Program, information processing device, and information processing method

Abstract

To predict influence on psychological safety felt by an other person with satisfactory accuracy to effectively notify a participant of an advice for improving psychological safety.SOLUTION: A program according to an embodiment of the present invention makes a computer function as a sensibility reading unit, a participant information reading unit, a characteristics reading unit, an influence calculating unit, a selection unit, and a notification unit. The sensibility reading unit reads, from a storage device, sensibility information regarding psychological safety in a communication environment. The participant information reading unit reads, from the storage device, participant information for used in specifying a plurality of participants who participate in a first communication. The behavior characteristics reading unit reads, from the storage device, first behavior characteristics information on each of the participants specified by the participant information. The influence calculating unit calculates influence on each participant given to each other based on the sensibility information regarding the psychological safety and the first behavior characteristics information. The selection unit selects an advice for improving the psychological safety based on the influence. The notification unit notifies the notification targets of the advice.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] Embodiments of the present invention relate to a program, an information processing device, and an information processing method. [Background technology]

[0002] There is growing interest in psychological safety, which has been reported to be a common characteristic of highly productive workplaces. For example, techniques for tailoring advice to facilitate smooth meetings based on participants' sensitivities and providing guidance based on their words and actions have been known for some time. [Prior art documents] [Patent Documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-165118 [Overview of the project] [Problems that the invention aims to solve]

[0004] However, conventional technologies have made it difficult to more accurately predict the impact on how others perceive psychological safety and to more effectively provide advice to improve psychological safety. [Means for solving the problem]

[0005] The program of the embodiment causes the computer to function as a sensitivity reading unit, a participant information reading unit, a characteristic reading unit, an impact calculation unit, a selection unit, and a notification unit. The sensitivity reading unit reads sensitivity information of psychological safety in the communication environment from a storage device. The participant information reading unit reads participant information from the storage device that identifies a plurality of participants participating in the first communication. The behavioral characteristic reading unit reads first behavioral characteristic information of each participant identified by the participant information from the storage device. The impact calculation unit calculates the influence each participant has on each other from the psychological safety sensitivity information and the first behavioral characteristic information. The selection unit selects advice to improve psychological safety based on the influence. The notification unit notifies the recipient of the advice. [Brief explanation of the drawing]

[0006] [Figure 1] A diagram showing an example of the device configuration of the information processing system according to the first embodiment. [Figure 2] A diagram showing an example of the functional configuration of the information processing device according to the first embodiment. [Figure 3] A diagram showing examples of the behavioral characteristics of each participant in the first embodiment. [Figure 4] A diagram illustrating an example of the sensitivity of psychological safety in the communication environment of the first embodiment. [Figure 5] A flowchart illustrating an example of a method for initiating or processing information during communication according to the first embodiment. [Figure 6] A diagram showing an example of calculating the impact on the surroundings of the first embodiment. [Figure 7] A diagram showing an example of calculating the influence received from the surroundings in the first embodiment. [Figure 8] A figure illustrating an example of advice for the first embodiment. [Figure 9] A figure illustrating example 2 of advice for the first embodiment. [Figure 10] A flowchart illustrating an example of an information processing method after the completion of communication in the first embodiment. [Figure 11]A diagram showing an example of display information in the first embodiment. [Figure 12] A diagram showing an example of the functional configuration of the information processing apparatus in the second embodiment. [Figure 13] A diagram for explaining the behavior characteristic grasping process in the second embodiment. [Figure 14] A flowchart showing an example of the information processing method during the start of communication and during communication in the second embodiment. [Figure 15A] A diagram showing an example of the normal behavior characteristics of each participant in the second embodiment. [Figure 15B] A diagram showing an example of the actual behavior characteristics of each participant in the second embodiment. [Figure 16] A diagram showing an example of display information in the second embodiment. [Figure 17] A diagram showing an example of the functional configuration of the information processing apparatus in the third embodiment. [Figure 18] A diagram showing an example of the time required for the fluctuation range of the normal behavior characteristics of the notification target person in the third embodiment to return. [Figure 19] A diagram showing an example of display information in the fifth embodiment. [Figure 20] A diagram showing an example of the hardware configuration of the information processing apparatus according to the first to fifth embodiments.

Embodiments for Carrying Out the Invention

[0007] Hereinafter, embodiments of a program, an information processing apparatus, and an information processing method will be described in detail with reference to the accompanying drawings.

[0008] (First Embodiment) In the first embodiment, an information processing system operating as a conference support system will be described as an example. Note that this information processing system is not limited to remote conferences and offline conferences, and can also target any communication.

[0009] [Example of Device Configuration] Figure 1 shows an example of the device configuration of the information processing system 100 according to the first embodiment. The information processing system 100 according to the first embodiment comprises an information processing device 101, and a plurality of client devices such as a remote conference terminal 103, a conference room terminal 104, and a room smart speaker 105. The information processing device 101 and the plurality of client devices are connected by a network 102, such as the Internet.

[0010] The communication method of network 102 may be wired or wireless. Furthermore, network 102 may be configured using a combination of wired and wireless methods.

[0011] The remote conferencing terminal 103 is, for example, a personal computer with a remote conferencing application installed. The conference room terminal 104 is, for example, a terminal installed in a conference room. The room smart speaker 105 is, for example, a smart speaker that assists with casual conversations in a room.

[0012] The information processing device 101 of the first embodiment provides the functions of a conference support system to remote conference terminals 103, conference room terminals 104, and in-room smart speakers 105, etc., via the network 102.

