional state data for the first incarnation, in order to improve the first incarnation’s benefit with respect to a first future event in which the second incarnation will participate, a second future event in which the second incarnation will not participate, or a combination thereof, wherein the recommendations, media content, the first conditional state data, or the combination thereof are accessed by using the secure mapping key; Based on the recommendations, media content, or a combination thereof, feedback is received from a user that relates to enhancing the effectiveness of the first avatar in at least one task-related activity or interaction in the first future event, the second future event, or a combination thereof; The artificial intelligence system is trained based on feedback from the user relating to the effectiveness of enhancing the first avatar's task-related activities or interactions in the first future event, the second future event, or a combination thereof; and By using the artificial intelligence system trained based on the feedback, new recommendations, new media content, or combinations thereof are provided to the first avatar to improve the effectiveness of the first avatar in a third future event.

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