[0013] [Example of functional configuration] Figure 2 is a diagram showing an example of the functional configuration of the information processing device 101 of the first embodiment. The information processing device 101 of the first embodiment includes a storage unit 300, a sensitivity reading unit 301, a participant information reading unit 302, a behavioral characteristics reading unit 303, an influence calculation unit 304, a selection unit 305, a notification unit 306, a behavioral characteristics calculation unit 307, an acquisition unit 308, a sensitivity calculation unit 309, and a display control unit 310.

[0014] The memory unit 300 is a memory device that stores various types of information. For example, each user's behavioral characteristics in communication and their sensitivity to psychological safety from their surroundings are stored in the memory unit 300 in advance. Also, for example, the memory unit 300 stores participant behavior data from past communications. Also, for example, the memory unit 300 stores the level of psychological safety each participant felt during each communication, such as a meeting.

[0015] Behavioral characteristics and sensitivities are updated, for example, by the behavioral characteristics calculation unit 307, acquisition unit 308, and sensitivity calculation unit 309 each time a communication in which a user has participated ends. Details of the updating method will be described later. Also, for example, behavioral characteristics and sensitivities are set by the user when the information processing device 101 is first used.

[0016] The sensitivity reading unit 301 reads sensitivity information regarding psychological safety in the communication environment from the memory unit 300. The sensitivity information regarding psychological safety will be described later.

[0017] The participant information reading unit 302 reads participant information from the storage unit 300 to identify multiple participants participating in the communication. For example, when meeting A is held and the participants are decided, the participant information reading unit 302 reads participant information from the storage unit 300 indicating that the user, Suzuki, Yamada, and Sato will participate.

[0018] The behavioral characteristics reading unit 303 reads the behavioral characteristics information of each participant, which is identified by the participant information, from the storage unit 300.

[0019] Figure 3 shows examples of the behavioral characteristics of each participant in the first embodiment. Each participant's behavioral characteristics are represented by information (e.g., a numerical value) that indicates the degree of at least one characteristic, along with an index of that characteristic. For example, indicators of behavioral characteristics include "interrupting," "speaking for long periods," "using many positive keywords," "using many negative keywords," "being quick-tempered," and "nodding in agreement."

[0020] In the example in Figure 3, "interrupting," "quick-tempered," "nodding," and "frequent use of positive keywords" are used as indicators. For example, person C's degree of "interrupting" is represented by +5, meaning that their degree of "interrupting" is higher than that of an average person (0).

[0021] Furthermore, the behavioral characteristics of each participant may be represented not by a numerical value indicating the strength or weakness of the relevant property, but by a logical value (0 or 1) indicating the presence or absence of the relevant property.

[0022] Returning to Figure 2, the influence calculation unit 304 calculates the influence each participant has on each other based on their sensitivity to psychological safety in the communication environment and their behavioral characteristics.

[0023] The selection unit 305 selects advice to improve psychological safety based on the impact calculated by the impact calculation unit 304.

[0024] The notification unit 306 notifies the recipient of the advice selected by the selection unit 305.

[0025] The behavioral characteristics calculation unit 307 calculates the behavioral characteristics of each participant from behavioral data in past communications (second communications). The behavioral characteristics calculation unit 307 can calculate the behavioral characteristics of participants from past behaviors identified from behavioral data, without requiring the user to set the behavioral characteristics.

[0026] For example, "interrupting" can be quantified by calculating the frequency of a participant starting to speak while another participant is still speaking (turn-taking frequency) from the speech and behavior data during the meeting. Specifically, the behavioral characteristic calculation unit 307 identifies speaker a from the video information, determines whether the speaker is in the middle of speaking or has finished speaking based on the intonation and intervals of the speech, and records that speaker b interrupted once if another speaker b starts speaking in the middle of speaking. The behavioral characteristic calculation unit 307 similarly counts the interruption events for each speaker and normalizes them by the length of the meeting to calculate the frequency of interruptions by each speaker per unit of time.

[0027] For example, "long speaking time," an indicator of speaking duration, is quantified by using the continuous speaking time from the speech data during the meeting. Specifically, the behavioral characteristic calculation unit 307 quantifies the continuous speaking time by measuring the speaking time of speaker a from the video information and measuring the time until someone other than speaker a starts speaking. The behavioral characteristic calculation unit 307 calculates the speaking rate per unit meeting by normalizing the quantified continuous speaking time by the length of the meeting.

[0028] For example, "a high number of positive keywords" can be quantified by the number of times positive keywords appear per unit of speaking time or per unit of meeting time. Specifically, the behavioral characteristic calculation unit 307 applies a speech content recognition device to the speech data during the meeting to convert the content of the speech into text information and compares it with predetermined positive keywords. This makes it possible to calculate the number of times positive keywords appear per unit of speaking time or per unit of meeting time.

[0029] Positive keywords are those that express agreement, such as "That's a good point" or "Please continue as you are."

[0030] Similarly, the statement "there are many negative keywords" can be quantified by measuring the frequency of negative keywords.

[0031] Negative keywords are those that express negation, such as "That's no good" or "Please reconsider."

[0032] These behavioral characteristic indicators are not limited to the examples above; any indicator that shows how one behaves in communication can be used. Furthermore, any method can be used to quantify these behavioral characteristics.

[0033] Figure 4 shows an example of the sensitivity to psychological safety in a communication environment according to the first embodiment. Sensitivity to psychological safety is evaluated based on an index of the nature of participants' behavior in the communication environment and includes information indicating the degree of increase or decrease in psychological safety in the communication environment. For example, as shown in Figure 4, sensitivity to psychological safety is calculated by the sensitivity calculation unit 309 from an index of the communication environment that represents the extent to which there were attendees exhibiting corresponding behavioral characteristics in meetings that each participant has previously attended, and information on how psychologically safe the participant felt about that meeting. The total value for each index of behavioral characteristics of the participant (e.g., attendees at the meeting) is used to quantify each index that evaluates the communication environment. Sensitivity to psychological safety is expressed by numerical values ​​along several indicators, as shown in Figure 4. Each numerical value represents the degree to which psychological safety increases or decreases in relation to the surrounding environment. Positive values ​​represent the degree to which psychological safety is improved, and negative values ​​represent the degree to which psychological safety is decreased.

[0034] In the example in Figure 4, participant A and participant B show their sensitivity to the communication environment, indicating how they perceive psychological safety in that environment. The combined value when participants A and B are present together is also shown. The combined sensitivity of the participants quantifies their perception of psychological safety.

[0035] In the example in Figure 4, the indicators used for behavioral characteristics are "being interrupted," "having an irritable person," "frequent nodding," and "using many positive keywords."

[0036] For example, participant A's score of -10 for "there are angry people" indicates that they are more likely to experience a decrease in psychological safety when angry people are present.

[0037] Furthermore, in the example in Figure 4, the sensitivity to psychological safety when participants A and B are present is quantified by the sum of the sensitivity values ​​of participants A and B.

[0038] As shown in Figure 4, sensitivity is stored numerically in the memory unit 300, indicating the degree to which the participant's psychological safety in relation to their surrounding environment increases or decreases, according to several indicators.

[0039] Psychological safety is measured by the acquisition unit 308. The acquisition unit 308 acquires the psychological safety each participant feels during communication and stores the acquired psychological safety in the storage unit 300, linked to user identification information.

[0040] Generally, psychological safety is thought to be fostered in a communication environment from the following perspectives: (1) When you make a mistake in a team, you are usually blamed. (2) Team members can point out challenges and difficult problems to each other. (3) Team members may reject others on the grounds that they are different from themselves. (4) It is safe to take actions that may be risky for the team. (5) It is difficult to ask other members of the team for help. (6) No team member intentionally belittles their own work. (7) When working with team members, I feel that my skills and talents are respected and utilized. (Source: Google re:Work guide: Understanding what makes an effective team)

[0041] The acquisition unit 308 acquires the psychological safety of each participant by detecting the contents of (1) to (7) using, for example, video recognition, voice recognition, and biometric information recognition. For example, the acquisition unit 308 quantifies item (1) by analyzing the content of statements made by those present after the report of the mistake. Alternatively, the acquisition unit 308 may acquire the psychological safety of the meeting from the user through a post-meeting questionnaire.

[0042] Alternatively, the acquisition unit 308 may obtain a quantitative value of psychological safety by analyzing the length of speaking time, the number of hesitations, and the number of calming gestures such as placing a hand on the chest using speech recognition, video recognition, and biometric information recognition. Specifically, the acquisition unit 308 determines that psychological safety is low / high if the speaking time in the target meeting is shorter / longer than the average speaking time in similar meetings (e.g., regular meetings) that the user has participated in in the past.

[0043] The sensitivity calculation unit 309 calculates sensitivity parameters such as "being interrupted," "having an irritable person," "frequent nodding," and "many positive keywords." These sensitivity parameters are calculated from an indicator of the communication environment, which represents the extent to which attendees exhibited the corresponding behavioral characteristics in meetings each participant had previously attended, and information on the psychological safety they felt in those meetings.

[0044] For example, after communication has ended, the sensitivity calculation unit 309 calculates the sensitivity information for psychological safety using a psychological safety model that models the relationship between psychological safety acquired by the acquisition unit 308, an indicator of the communication environment, and the sensitivity information for psychological safety.

[0045] The following shows an example of how the relationship between psychological safety, sensitivity, and the communication environment is modeled using a linear model by the system (for example, the sensitivity calculation unit 309) in the sensitivity calculation unit 309. Note that the system performing the modeling may be a separate device from the information processing device 101.

[0046] The psychological safety y that users feel in a meeting is related to the sensitivity a of the i-th indicator modeled by the system. i And the corresponding communication environment indicator x i The score obtained by multiplying by and is estimated by summing the results over all indicators i∈I used in the model (Equation (1) below).

[0047]

number

[0048] The correct value of psychological safety y analyzed in past conferences j∈J ~ j And y estimated by the system j The sensitivity a that minimizes the difference from i This is adjusted by the following formula (2).

[0049]

number

[0050] Furthermore, the model illustrating the relationship between psychological safety, sensitivity, and the communication environment is not limited to a linear model; it may be represented by any arbitrary modeling method.

[0051] As a variation in modeling, for example, the influence of average behavioral characteristics (workplace culture) for each workplace k is considered. k You may also add a bias towards the communication environment. For example, an offset c that represents the person's perception of metric i. i You may also add an offset d that represents the individual's perceived psychological safety, independent of any indicator.

[0052] An example of a variation in modeling is shown in equation (3) below.

[0053]

number

[0054] Note that for influence b k and offset c i and offset d, part of them may be used for modeling.

[0055] Thus, in the first embodiment, even if the user does not set the sensitivity information himself / herself, the sensitivity calculation unit 309 can calculate the sensitivity information of psychological safety using the psychological safety model from the index of the communication environment (e.g., a meeting, etc.) participated in the past and the psychological safety felt at that time.

[0056] [Example of information processing method] FIG. 5 is a flowchart showing an example of an information processing method before the start of communication in the first embodiment. First, the participant information reading unit 302 reads, from the storage unit 300, the participant information that identifies a plurality of participants participating in the communication (step S1).

[0057] Next, the behavior characteristic reading unit 303 reads, from the storage unit 300, the behavior characteristic information of each participant identified by the participant information (step S2).

[0058] Next, the sensitivity reading unit 301 reads, from the storage unit 300, the sensitivity information of psychological safety in the communication environment (step S3).

[0059] Next, the influence calculation unit 304 reads, from the storage unit 300, the above-described psychological safety model (step S4).

[0060] [[ID=#33]]Next, the influence calculation unit 304 uses the psychological safety model to calculate the influence that each participant has on each other from the sensitivity information of psychological safety in the communication environment and the behavior characteristic information of each participant (step S5).

[0061] Figure 6 shows an example of calculating the impact on the surroundings in the first embodiment. In the example in Figure 6, the impact that participants c and d have on their surroundings is represented by scores calculated based on a psychological safety model expressed as a linear model. The sensitivity of the surroundings represents the sum of the sensitivities of the participants other than c, and corresponds to the sum of the sensitivity examples in Figure 4 above. For example, for the behavioral characteristic index of c, "being interrupted" (+5), the impact score of c on the surroundings is (-4) × (+5) = (-20).

[0062] Figure 7 shows an example of calculating the influence received from the surroundings in the first embodiment. In the example in Figure 7, the influence received from the surroundings of participants C and D is represented by a score. In the example in Figure 7, the influence received from the surroundings of participants C and D is represented by a score calculated based on a psychological safety model represented by a linear model. The behavioral characteristics of the surroundings represent the sum of the behavioral characteristics of participants other than C. For example, for the sensitivity index of C, "being interrupted" (-2), the influence score received from the surroundings of C is (+5) × (-2) = (-10).

[0063] Returning to Figure 5, the selection unit 305 then determines whether or not it is necessary to notify the participants based on the impact calculated in step S5 (step S6). Specifically, the selection unit 305 refers to the storage unit 310 and selects advice to notify the participants based on the impact calculated in step S5. If there is advice to be notified, it is determined that it is necessary to notify the recipients of that advice.

[0064] Figure 8 shows an example of advice 1 of the first embodiment. Figure 9 shows an example of advice 2 of the first embodiment. As shown in Figures 8 and 9, the storage unit 310 stores advice according to the degree of influence of various indicators of behavioral characteristics.

[0065] In the examples in Figures 8 and 9, advice is stored in a database divided into three categories (low, medium, and high) according to the magnitude of the influence score (degree of influence). Note that the categories are not limited to low, medium, and high; any two or five categories may be used, or there may be no categories at all. Advice based on a continuous value N, such as "Try counting to N seconds when you feel like you're about to get angry," may also be provided.

[0066] In addition to users registering for the advice, it may also be distributed via the network by the service provider.

[0067] The selection unit 305 selects one or more pieces of advice from those stored in the database. For example, the selection unit 305 selects the participant with the highest score among the scores of influence received by other participants as the notification target, and selects the advice for the category corresponding to that highest influence score.

[0068] For example, the selection unit 305 selects the participant whose influence score is the highest among the scores of the influence a participant has on other participants as the person to be notified, and selects the advice category corresponding to that highest score.

[0069] Furthermore, the selected advice is not limited to the advice corresponding to the top score, but may also be advice corresponding to the top n scores. In addition, the selection is not limited to advice corresponding to the top score category, but may also include advice corresponding to the bottom score category.

[0070] Returning to Figure 5, if advice is needed (Step S6, Yes), the notification unit 306 notifies one or more recipients of the advice (Step S7). If advice is not needed (Step S6, No), the process ends.

[0071] Figure 10 is a flowchart illustrating an example of the information processing method after the completion of communication in the first embodiment. First, the behavioral characteristics calculation unit 307 calculates behavioral characteristics from the behavioral data of each participant in the communication (for example, meeting A) after the communication has ended (step S21).

[0072] Next, the acquisition unit 308 reads the psychological safety that the participant felt during the communication from the memory unit 300 (step S22). The participant's psychological safety is periodically acquired by the acquisition unit 308 during the communication and stored in the memory unit 301.

[0073] Next, the sensitivity calculation unit 309 calculates the sensitivity in the communication based on the behavioral characteristics calculated in step S21 and the psychological safety read in step S22 (step S23).

[0074] Next, the memory unit 300 stores the information indicating the behavioral characteristics calculated in step S21 and the information indicating the sensitivity calculated in step S23, together with participant information that identifies the participant (step S24).

[0075] Returning to Figure 2, the display control unit 310 controls the display of the information to a client device or the like.

[0076] [Example of displayed information] Figure 11 shows an example of display information according to the first embodiment. The example in Figure 11 shows a case where the above-mentioned advice notification function is incorporated into the UI (User Interface) screen of a schedule management application.

[0077] In the example shown in Figure 11, the display control unit 310 displays a details screen when it receives a click on a specific event on the schedule screen. The details screen shows the details of the event and the relationship between the participants and the user who are scheduled to attend.

[0078] The example in Figure 11 shows a scenario where four participants (User, Suzuki, Yamada, and Sato) are participating in a communication. The arrows on the details screen indicate the mutual influence between them. The display control unit 310 displays display information (first display information) on the display device with an icon superimposed to highlight the notification when the influence exceeds a predetermined level. In the example in Figure 11, relationships that have an influence above a certain level are highlighted with an exclamation mark icon. By hovering the mouse over the arrow highlighted with the exclamation mark, corresponding advice is displayed. This allows notifications to be highlighted so that they catch the user's eye when particular attention is needed.

[0079] Furthermore, the form of communication is not limited to meetings; it can also be one-on-one meetings, regular meetings, presentations, informal chats, and phone calls. The scale of the communication is also at the discretion of the participants. In addition, communication may take place online, or it may be a hybrid meeting including both online and in-person participants.

[0080] As described above, in the information processing device 101 of the first embodiment, the sensitivity reading unit 301 reads sensitivity information regarding psychological safety in the communication environment from the storage device (storage unit 300 in the first embodiment). The participant information reading unit 302 reads participant information from the storage device to identify a plurality of participants participating in the first communication. The behavioral characteristics reading unit 303 reads first behavioral characteristics information for each participant identified by the participant information from the storage device. The influence calculation unit 304 calculates the influence that each participant has on each other from the sensitivity information regarding psychological safety and the first behavioral characteristics information. The selection unit selects advice to improve psychological safety based on the influence. Then, the notification unit 306 notifies the recipient of the advice.

[0081] As a result, according to the first embodiment, it is possible to predict with greater accuracy the impact on the psychological safety perceived by others and to more effectively provide advice to improve psychological safety. For example, the impact on each participant can be predicted in advance from the behavioral characteristics information of each participant in a communication such as a meeting and the information on their sensitivity to psychological safety. Specifically, for participants who feel psychologically unsafe, advice can be given before they fall into an unsafe situation, encouraging them to respond with composure. Also, for perpetrators who create unsafe environments for those around them, advice can be given in advance while they are in a calm state of mind. This provides an opportunity to efficiently review communication.

[0082] Furthermore, with conventional technologies, for example, advice is determined by behavioral data and advice rules, so there is no adjustment based on the combination of participants present. In other words, it was not possible to provide appropriate advice to participants based on each participant's sensitivity to psychological safety, specifically "how they felt after receiving the words and actions."

[0083] On the other hand, according to the first embodiment, by modeling the behavioral characteristics of participants and their sensitivity to psychological safety based on the behavior of those around them, it is possible to provide advice at a predetermined time when participant information is available. In other words, advice can be given before participants fall into psychologically unsafe situations, giving them time to prepare themselves mentally in advance. Furthermore, perpetrators who put others in unsafe situations can be advised in advance while they are in a calm state of mind, and their behavioral characteristics can be efficiently reviewed.

[0084] (Second Embodiment) Next, the second embodiment will be described. In the description of the second embodiment, explanations similar to those of the first embodiment will be omitted, and the differences from the first embodiment will be explained. The difference between the second embodiment and the first embodiment is that the second embodiment is further equipped with a function to grasp the actual behavioral characteristics based on information during communication.

[0085] [Example of functional configuration] Figure 12 shows an example of the functional configuration of the information processing device 101-2 of the second embodiment. The information processing device 101-2 of the second embodiment has an additional gripping unit 401 in addition to the configuration of the information processing device 101 of the first embodiment.

[0086] The recognition unit 401 recognizes the behavioral characteristics of participants during communication (for example, during a meeting) based on the participants' behavior during the communication. In contrast to the behavioral characteristic calculation unit 307 of the first embodiment, which calculates behavioral characteristics (first behavioral characteristic information) from the behavioral data of each participant in past meetings, the recognition unit 401 of the second embodiment calculates behavioral characteristics at a certain frequency or always, without waiting for the meeting to end.

[0087] Figure 13 is a diagram illustrating the process for determining behavioral characteristics in the second embodiment. The period 411 from the start time of the meeting to the end time of the meeting indicates the period during which the behavioral characteristics calculation unit 307 calculates the behavioral characteristics of the participants.

[0088] The information gathering unit 401 uses a sliding window with a fixed time width 412 prior to the current time as an input window to extract a time period for understanding the participants' behavior, and calculates the behavioral characteristics of the participants during the extracted time period. This makes it possible to understand the behavioral characteristics of the participants without waiting for the meeting to end.

[0089] The method for calculating behavioral characteristics by the grasping unit 401 and the method for calculating behavioral characteristics by the behavioral characteristics calculation unit 307 may be different. For example, the models and coefficients used to calculate behavioral characteristics in the grasping unit 401 and the behavioral characteristics calculation unit 307 may be different.

[0090] [Examples of information processing methods] Figure 14 is a flowchart illustrating an example of the communication initiation and information processing method during communication according to the second embodiment. First, the participant information reading unit 302, behavioral characteristics reading unit 303, sensitivity reading unit 301, and influence calculation unit 304 pre-load participant information, behavioral characteristics information, psychological safety sensitivity information, and a psychological safety model (step S31).

[0091] Next, the information gathering unit 401 grasps the behavioral characteristics of the participants from their behavior during communication (for example, during a meeting) (step S32).

[0092] Next, the influence calculation unit 304 uses a psychological safety model to calculate the influence each participant has on each other, based on the sensitivity information for psychological safety in the communication environment and the behavioral characteristic information of each participant obtained in step S32 (step S33).

[0093] Next, the selection unit 305 determines whether or not it is necessary to notify the participants based on the impact calculated in step S33 (step S34). In the second embodiment, the timing at which it is determined that notification is necessary (timing of notification to the recipients) may be changed to take into account the impact based on the behavioral characteristics during communication.

[0094] Specifically, the selection unit 305 determines the timing of notification to the recipient based on their usual behavioral characteristics and their behavioral characteristics during communication, and selects advice at that notification timing. For example, the selection unit 305 selects advice when the second behavioral characteristic information described above shows a change that exceeds a threshold determined based on the first behavioral characteristic information described above.

[0095] Figure 15A shows an example of the usual behavioral characteristics of each participant in the second embodiment. In the example in Figure 15A, the usual behavioral characteristics are represented by the average behavioral characteristic value and the variance. For example, for the index of "irritable," person c's usual behavioral characteristics are represented by the average behavioral characteristic value of 0 and the variance of ±1.

[0096] Figure 15B shows an example of the actual behavioral characteristics (behavioral characteristics acquired during communication) of each participant in the second embodiment. The selection unit 305 selects advice when the behavioral characteristics acquired during communication show a change that exceeds a threshold determined based on the usual behavioral characteristics. The threshold is determined, for example, by considering the variance of the usual behavioral characteristics. For example, in the case of person c, the threshold is 1 because the usual behavioral characteristics are 0 ± 1. In the example in Figure 15B, person c's actual behavioral characteristics are +2, so it exceeds the threshold = 1. Therefore, the selection unit 305 selects advice for person c.

[0097] This allows for earlier notification of advice to both a person who is usually quick to get angry (person d in the example in Figure 15A) and a person who is usually not quick to get angry (person c in the example in Figure 15A), even when the latter is likely to get angry.

[0098] Returning to Figure 14, if advice is needed (Step S6, Yes), the notification unit 306 notifies one or more recipients of the advice (Step S35).

[0099] If no advice is needed (Step S6, No), the grasping unit 401 determines whether communication has ended (Step S36). If communication has not ended (Step S36, No), the processes in Steps S32 to S36 are repeated at predetermined intervals. If communication has ended (Step S36, Yes), the process ends.

[0100] [Example of displayed information] Figure 16 shows an example of display information in the second embodiment. The example in Figure 16 shows a case where the above-mentioned advice notification function is incorporated into the UI screen of a schedule management app. In the detail screen of the second embodiment, for individuals whose behavioral characteristics have been updated during communication, the degree of improvement or deterioration is displayed with upward or downward arrows.

[0101] The mutual influences are indicated by arrows, as in the first embodiment. Relationships that influence each other to a certain degree or higher are highlighted with an exclamation mark (!). Hovering over an arrow with the mouse displays corresponding advice.

[0102] As explained above, according to the second embodiment, it becomes possible to provide more timely advice based on the participant's behavioral characteristics estimated from past behavioral tendencies and the behavioral characteristics calculated from their current behavior in communication (behavioral characteristics that more accurately reflect reality). In other words, it becomes possible to provide more timely advice based not only on pre-set behavioral characteristics and past tendencies, but also on the actual behavioral characteristics during communication and the sensitivities of those around the participant.

[0103] (Third embodiment) Next, a third embodiment will be described. In the description of the third embodiment, explanations similar to those of the first embodiment will be omitted, and the differences from the first embodiment will be described. The difference between the third embodiment and the second embodiment is that the third embodiment further includes a function to adjust the advice stored in the memory unit 300 based on whether or not a change occurred in the behavioral characteristics before and after the notified advice.

[0104] [Example of functional configuration] Figure 17 shows an example of the functional configuration of the information processing device 101-3 of the third embodiment. The information processing device 101-3 of the third embodiment has an additional adjustment unit 501 in addition to the configuration of the information processing device 101 of the first embodiment.

[0105] The adjustment unit 501 adjusts the advice notified to the notified person based on whether or not there has been a change in the behavioral characteristics of the notified person before and after the advice has been notified. For example, the adjustment unit 501 adjusts the strength of the advice based on the length of time it takes for the advice notified by the notification unit 306 to take effect. Specifically, the adjustment unit 501 adjusts the strength of the advice notified when the notified person meets similar advice conditions in the future, based on the length of time required from the time of advice notification until the behavioral characteristics return to the normal range of fluctuation of the notified person's behavioral characteristics (see Figure 18).

[0106] Figure 18 shows an example of the time required for the notified person to return to the normal range of behavioral characteristics in the third embodiment. The adjustment is made by changing to advice in one or more adjacent categories in Figures 8 and 9 described above. For example, even if the notified person has a moderate influence on other participants (or the influence the notified person receives from other participants), if the time required to take effect is longer than a predetermined time, the adjustment unit 501 makes an adjustment to give high-level advice. Conversely, even if the notified person has a moderate influence on other participants (or the influence the notified person receives from other participants), if the time required to take effect is shorter than a predetermined time, the adjustment unit 501 makes an adjustment to give low-level advice.

[0107] According to the third embodiment, the strength of the advice can be adjusted for each user (e.g., meeting participants) depending on whether or not there is a change in their behavior in response to the advice, thereby preventing the advice from providing excessive or insufficient feedback.

[0108] (Fourth Embodiment) Next, the fourth embodiment will be described. In the description of the fourth embodiment, explanations similar to those of the first embodiment will be omitted, and the differences from the first embodiment will be described. The difference between the fourth embodiment and the first embodiment is that conditional behavioral characteristics and conditional sensitivity are used.

[0109] The behavioral characteristics reading unit 303 of the fourth embodiment reads conditional behavioral characteristics in addition to the behavioral characteristics of individual participants. Even for the same participant, the behavioral characteristics may change depending on the combination with other participants (for example, participants attending the meeting). Conditional behavioral characteristics are behavioral characteristics based on the combination of participants participating in the communication.

[0110] Conditional behavioral characteristics may include behavioral characteristics that differ not only depending on the combination with a specific person, but also depending on the combination with a specific attribute (for example, superior, subordinate, new employee, seniority, and gender).

[0111] In the first embodiment, the behavioral characteristics are calculated from the behavior in past communication situations. On the other hand, the conditional behavioral characteristics are calculated by aggregating the behavioral characteristics in communication situations that satisfy predetermined conditions (for example, combinations of participants attending a meeting) based on participant information and behavioral characteristic information stored in the memory unit 300. In other words, in the fourth embodiment, the behavioral characteristic calculation unit 307 calculates the conditional behavioral characteristics for each communication situation that satisfies the predetermined conditions.

[0112] Similarly, the sensitivity reading unit 301 of the fourth embodiment also reads conditional sensitivity. Even for the same participant, sensitivity may change depending on the combination with other participants. Conditional sensitivity is sensitivity based on the combination of participants participating in the communication.

[0113] Conditioned sensitivity, like conditional behavioral characteristics, is calculated from information on communication situations that satisfy predetermined conditions. In other words, in the fourth embodiment, the sensitivity calculation unit 309 calculates conditional sensitivity by modeling the relationship between psychological safety, sensitivity, and the communication environment for each communication situation that satisfies predetermined conditions. Then, the influence calculation unit 304 calculates the influence each participant has on each other from the conditional sensitivity information and the conditional behavioral characteristics information.

[0114] According to the fourth embodiment, more appropriate advice can be given based on more detailed conditions (conditional behavioral characteristics and conditional sensitivities that differ depending on the combination of participants, etc.) than in the first embodiment.

[0115] (Fifth embodiment) Next, the fifth embodiment will be described. In the description of the fifth embodiment, explanations similar to those of the fourth embodiment will be omitted, and the differences from the fourth embodiment will be described. The difference between the fifth embodiment and the fourth embodiment is that it further includes a function to display past notifications to participants and their subsequent behavioral characteristics. That is, the display control unit 310 further displays display information (second display information) on the display device, which includes the relationship between changes in each participant's behavioral characteristics and advice previously notified.

[0116] [Example of displayed information] Figure 19 shows an example of display information in the fifth embodiment. Figure 19 shows an example of an administration screen that can be viewed by a person who has the authority to check the communication information of each member of the group (e.g., an administrator). The administration screen provides a function that allows the user to view a list of the behavioral characteristics of each member of the group and the advice notified by the notification unit 306.

[0117] The history of advice recorded in the memory unit 300 is displayed with arrows, and details are displayed when the mouse hovers over or clicks on the arrow.

[0118] Behavioral characteristics 1 and 2 in Figure 19 represent two different conditional behavioral characteristics. Similarly, sensitivities 1 and 2 represent two different conditional sensitivities.

[0119] Furthermore, the management screen shown in Figure 19 may be equipped with a function to detect changes in the trends of various indicators and issue alerts. In order to detect trend changes, a settings screen may be provided that accepts detection conditions from the user, such as a drop below a predetermined percentage compared to the previous day.

[0120] According to the fifth embodiment, for example, the communication situation of a group can be grasped more easily. Specifically, a manager or other person can check the advice given by the notification unit 306 and the changes in behavior when such advice is received. This makes it possible to detect early changes in the trend of psychological safety felt by each member, as well as members who are repeatedly receiving advice.

[0121] Finally, we will describe examples of the hardware configurations of the information processing devices 101 (101-2, 101-3) according to the first to fifth embodiments.

[0122] [Example hardware configuration] Figure 20 shows examples of the hardware configuration of the information processing device 101 (101-2, 101-3) according to the first to fifth embodiments. The information processing device 101 (101-2, 101-3) comprises a processor 601, main memory 602, auxiliary storage 603, display device 604, input device 605, and communication device 606. The processor 601, main memory 602, auxiliary storage 603, display device 604, input device 605, and communication device 606 are connected via a bus 610.

[0123] Furthermore, the information processing device 101 (101-2, 101-3) may not be equipped with some of the above configurations. For example, if the information processing device 101 (101-2, 101-3) can utilize the input and display functions of an external device, the information processing device 101 (101-2, 101-3) may not be equipped with the display device 604 and the input device 605.

[0124] The processor 601 executes the program read from the auxiliary storage device 603 into the main memory 602. The main memory 602 is memory such as ROM (Read Only Memory) and RAM (Random Access Memory). The auxiliary storage device 603 is such as an HDD (Hard Disk Drive) and a memory card.

[0125] The display device 604 is, for example, a liquid crystal display. The input device 605 is an interface for operating the information processing device 101 (101-2, 101-3). The display device 604 and the input device 605 may be implemented by a touch panel or the like that has both display and input functions. The communication device 606 is an interface for communicating with other devices.

[0126] For example, a program executed by the information processing device 101 (101-2, 101-3) is provided as a computer program product in an installable or executable file format, recorded on a computer-readable storage medium such as a memory card, hard disk, CD-RW, CD-ROM, CD-R, DVD-RAM, and DVD-R.

[0127] Alternatively, for example, the information processing device 101 (101-2, 101-3) may be configured to store the program on a computer connected to a network such as the Internet, and provide it by allowing users to download it via the network.

[0128] Alternatively, for example, the information processing device 101 (101-2, 101-3) may be configured to provide the program via a network such as the Internet without requiring downloads. Specifically, it may be configured, for example, as an ASP (Application Service Provider) type cloud service.

[0129] Alternatively, for example, the information processing device 101 (101-2, 101-3) may be configured to be provided pre-installed in ROM or the like.

[0130] The programs executed by the information processing device 101 (101-2, 101-3) are configured as modules that include functions that can also be implemented by programs, among the functional configurations described above. In actual hardware terms, each of these functions is loaded onto the main memory 602 by the processor 601 reading and executing a program from the storage medium. In other words, each of these functional blocks is generated on the main memory 602.

[0131] Furthermore, some or all of the above-mentioned functions may be implemented using hardware such as an IC (Integrated Circuit) instead of software.

[0132] Alternatively, each function may be implemented using multiple processors 601, in which case each processor 601 may implement one of the functions, or two or more of the functions.

[0133] While several embodiments of the present invention have been described, these embodiments are presented as examples only and are not intended to limit the scope of the invention. These novel embodiments can be carried out in a variety of other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their variations are included in the scope and spirit of the invention, as well as in the claims of the invention and its equivalents. [Explanation of Symbols]

[0134] 100 Information Processing Systems 101 Information Processing Device 102 Network 103 Remote meeting terminal 104 Conference Room Terminal 105 Smart speaker in living room 300 Storage section 301 Sensitivity reading section 302 Participant Information Loading Section 303 Behavioral Characteristics Reading Unit 304 Impact Calculation Unit 305 Selection Section 306 Notification Department 307 Behavior Characteristics Calculation Unit 308 Acquisition Department 309 Sensitivity calculation section 310 Display Control Unit 401 Grasping part 501 Adjustment section 601 Processor 602 Main storage 603 Auxiliary storage device 604 Display device 605 Input device 606 Communication equipment 610 Bus

Claims

1. Computers, A sensitivity reading unit reads sensitivity information regarding psychological safety in a communication environment from a storage device, A participant information reading unit reads participant information from the storage device to identify multiple participants participating in the first communication, A behavioral characteristics reading unit reads first behavioral characteristics information of each participant identified by the participant information from the storage device, An influence calculation unit calculates the influence each participant has on others based on the aforementioned psychological safety sensitivity information and the aforementioned first behavioral characteristic information. Based on the aforementioned effects, a selection unit selects advice to improve psychological safety, It functions as a notification unit that notifies the recipient of the aforementioned advice, The first behavioral characteristic information includes, for each index of the behavioral properties, information representing the degree of the behavioral properties, The aforementioned information on the sensitivity of psychological safety is evaluated based on indicators of the nature of the participants' behavior in the communication environment and includes information indicating the degree of increase or decrease in psychological safety in the communication environment. program.

2. The aforementioned computer, Furthermore, it functions as a behavioral characteristic calculation unit that calculates the aforementioned first behavioral characteristic information for each participant from behavioral data from the second communication that took place in the past. The program according to claim 1.

3. The aforementioned computer, An acquisition unit that acquires the psychological safety felt by each participant during the first communication and stores the acquired psychological safety in the memory device, After the first communication is completed, the system is further configured to function as a sensitivity calculation unit that calculates the sensitivity information for psychological safety using a psychological safety model that models the relationship between the psychological safety acquired by the acquisition unit, the indicators of the communication environment, and the sensitivity information for psychological safety. The program according to claim 1.

4. The aforementioned computer, Based on the behavior of the participants during the first communication, the system further functions as a recognition unit that grasps second behavioral characteristic information indicating the behavioral characteristics of each participant during the first communication. The selection unit selects an advice when the second behavioral characteristic information shows a change that exceeds a threshold determined based on the first behavioral characteristic information. The program according to claim 1.

5. The aforementioned computer, Based on whether or not a change occurred in the behavioral characteristics of the person notified before and after the advice was given, the system further functions as an adjustment unit to adjust the advice given to the person notified. The program according to claim 1.

6. The behavioral characteristics reading unit reads conditional behavioral characteristics information based on the combination of participants participating in the first communication. The sensitivity reading unit reads conditional sensitivity information based on the combination of participants participating in the first communication, The influence calculation unit calculates the influence each participant has on the others based on the conditional sensitivity information and the conditional behavioral characteristic information. The program according to claim 1.

7. The aforementioned computer, If the aforementioned effect exceeds a predetermined degree, the display control unit further functions to display first display information on the display device, on which an icon emphasizing the notification is superimposed. The program according to claim 1.

8. The display control unit further displays second display information on the display device, including the relationship between changes in each participant's behavioral characteristics and advice previously given. The program according to claim 7.

9. A sensitivity reading unit reads sensitivity information regarding psychological safety in a communication environment from a storage device, A participant information reading unit reads participant information from the storage device to identify multiple participants participating in the first communication, A behavioral characteristics reading unit reads first behavioral characteristics information of each participant identified by the participant information from the storage device, An influence calculation unit calculates the influence each participant has on others based on the aforementioned psychological safety sensitivity information and the aforementioned first behavioral characteristic information. Based on the aforementioned effects, a selection unit selects advice to improve psychological safety, The system includes a notification unit that notifies the person to whom the advice is to be given, The first behavioral characteristic information includes, for each index of the behavioral properties, information representing the degree of the behavioral properties, The aforementioned information on the sensitivity of psychological safety is evaluated based on indicators of the nature of the participants' behavior in the communication environment and includes information indicating the degree of increase or decrease in psychological safety in the communication environment. Information processing device.

10. The information processing device reads information on the sensitivity of psychological safety in a communication environment from a storage device, The information processing device reads participant information from the storage device that identifies a plurality of participants participating in the first communication, The information processing device reads from the storage device the first behavioral characteristic information of each participant identified by the participant information, The information processing device performs the step of calculating the influence each participant has on each other based on the psychological safety sensitivity information and the first behavioral characteristic information. The information processing device includes the step of selecting advice to improve psychological safety based on the influence, The information processing device includes the step of notifying the person to be notified of the advice, The first behavioral characteristic information includes, for each index of the behavioral properties, information representing the degree of the behavioral properties, The aforementioned information on the sensitivity of psychological safety is evaluated based on indicators of the nature of the participants' behavior in the communication environment and includes information indicating the degree of increase or decrease in psychological safety in the communication environment. Information processing methods.

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